ISSN 0970-6380 Online ISSN 0976-2434 Journal of Food ...isprd.in/journal_31052014.pdf26. Studies on...

Indian Society of Pulses Research and DevelopmentIndian Institute of Pulses Research

Kanpur, India

Number 3 & 4

of

Journal

Food Legumes

September - December 2013

I SPR D1987

ISSN0970-6380

Online ISSN0976-2434

www.isprd.in

Volume 26

The Indian Society of Pulses Research andDevelopment (ISPRD) was founded in April 1987 with thefollowing objectives: To advance the cause of pulses research To promote research and development, teaching and

extension activities in pulses To facilitate close association among pulse workers

in India and abroad To publish “Journal of Food Legumes” which is the

official publication of the Society, published four timesa year.

Membership : Any person in India and abroad interestedin pulses research and development shall be eligible formembership of the Society by becoming ordinary, life orcorporate member by paying respective membership fee.Membership Fee Indian (Rs.) Foreign (US $)Ordinary (Annual) 350 25Life Member 3500 200Admission Fee 20 10Library/ Institution 3000 100Corporate Member 5000 -

INDIAN SOCIETY OF PULSES RESEARCH AND DEVELOPMENT(Regn. No.877)

The contribution to the Journal, except in case ofinvited articles, is open to the members of the Societyonly. Any non-member submitting a manuscript will berequired to become annual member. Members will beentitled to receive the Journal and other communicationsissued by the Society.

Renewal of subscription should be done in Januaryeach year. If the subscription is not received by February15, the membership would stand cancelled. Themembership can be revived by paying readmission fee ofRs. 10/-. Membership fee drawn in favour of Treasurer,Indian Society of Pulses Research and Development,through M.O./D.D. may be sent to the Treasurer,Indian Society of Pulses Research and Development,Indian Institute of Pulses Research, Kanpur 208 024,India. In case of outstation cheques, an extra amount ofRs. 40/- may be paid as clearance charges.

EXECUTIVE COUNCIL : 2013-2015

Zone I : Dr Brij Nandan(SKUAST) Sambha (J&K)

Zone II : VacantZone III : VacantZone IV : Dr OP Khedar

Durgapura, Jaipur, Rajasthan

Councillors

Dr Jagdish Singh, IIPR, KanpurDr A Amarendra Reddy, ICRISAT, HyderabadDr CS Praharaj, IIPR, Kanpur

Chief PatronDr S Ayyappan

PatronDr SK Datta

Co-patronDr N Nadarajan

Zone V : Dr DK PatilBadnapur

Zone VI : VacantZone VII : VacantZone VIII : Dr Devraj Mishra

IIPR, Kanpur, U.P.

Dr IP Singh, IIPR, KanpurDr Mohd Akram, IIPR, Kanpur

PresidentDr NP Singh

SecretaryDr GP Dixit

Joint SecretaryDr KK Singh

TreasurerDr KK Singh (Acting)

Vice PresidentDr Guriqbal Singh

Editors

Journal of Food Legumes(Formerly Indian Journal of Pulses Research)

Vol. 26 (3 & 4) September - December 2013

CONTENTSRESEARCH PAPERS

1. Heavy metal toxicity to food legumes: effects, antioxidative defense and tolerance mechanisms 1

Navneet Kaur and Harsh Nayyar

2. Assessment of genetic diversity at molecular level in mungbean (Vigna radiata (L.) Wilczek) 19

S. K. Gupta, R. Bansal, U. J. Vaidya and T. Gopalakrishna

3. Effectiveness and efficiency of gamma rays and Ethyl Methane sulphonate (EMS) in mungbean 25

Kuldeep Singh and M.N. Singh

4. Combining ability analysis in medium duration CGMS based hybrid pigeonpea (Cajanus cajan (L.) Millsp.,) 29

M. P. Meshram, A.N. Patil and Abhilasha Kharkar

5. Genetic variability, character association and path analysis in clusterbean (Cyamopsis tetragonoloba (L.) Taub) 34

A. Manivannan and C. R. Anandakumar

6. Genetic analysis for quantitative traits in pigeonpea (Cajanus Cajan L. Millsp.) 38

C. K. Chethana, P. S. Dharmaraj, R. Lokesha, G. Girisha, S, Muniswamy, Yamanura,Niranjana Kumar and D. H. Vinayaka

7. Genetic variabilty and association studies in cowpea (Vigna unguiculata L. walp.) 42

Hasan Khan, K. P. Vishwanatha and H.C. Sowmya

8. Yield and yield attributes of hybrid pigeonpea (ICPH 2671) grown for seed purpose as influenced by 46

plant density and irrigation

M.G. Mula, KB Saxena, A. Rathore and R.V. Kumar

9. Influence of organic nutrient sources on growth, seed yield and economics of cowpea under 51

mid hills of Arunachal Pradesh

V.K. Choudhary, P. Suresh Kumar and R. Bhagawati

10. Pathogenic variation and compatibility groups in Sclerotium rolfsii isolates causing collar rot on 55

chickpea (Cicer arietinum L.)

O.M. Gupta, Sachin Padole and Madhuri Mishra

11. Efficacy of bioinoculants in combination with insecticides against insect pests of 59

blackgram Vigna Mungo (L.) HepperP.S. Singh and V. Chourasiya

12. Studies on insecticide efficacy and application schedule for management of blister beetles on greengram 63

K.S. Pawar, Sarika P. Shende, R.M. Wadaskar and A.Y. Thakare

13. Ovipositional preference of bruchid (Callosobruchus Maculatus Fabricius) on pod character and pod maturity 70

S. Nandini and G. Asokan

14. Beneficial traits of endophytic bacteria from field pea nodules and plant growth promotion of field pea 73

S. Narula, R.C. Anand and S.S. Dudeja

15. Effect of temperature-tolerant rhizobial isolates as PGPR on nodulation, growth and yield of 80Pigeonpea [Cajanus cajan (L) Milsp.]Simranjit Kaur and Veena Khanna

16. Phenotypic characterization of rhizobacteria associated with mungbean rhizosphere 84Navprabhjot Kaur and Poonam Sharma

17. Root morphology and architecture (CRIDA indigenous root chamber-pin board method) of two 90morphologically contrasting genotypes of mungbean under varied water conditionsV. Maruthi, K. Srinivas, K.S. Reddy, B.M.K. Reddy, B.M.K. Raju, M. Purushotham Reddy,D.G.M. Saroja and K. Surender Rao

18. Selection parameters for pigeonpea (Cajanus cajan L. Millsp.) genotypes at early growth stages 97against soil moisture stressAnuj Kumar Singh, J.P. Srivastava, R.M. Singh, M.N. Singh and Manoj Kumar

19. Optimization of extrusion process variables for development of pulse-carrot pomace 103incorporated rice based snacksMd. Shafiq Alam, Baljit Singh, Harjot Khaira, Jasmeen Kaur and Sunil Kumar Singh

20. Area expansion under improved varieties of lentil through participatory seed production programme 115in Ballia District of Uttar PradeshS. K. Singh, Riyajuddeen, Vinay Shankar Ojha and Sanjay Yadav

21. Performance of chickpea in varied conditions of Uttar Pradesh 120Lakhan Singh and A.K. Singh

22. Role of pulses in the food and nutritional security in India 124Shalendra, K. C. Gummagolmath, Purushottam Sharma and S. M. Patil

SHORT COMMUNICATIONS

23. Genetic variability and character association analysis in french bean (phaseolus vulgaris L.) 130Anand Singh and Dhirendra Kumar Singh

24. Assessment of heritable components in chickpea (Cicer arietinum L.) 134Sudhanshu Jain, S. C. Srivastava, Y. M. Indapurkar and H.S. Yadava

25. Genetic variability and character association for yield and its components in black gram 137(Vigna mungo (L.) Hepper)A. Narasimhan, B. R. Patil and B. M. Khadi

26. Studies on genetic variability, heritability and genetic advance in chickpea (Cicer arietinum L) 139Shweta, A.K. Yadav and R.K. Yadav

27. Effect of zinc, molybdenum and Rhizobium on yield and nutrient uptake in summer urdbean (Vigna mungo L.) 141Khalil Khan and Ved Prakash

28. Effect of seed dressers against root rot of cowpea 145D. B. Patel, S. M. Chaudhari, R.G. Parmar and Y. Ravindrababu

29. Development of tempeh a value added product from soyabeans and other underutilised 147cereals/millets using Rhizophus Oryzae PGJ-1G. Gayathry, K. Jothilakshmi, G. Sindumathi and S. Parvathi

Journal of Food Legumes 26(3 & 4): 1-18, 2013

Heavy metal toxicity to food legumes: effects, antioxidative defense and tolerancemechanismsNAVNEET KAUR and HARSH NAYYAR*

Department of Botany, Panjab University, Chandigarh, India; *E-mail:[email protected]

ABSTRACT

Heavy metal stress has emerged as one of the most detrimentalfor the major food crops due to persistent soil pollution. Thesemetals are known to replace essential metals in pigments orenzymes disrupting their function and have thus proved to betoxic. Their toxicity results in chlorosis, weak plant growth,yield depression accompanied by reduced nutrient uptake,disorders in plant metabolism and, in leguminous plants, areduced ability to fix molecular nitrogen. Most of theleguminous crops are affected by metal stress present in thesoil mainly due to contaminated agrochemicals and sewagesludge. They are known to cause deleterious effect on the celldivision of the plants and cause many chromosomalabnormalities which depend upon the concentration and theintensity of the exposure of the same. Uptake and accumulationof metals at higher concentrations cause ultra-structural andanatomical changes in the plant cells. Various plantphysiological activities like seed germination, nutritiondistribution, enzymatic activity, nitrogen fixation,photosynthesis and pollen function are adversely affected.Uptake into the seeds adversely affects the nutritional qualityof seeds. However, the plants possess various defense andtolerance mechanisms to cope up with stresses. In this review,we describe various effects, defense and tolerance mechanismsdue to heavy metals, especially for legumes.

Key words: Heavy metals, Legumes, Tolerance mechanism, Toxicity

1. Introduction

Plants experience various biotic and abiotic stresseswhich adversely affect the growth,deteriorate the yield andphysiological parameters of the crops. Among these stresses,heavy metal stress has emerged as one of the most detrimentalfor the major food crops. Toxic metals have also contributedtowards most of the soil and water pollution in the environment.

The term heavy metal refers to any metallic chemicalelement that has relative high density and molecular weightand is toxic even at low concentrations. These include thetransition metals, metalloids, lanthanides and actinides in theperiodic table, mostly having a specific gravity greater than5.0 (Nieboer and Richardson 1980). According to another view,heavy metals can include elements lighter than carbon andcan exclude some of the heaviest metals. While speaking ofheavy metals, we generally mean lead, mercury, iron, copper,manganese, cadmium, arsenic, nickel, aluminium, silver andberyllium. Some heavy metals are essential to the livingorganisms but at higher concentrations they produce toxicity.

In general, heavy metals produce toxicity by formingcomplexes or “ligands” with organic compounds. Thesemodified biological molecules lose their ability to functionproperly, and result in malfunction or death of the affectedcells. The most common groups involved in ligand formationare oxygen, sulphur, and nitrogen.Carboxylic acids and aminoacids such as citric acid, malic acid and histidine are potentialligands for the heavy metals(Rauser 1999). When the metalsbind to these groups they may inactivate the important enzymesystems, or affect protein structure of various biologicalmolecules and thus may block the pathways of majorphysiological processes. These have affected the biospherein many places worldwide (Cunningham et al. 1997). Heavymetals are one of the main abiotic stressors for the plantsbecause of their increased use in the industries andagrotechnics and also because of their high bioaccumulationability and toxicity (Maksymiec 2007). Heavy metals are knownto replace essential metals in pigments or enzymes disruptingtheir function (Ghosh and Singh 2005) and have thus provedto be toxic. Roots are the first target to the heavy metals,which get damaged and lead to inhibition of the plant growthand ultimately crop failures. A long-term exposure of wholeplants to enhanced metal concentrations may also affect thechlorophyll synthesis and thus have an important role in both

Dr. Harsh Nayyar is a Professor of StressPhysiology at Department of Botany,

Panjab University, Chandigarh, India. Hereceived his M.Sc. and Ph.D from PunjabAgricultural University, Ludhiana India. Heworked as a Scientist (A.R.S.) underI.C.A.R., New Delhi for some time andsubsequently at H.P. Agricultural University, Palampur(H.P.) for 10 years and later moved to Panjab University,Chandigarh in the year 2000. His research interests includeeffects of abiotic stresses on legumes with reference tometals, salts, drought and temperature. He is working incollaboration with P.A.U., Ludhiana, ICRISAT, Hyderabad,CSIRO, Australia and University of Western Australia. Hewas awarded Indo-Australian Projects (DST, India andDEST, Australia) twice to work on sensitivity of chickpeato abiotic stresses in collaboration with scientists from theseorganisations. He has published about 100 research papersand articles in various journals of national and internationalrepute.

2 Journal of Food Legumes 26(3 & 4), 2013

the chloroplast development in young leaves and theinhibition of photosynthesis (Boddi et al. 1995).

The sources of heavy metals pollution can be bothnatural and anthropogenic. Natural sources include the motherrocks and minerals of the metals while the anthropogenicsources are agriculture, black and colored metallurgy andtransport (Budnikov 1998).There are many records that theplaces adjacent to the industrial places have been affectedmainly by the toxic heavy metals (Rao 1979). Human activityhas contributed metal concentrations in soil range from lessthan 1 mg/kg to as high as 100,000 mg/kg (Blaylock and Huang2000), which have lead to the disruption of natural, aquaticand terrestrial ecosystems. Above certain concentrations andover a narrow range these heavy metals can turn into toxicproducts (Babich and Stotzky 1978). It is reported that thecontinuous exposure to the heavy metals have severelyaffected the health of human beings, plants, animals and themicrobial populations that have disrupted the ecologicalhabitats (Sterritt and Lester 1980, Brynhildsen and Rosswall1997).

2. Toxic effects of various heavy metals on plants

Heavy metals cause acute toxic effects on plants grownon the contaminated soils. Their toxicity results in chlorosis,weak plant growth, yield depression accompanied by reducednutrient uptake, disorders in plant metabolism and, inleguminous plants, a reduced ability to fix molecular nitrogen(Chaudri et al. 2000, Dan et al. 2008). Agricultural yield isdecreased due to their prevalent use and cause dangeroushealth effects as they enter into the food chains (Schicklerand Caspi 1999). Heavy metals are transmitted through thefood chains and strongly affect the human health (Brunet al. 2001, Gincchio et al. 2002). There are metals like Pb, Hg,Cd, Ar and Cr, which have no biological function but are toxicto life even at very low concentration (Salt et al. 1995). Manymetals are nutrients at permissible levels but act as toxinswhen the concentrations found in the soil exceed to thoserequired as the nutrients. Arsenic is non-essential elementand generally toxic to plants. Symptoms include poor seedgermination and marked reductions in root growth. Plants mayshow reduced growth, nutrient deficiencies and chlorosisresulting from reduced chlorophyll biosynthesis (Mascheret al. 2002).Cadmium is also a non-essential element, theaccumulation of which may cause several physiological,biochemical and structural changes in plants (Feng et al. 2010).It also alters mineral nutrients uptake, cause inhibition instomatal opening by interacting with the water balance ofplant (Hossain et al. 2010), disturbs the Calvin cycle enzymes,photosynthesis, carbohydrate metabolism (Shi et al. 2010)and ultimately reduces the crop productivity (di Toppi andGabreilli 1999).There are reports that excess of chromiumcauses inhibition of plant growth, chlorosis in young leaves,nutrient imbalance, wilting of tops, and root injury (Scoccianti

et al. 2006). It inhibits the chlorophyll biosynthesis in terrestrialplants (Vajpayee et al. 2000). High levels of Cr affected totaldry matter production and yield of plants (Shanker et al. 2005).Like other heavy metals, chromium toxicity produces chlorosisand necrosis in plants (Cervantes et al. 2001).

Copper is considered as an important micronutrient forplants (Thomas et al.1998) and plays important role in CO2assimilation and ATP synthesis. It is known to be an essentialcomponent of various proteins like plastocyanin ofphotosynthetic system and cytochrome oxidase of respiratoryelectron transport chain (Demirevska-kepova et al. 2006) aswell as other various proteins. In acute Cu toxicity, leavesmay become wilted before eventually becoming necrotic (Yauet al. 1991). Plants can accumulate some amount of cobaltfrom the soils but the uptake and distribution of cobalt inplants is species-dependent and is controlled by differentmechanisms (Kukier et al. 2004, Li et al. 2004 and Bakkauset al. 2005). There are some reports that Co adversely affectsthe shoot growth and biomass in some plants (Li et al. 2009).Lead is a major heavy metal that has gained importance as apotent environmental pollutant (Sharma and Dubey 2005). Leadaffects a number of plants by decreasing the productivity ofplants growing in lead- polluted soils (Johnson and Eaton1980). Its phytotoxicity leads to inhibition of number of enzymeactivities, disturbances in the mineral nutrition, waterimbalance, and changes in the hormonal status and alterationin the membrane permeability. At high concentrations, leadmay even lead to cell death (Seregin and Ivanov 2001).Mercury is also a very important toxic metal. Exposure to themercurials in crop plants are by direct administration asantifungal agents, through the seed treatment or foliar spray,or accidentally (Patra and Sharma 2000). It affects both thelight and dark reactions of photosynthesis by the substitutionof magnesium of chlorophyll thereby resulting in thebreakdown of photosynthesis. It binds to water channelproteins, thus inducing leaf stomata to close and physicalobstruction of water flow in plants (Zhang and Tyerman 1999).High levels of mercury interferes with the mitochondrialactivity and induces oxidative stress by triggering thegeneration of ROS thus leading to the disruption ofbiomembrane lipids and cellular metabolism in plants ( Israret al. 2006, Cargnelutti et al. 2006).

Nickel also causes phytotoxicity by alter ingphysiological reactions and diverse toxicity symptoms suchas chlorosis and necrosis in different plant species (Zornozaet al. 1999, Pandey and Sharma 2002, Rahman et al. 2005),including rice (Samantaray et al. 1997). Yadav (2009) havereported that plants grown in high Ni2+ containing soil showedimbalance of nutrients and resulted in disorder of cellmembrane functions.Zn concentrations in the range of 150 to300 mg/kg has been categorized as toxic that inhibits variousplant metabolic processes, results in reduced growth andcause senescence. Shoot and root growth also decrease by

Kaur & Nayyar : Heavy metal toxicity to food legumes: effects, antioxidative defense and tolerance mechanisms 3

the application of zinc (Fontes and Cox 1998). Prolongedexposure to zinc causes chlorosis in the younger leaves,which can extend to older leaves (Ebbs and Kochian 1997).3. Effects on Legumes

Legumes belonging to the family Fabaceae areresponsible for substantial part of the global flux of nitrogenfrom atmospheric nitrogen to the fixed forms such as ammonia,nitrate and organic nitrogen. Most of these are agriculturallyimportant food crops and are a rich source of proteins to theanimals and human beings(Gupta 1987). Most of theleguminous crops are affected by metal stress present in thesoil mainly due to contaminated agrochemicals and sewagesludge. Due to this, various plant physiological activities likeseed germination, nutrition distribution, enzymes activity,alternation of the membrane permeability, nitrogen fixation,photosynthesis, transport of the assimilates and respirationare adversely affected.3.1. a. Cytology:

Heavy metals adversely affect the cytology of the plantcells. The genotoxicity of heavy metals influences the DNAsynthesis, duplication of DNA and chromosomes causingmany chromosomal aberrations (Cheng 2003). They are knownto cause deleterious effect on the cell division of the plants,which depend upon the concentration and the intensity ofthe exposure of the same.

Fig: 1 Heavy metal induced chromosomal abnormalitiesin plant cells

The effects of Cd on the cell division of the root tips inbeans were studied by Mo and Li 1992. The treatment of beansby Cd, Pb , and Hg at concentrations 0.01,1.0 and 10 ppm,respectively shortened the cell division but extended the cellcycle. The chromosomes of beans exposed to Cd, Pd, Hg gotinjured and revealed polyploidy, C-karyokinesis and variouschromosomal abnormalities like formation of chromosomalbridges, chromosomal rings and chromosome fragmentation,chromosome micro-nuclei and nuclear decomposition (Mo and

Li 1992, Liu et al.1992, Duan and Wang 1995). ( Fig. 1). Gomez-Arroyo et al. (2001) reported that the salts of nickel, cobaltand cadmium increased the frequency of the sister chromatidexchanges (SCE) in Vicia faba. It has been observed in thesome plants that mercury poisoning leads to the disturbancein the spindle activity resulting in the formation of polyploidand aneuploid cells and c-tumours. Kumar (2007) studied themutagenic potential of lead (25, 50, 100, 200, and 300 ppm) inLathyrus sativus and showed that chromosomal abnormalitiesincreased with the lead nitrate concentration. Theseabnormalities included condensed bivalents, laggards,bridges, cytomixis and stickiness of the chromosomes.Siddiqui et al.(2009) studied the effect of cadmium on the roottips of Pisum sativum L. Seeds of P. sativum were treated witha series of concentrations ranging from 0.125, 0.250, 0.500 and1 mM Cd for 6 h. It was reported that the overall percentage ofaberrations generally increased with increasingconcentrations of Cd. The most common chromosomalabnormalities were laggards, bridges, stickiness, precociousseparation and fragments. Zhang et al. (2009) investigatedthe effects of different concentrations of Cd (1-50µM) on celldivision and nucleoli in root tip cells of Vicia faba. Resultsrevealed that Cd induced c-mitosis, chromosome bridges,chromosome stickiness and lagging chromosomes. Smallamounts of nucleolus materials were extruded from the nucleusinto the cytoplasm at 1µM Cd when the root tips were exposedfor 24 hours. Zhang et al. (2009) studied the effects of differentconcentrations of Al (10 µM, 50 µM, 100 µM) on nucleoli inroot tip cells in hydroponically grown Vicia faba L. It wasrevealed that aluminum significantly inhibited root growth ofV. faba treated with 50 µM and 100 µM concentrations. In thenucleolus of root tip cells, some particulates containingagyrophilic proteins were extruded from the nucleus into thecytoplasm, and some were scattered in the nucleus after Alstress in the plants. In the root tips of green gram (Vignaradiata. L), arsenic and manganese induced chromosomalstickiness at higher concentrations. However it was reportedthat arsenic had more toxic effect than manganese on the roottip cells of greengram during mitosis (Mumthaz 2010).

Studies were carried out by Muneer et al. (2011) on roottips and leaves of Vigna radiata, where 15 days old plantletsgrown in nutrient Hoagland media were exposed to variouslevels of cadmium chloride (0.05, 0.10 and 0.50 mM) for 48 and72 hours. It was shown that Cd exhibited inhibitory effect oncytological studies namely, mitotic index and chromosomenumber. Chromosomal studies showed various chromosomalabnormalities such as laggard chromosomes, anaphasicbridges, and uni-distribution of chromosomes.

Bhat (2011) reported that heavy metals aroundautomobile refining shops induce synergistic cytogeneticeffects in Trifolium repens and noticed a significant increasein micronucleus (MN), chromosomal aberrations (CAs),percentage of nuclei with comet tails (NCTs), the relative comet


tail length (CTL), comet tail DNA (CT, DNA), and tail moment(TM) with increased concentration of three heavy metals, likeCd, Pb and Hg. The most prominent abnormalities induced byheavy metals were micronucleus, precocious separation, andlaggard formation. Ritambhara et al.(2010) carried out somecytogenetic studies to evaluate the genotoxic effect of lead(Pb) and zinc (Zn) on the gametic cells of grass pea (Lathyrussativus). A severe chromosome stickiness in meiosis impairingnormal chromosome segregation was reported, whichpersisted upto microspore stage, ultimately leading tochromosome degeneration. Recently, Oladele et al. (2013)reported thatincreased metal pollution can lead to someirreversible cytogenetic effects in plants and higher organisms.Their group investigated the effects of lead and zinc nitratesat different concentrations: 25, 50 and 100 mg/L on thechromosomes of bambara groundnut (Vigna subterranean).The results show the most frequent chromosomal anomaliesinduced by these heavy metals as stickiness and bridges.3.1.b.Anatomy and Ultrastructure

Han et al. (2004) have reported that uptake andaccumulation of metals at higher concentrations cause ultra-structural and anatomical changes in the plant cells. Theseinclude structural modifications in the chloroplast, thylakoidmembranes, deposition of electron dense globules in vacuoles,increase or decrease in the size of cells, reduction of theintercellular spaces and also changes in the turgor pressureof the plant cells. In the thylakoids, modifications includeswelling and curling of the thylakoidal membranes. Also, ithas been reported that heavy metal stress causes degradationof polypeptide compositions of the thylakoid membrane,reduction, disappearance or swelling of the grana cascade ofchloroplast mitochondria (Cheng 2003). Heavy metal inducedcellular and ultrastructural modifications have been illustratedin Fig.2.

There was accumulation of callus on the sieve plates ofphloem of Phaseolus vulgaris seedlings exposed to excess ofCo, Ni and Zn (Peterson and Rauser 1979). In case of beans,toxicity of chromium has also found to decrease the diameterof the treachery vessels, which resulted in reducedlongitudinal water movement (Vazques et al.1987). Reducedturgor pressure and plasmolysis in the epidermal and corticalcells of bush bean plants, which were exposed to chromiumwas also observed (Vazques et al.1987). Formation of wallingrowths in hypodermal cells of the cadmium treatedPhaseolus vulgaris roots was reported (Vazques et al.1989).Cadmium treatments to Arachis hypogea plants inducedxerophyte anatomic features of leaves i.e. thick lamina, upperepidermis, palisade mesophyll, high palisade to spongythickness ratio, as well as abundant and small stomata (Shiand Cai 2008). In 5µg/ml cadmium treated roots of bush beanplants (Phaseolus vulgaris L. cv. Contender) grown on perlite,plastid ultrastructure was hardly affected, while in the upperparts of the plant the chloroplasts showed severe alterations.Younger trifoliate leaves showed greater disruption ofchlorophyll synthesis and plastid ultrastructure (Barceloet al. 1987). In the experiments of Baszynski et al. (1980) andStoyanova and Chakalova (1990), it was established thatcadmium, applied in toxic concentrations, disturbs thechloroplast envelope and the integrity of the membrane systemand leads to increased plastoglobule number, changing thelipid composition and the ratios of the main structuralcomponents of thylakoid membranes. Heavy metals effectson the structure and functions of the photosyntheticmembranes of the higher plants showed that the sub-microstructure of the chloroplast was changed (Yang 1991).Ultra structural alternations in the cortical root cells of pigeonpea in response to zinc and nickel both at cellular and theorganelle level were observed (Sresty et al. 1999). Unusualdeposition of electron dense globules in the vacuoles of theroot cortical cells and appearance of unusual two nucleolioccurred. The ultra structural analysis of the leaves of peaplants grown with 50µM CdCl2 showed the internal celldisturbances characterized by an increase of mesophyll cellsize, a reduction of the intercellular spaces and severedisturbances in the chloroplast structure (Sandalio et al. 2001).In the pea leaves treated with Cd, there was disorganizationof the chloroplast structure, with an increase in the number ofplastoglobuli and formation of vesicles in the vacuoles(Mc Carthy et al. 2001). The effect of Cu2+ at concentrations(50 and 75uM) on the ultra-structure of the chloroplasts ofthe bean seedlings revealed that excess of copper inducedchanges in the ultra-structure of chloroplasts visible in formof deterioration in the grana structure and the accumulationand swelling of starch grains in the stroma (Bouaziziet al. 2010).

Fig: 2: Heavy metal induced ultrastructural modificationsin the cell and chloroplast


3.2 Germination of legume seeds

Germination of the seed is one of the most highlysensitive processes and toxicity with the essential and nonessential heavy metals invariably affects the germination rateand subsequent seedling growth. It represents a limiting stageof plant life cycle under heavy metal stress situation (Rahouiet al. 2008, Smiri et al. 2009). High levels (500 ppm) ofhexavalent Cr in soil reduced germination up to 48% in thebush bean Phaseolus vulgaris (Parr and Taylor 1982). Thegrowth of embryonic axis of germinating pea seeds (Pisumsativum cv. Bonneville) was significantly inhibited by as lowas 0.25 mM cadmium and the elongation of the radicle wasaffected more severely than that of the plumule (Chugh andSawhney 1996). In another experiment, Al-Yemini and Nasser(2001) reported a significant decrease in the percentage ofseed germination, seedling growth and an increase in radiclelength of Vigna ambacensis L.after treatment with cadmium,mercury and lead at concentrations (0.05-50mM). Seedgermination of the alfalfa plant (cultivar Malone) was seriouslyaffected by a concentration of 20 ppm of Cd(II), Cr(VI), and by40 ppm of Cu(II) and Ni(II) (Peralta et al. 2001). However, theroot and shoot growth of the alfalfa plant was stimulated by aconcentration of 5 ppm of Cr(VI), Cu(II), Ni(II), and Zn(II). Ina study, Al-Rumaih et al. (2001) revealed that cadmium chlorideadversely influenced the germination process of Vignaunguiculata seeds. The germination percentage and thegermination rate index (GRl) expressed as percentagegermination per day showed a significant (p~0.05) decreaseat 40 ppm, and the decline in these measures became highlysignificant (p~0.01) at 80 and 160 ppm cadmium chlorideconcentrations, as compared with the untreated control ones.Cr (VI) at 40 ppm reduced seed germination by 23% of seedsof lucerne (Medicago sativa cv. Malone) and growth in thecontaminated medium (Peralta et al.2001).The effect of severaldoses of As (V), Cd (II), Pb (II), Hg (II), Cu (II), Zn (II) on theseed germination of four common pulses (Vigna mungo(L.)Hepper, Vigna radiata (L.)Wilzek, Pisum sativum L. andLens culinaris L.) were observed by Mandal andBhattacharyya 2007. Certain levels of some heavy metalswere favourable for seed germination while others were theinhibitory ones. Exposure of 20 ppm Hg (II) showed highertoxicity than other heavymetals and reduced the germinationpotential to 50% as compared to control. It was also shownthat the order of toxicity of the metal elements on the fourpulses decreased as follows: Hg> As> Cd> Pb> Cu> Zn. Inalfalfa, it was reported that the seed germination is seriouslyaffected by 20 ppm of Cd+2, Cr+6, and by 40 ppm of Cu+2, Ni+2

while the root and shoot growth are stimulated by 5 ppm ofCr+6, Cu+2, Ni+2, and Zn+2(Aydinalp and Marinova 2009). Inanother experiment Al-Qurainy (2009) studied the toxicity ofAl and Ni individually on P. vulgaris which affected root andshoot length and their effects on length was appeared after 3days of germination but % germination was not inhibited inboth metal treatments. A reduction in seed germination and

seedling growth in chickpea treated with 50, 100, 200 and 400ppm of nickel and cobalt was reported by Khan and Khanet al. 2010. The germination of Vigna unguiculata seeds aftertreatment in solution containing varying concentration ofcadmium chloride (CdCl2.H2O) was observed (Egharevba andOmoregie 2010).The concentrations of cadmium (Cd) in thesolution used for the treatment were 0.00 ppm, 0.80 ppm, 8.00ppm, 40.00 ppm, 100.00 ppm and 180 ppm. Results showedthat the percentage germination and rate of increment in shootheight decreased as cadmium level in the treatment solutionincreased. However, no growth was observed at 100 and120 ppm.

There can be a number of reasons behind the decreasedrate of seed germination in plants. The decrease in seedgermination of heavy metal treated plants can be attributed tothe accelerated breakdown of stored food materials in seed(Shafiq et al. 2008). Several authors reported that the inhibitionof root elongation caused by heavy metals may be due tometal interference with cell division, including inducement ofchromosomal aberrations and abnormal mitosis (Radhaet al. 2010, Liu et al. 2003), which can affect the seedlinggrowth. These observations indicated variable effects ofmetals, though inhibitory in each of the legume species tested.3.3. Nitrogen fixation and symbiosis

It is reported that excessive metal concentrations in thepolluted soils cause damage to Rhizobia, legumes and theirsymbiosis (Ahmad et al. 2012). The establishment of symbiosisi.e. root nodulation is an orderly process, which is influencedby various edaphic factors and the presence of pollutants inthe soil. However, very little is known about how legume–Rhizobium symbiosis is affected by varying metalconcentration (Huang et al.1974, Mcilveen and Cole 1974,Decarvalho et al. 1982, Paivoke 1983, Yakoleva 1984). Variouseffects of heavy metals on nitrogen fixation are shown in Fig.3.

3.3.1 Heavy metals inhibit the activity of the symbioticnitrogen fixers

Heavy metals affect the nitrogen fixation process byinterfering with the performance of the symbiotic bacteria.

Fig:3 Effect of heavy metals on the nitrogen fixationefficacy of legumes


Various metals (e.g. Cu, Ni. Zn, Cd, As) are known to inhibitthe growth, morphology and activities of various symbioticN2 fixers (Stan et al. 2011) like R. leguminosarum,Mesorhizobium ciceri, Rhizobium sp. and Bradyrhizobiumsp. and Sinorhizobium (Arora et al. 2010, Bianucci et al. 2011).The population of R. leguminosarum bv. trifolii was radicallyaltered by long-term exposure to heavy metals and it lost theability to form functional symbiosis with white and red clover(Hirsch et al. 1993). Chaudri et al. (2000) reported a decreasein two agriculturally important species of Rhizobia, R.leguminosarum bv. viciae and R. leguminosarum bv. trifolii,in soils, which were irrigated with sewage sludge containingZn or Cu or mixture of Zn and Cu. Similarly, there arenumerousreports where elevated amounts of heavy metalshave been found to limit the rhizobial growth and their hostlegumes (Heckman et al. 1987, Broos et al.2005) andtherebyreducing the total crop yields (Moftah 2000).3.3.2 Inhibition and delay in nodulation in the legume roots

Nodulation in the soybean roots was greatly inhibitedby the addition of Cd (10-20mg/kg) to the soil (Chen et al.2003) but the nitrogen fixation of the root nodule wasstimulated with low concentrations of Cd, which decreasedsharply with the further additions. The impact of heavy metalssuch as cadmium (23mg/kg) and lead (390mg/kg) on nitrogenuptake in chickpea was studied by Wani et al. 2008. It wasreported that cadmium and lead reduced the number of nodulesby considerable percentages. The total nitrogen content ofthe shoots, nodule weight, nodule number and N2 (C2H2)-fixation were reduced significantly in dry beans treated with10µM Cd /L (Vigue et al.1981). The responses of Lablabpurpureus-rhizobium symbiosis to the effect of different levelsof heavy metals Cd, Zn Co and Cu at concentrations (control,50, 100, 150 and 200 mg/kg soil) was reported (Younis 2007). Itwas reported that there was enhancement in the nodulenumber and their mass in the soil treated with 100 mg/kg soilof Co and Cu, respectively while there was inhibition at otherlevels. There was severe inhibition in the nitrogenase activity.Delay in the nodulation process in some legume crops hasalso been observed. For example, with increasingconcentration of arsenic (As) in the nutrient solution, therewas greater time required for Bradyrhizobium japonicumstrain CB1809 to inoculate soybean. (Riechman 2007).3.3.3 Decrease in the rate of symbiosis

A considerable decrease in the total yield, nitrogencontent in the plant tissue and the protein content of theseeds was noticed chickpea-rhizobium and green gram-bradyrhizobium symbiotic systems when treated with cadmium,lead, copper, zinc, chromium and nickel added in combinationsand separately (Athar and Ahmad 2002). Adverse effects ofsludge application on N2 fixation in faba bean (Vicia faba)have been reported (Chaudri et al.1993). In white clover,cadmium, lead and zinc caused reduction in growth andsymbiosis when they were grown in soils highly contaminated

with these metals (Rother et al.1983). Chickpea-rhizobiumsymbiotic system was more sensitive to the metals toxicitythan green gram-bradyrhizobium system (Antipchuket al. 2000).The adverse effects of mercury, cadmium, nickel(1mg/ml) on nodulation and nitrogen fixation in Cicerarietinum-rhizobium symbiotic system were reported asdecrease in dry weight of both total nodules and effectivenodules indicating disturbances in the nodule function (Pal1996).3.3.4.Nitrogenase activity and protein content

Soybean (Glycine max L.) nodules and roots in plantswere subjected to two different concentrations (50 and 200µM) of CdCl2 (Karina et al. 2003). Nitrogenase activitydecreased in nodules treated with 200 µM Cd2+. In 50 µMCd2+-treated plants, NH4

+ content increased by 55% in roots.Glutamate (Glu) and protein contents remained unaltered innodules treated with 50 µM Cd2+, while at the higher Cd2+

concentration, both were decreased.Cadmium significantlydepressed biological nitrogen fixation in 0-10mM treated onemonth old pea (Pisum sativum) and also decreased nitratereductase and glutamate synthase activities 6 days aftertreatment (Chugh et al. 1999). In Lablab purpureus, nodulationand nitrogenase activity were severely affected with 50-200mg/kg metal concentrations of Cd, Zn, Co, and Cu (Younis2007). (Fig.3)3.4 Photosynthetic efficiency of some legumes

Heavy metals are known to interfere with many vitalprocesses of the plants including photosynthesis (Clijstersand Assche 1985) and cause inhibition in this process. Thisinhibition has been attributed with an indirect action on plantwater balance, stomatal conductance and CO2 availability. Thedirect effects include effect on chloroplast organization,chlorophyll biosynthesis, electron transport and enzymes ofphotosynthetic carbon metabolism (Fig. 4).

3.4.1 Interference in the photosynthetic function andmachinery

Heavy metals lead to oxidative stress in the plants. As aresult, there is decreased photosynthetic activity and growthof tissues, which is followed by reduction of plant productivity(Ouzounidou 1995 Maksymiec 1997). The insufficiently utilizedassimilatory force by Calvin cycle slowed down due to heavy

Fig: 4 How do heavy metals effect the process ofphotosynthesis?


metal stress may, in consequence, enhance proton gradientformed in chloroplasts and increase non-photochemicaldissipation of light energy and/or decrease photochemicalefficiency (Maksymiec and Baszyn´ski 1996, Maksymiec 1997).Many heavy metals are known to interfere with thephotosynthetic machinery (Fig.4). For example cadmiuminterferes with the chloroplast function and electron transportsystem by damaging PSII of photosynthesis. Copper showsnegative effect on the components of both the light reactionse.g., PSII, thylakoid membrane structure andchlorophyllcontent (Ralph and Burchett 1998, Szalontai et al.1999, Pätsikkäet al. 2002 and CO2-fixation reactions ( Angelov et al.1993).However, in studies that examined both light and CO2-fixationcomponents, the relative sensitivity of each to Cu varies amongstudies ( Moustakas et al. 1994). Krupa and Baszynski (1995)investigated the heavy metals treated legumes and reportedthat they severely affect the rate of photosynthesis byinhibiting the light and dark photosynthetic reactions,inhibiting the enzymes of the carbon reduction pathways anddisturbing the photosynthetic apparatus.3.4.2.Interference in chlorophyll synthesis

Studies indicate that heavy metals have deleteriouseffects on the total chlorophyll content in plants (Fig.4). Theeffect of Cr on chloroplast pigment content in mungbeanshowed that irrespective of concentration, chlorophyll a,chlorophyll b and total chlorophyll decreased in 6-day-oldmungbean seedlings (Bera et al.1999). Effects of some heavymetals on content of chlorophyll in bean Phaseolus vulgarisseedlings was investigated by Zengin and Munzuroglu 2005grown in Hoagland solution spiked with variousconcentrations of Pb, Cu, Cd and Hg. It was reported that thetotal chlorophyll content declined progressively withincreasing concentrations of heavy metals. The totalchlorophyll content, chlorophyll b content and carotenoidscontent was severely affected with in blackgram varietiestreated with lead and copper (Bibi and Hussain 2005). Also, itwas concluded that application of lead and copper to boththe black gram cultivars caused significant reduction in thephotosynthetic gas exchange, inactivation of enzymes suchas Rubisco, Rubisco activase and carbonic anhydrase. Totalchlorophylls and carotenoids were calculated from theseedlings of Cyamopis tetraganoloba treated with heavymetals Cd, Pd, Ni, Zn and Cu. It was concluded that Cd and Pbin comparison to Zn, Cu, and Ni reduced the total chlorophyllcontent at 1000 ppm. Shi and Cai (2008) reported the effects ofcadmium treatments on Arachis hypogea plants andconcluded that these treatments caused a decrease in the netphotosynthetic rate and reduced the content of thephotosynthetic pigments as well. Phaseolus vulgaris L. plantsgrown in soil supplemented with different Pb and Cdconcentrations (2,4, 6, 8 g kg-1 for lead and 1.5, 2.0, 2.5, 3.0 gkg-1 for cadmium) showed decrease in the content of

photosynthetic pigments, total soluble sugars, starch contentas well as soluble protein. However, total free amino acidcontent and lipid peroxidation were increased with increasingconcentration of heavy metals (Bhardwaj et al. 2009). Kamel(2008) treated Vicia faba plants with different concentrationsof lead nitrate ranging from 0-48 mM in hydroponic solution.It was observed that low doses of Pb (0.49 mM) increased thechlorophyll content while the chl-a content decreased at highconcentrations of Pb (48 mM). It was also observed that the14C-fixation decreased at all the applied Pb concentrations.3.4.3. Reduction in the activities of photosynthetic enzymes

and inhibition of photosynthetic rate

Heavy metals interfere with chlorophyll synthesis eitherthrough direct inhibition of an enzymatic step or by inducingdeficiency of an essential nutrient (Van Assche and Clíjsters1990). Sheoran et al.(1990) studied the effect of Cd2+ and Ni2+

on the rate of photosynthesis and activities of key enzymesof the photosynthetic carbon reduction cycle in leaves frompigeonpea (Cajanus cajan L., cv. UPAS-120) grown in nitrogenfree sand culture. It was concluded that the application ofCd2+ and Ni2+ (0.5 and 1.0 mM) at an early vegetative stage (30days after sowing) resulted in about 50% and 32% reductionin net photosynthesis, respectively. The activities of thephotosynthetic enzymes were decreased to different levels(2–61%) depending upon the enzyme and the concentrationof the metal ion. It was found that Cd toxicity caused notablereduction in photosynthetic rate in different plant species(Baszynski et al.1980). In case of pigeon pea, Cdconcentrations of 56 and 112 mg/L inhibited netphotosynthesis to about 50% at early development stages(30-day-old plants) and did not exert any significant effect onthat process at later stages (70-day-old plants). Sheoran etal.(1990) also reported that at the early stage of pigeonpea,CO2 exchange rate was quite susceptible to Cd stress.Application of copper and lead at concentrations 25 or 50 mgL-1 in two Mungbean cultivars Vigna radiata (L.) Wilczek](Mung-1 & Mung-6) caused significant reduction in the CO2exchange and photosynthetic pigments. Also, there wassignificant inhibition of photosynthetic and transpiration ratesand stomatal conductance compared to the same doses ofcopper at higher concentration of lead (50 mg L1) compared tothe same doses of copper (Ahmad et al. 2008). In the excisedleaf segments of pea, it was reported by Sengar and Pandey(1996) that Pb lowered photosynthesis specifically by theinhibition of –amino levulinic acid synthesis and the decreasein the 2-oxoglutamate and glutamate pool, which may becaused by the competition between the essential ions requiredfor chlorophyll synthesis and lead. Applying Cd upto 1 mMconcentration to pea (Pisum sativum) seedlings caused asharp decline in the chlorophyll content, photosynthetic rates,activity of photosystems and photosynthetic enzymes(RUBISCO etc.) in 6 days and these effects became morestressed during extended treatment.


3.5 Reproductive biology: Pollen function

It has been found, that inhibitory effects of sulfur dioxideon pollen germination and tube elongation have occurred atconcentrations lower than those at which foliar effects havebeen recorded (Varshney and Varshney 1980). This suggeststhat heavy metals, even if present at low concentrations inplant tissue, may affect pollen germination and pollen tubegrowth. Pollen tubes are excellent standard systems withwhich the effects of drugs and pollutants can be investigated(Kristen et al.1993). Studies report that heavy metals at toxiclevels inhibit pollen germination, pollen tube growth (Tunaet al. 2002) by causing ultra-structural changes. Xiong andPeng(2001)tested 5 herb species (Vicia augustifolia,V.tetrasperma, Pisum sativum, Plantago depressa, andMedicago hispida) for their responses against Cd exposurefor pollen germination and tube growth to Cd exposure invitro. Results revealed that pollen germination of all the specieswas inhibited at Cd concentrations of 2.51µg/ml and higher,and tube growth was inhibited at concentrations of 1.58µg/mland higher. The pollen response to Cd stress exhibitedinterspecies differences. Vicia angustifolia and V. tetraspermawere sensitive to Cd and were inhibited in either pollengermination or tube growth by Cd at 0.01 µg/ml. At 1 µg/ml,pollen tube growth of V. angustifolia, V. tetrasperma, and P.sativum was inhibited. Results suggested that cadmium atsuch a low concentration as 0.01 lg/mL is able to exert adverseeffects on pollen germination in some sensitive species, whileit fails to do so for less-sensitive species.3.6 Phyto-hormones

Quantitative determination of endogenous chemicalcompounds including hormones in plants growing undercontrolled environmental conditions in presence and absenceof heavy metals is used to study the effect of heavy metals(Varga et al.1999). Atici et al. (2005) investigated the changesin abscissic acid, gibberellic acid, zeatin and zeatin ribosidehormones of chickpea seeds germinating under Pb or Zn heavymetals exposure. Pb increased abcisic acid and zeatin contentswhile decreased gibbrellic acid content in the germinatingseeds. High concentrations of Zn (1.0 and 10 mM) decreasedcontents of zeatin, zeatin riboside and giberellic acid while 0.1mM Zn increased the content of the same hormones. ABAcontent was enhanced by Zn in all concentrationsused.Cakmak et al. (1989) estimated the concentrations ofphytohormones particularly IAA and concluded that itsconcentration in zinc-deficient bean (Phaseolus vulgaris L.)plants are clearly lower compared to those of Zn-sufficientplants(Zn2+), changes in concentrations of ABA are lessdistinct. Re-supply of Zn to deficient plants restores the IAAlevel to that of the Zn-rich plants within 96 h, whereas theABAconcentrations are only slightly increased after Znresupply.In contrast, the effect of Zn nutritional statusoncytokinin levels is less clear. Information on effect ofphytohormones is sparse and is required to be worked out.

3.7 Adverse effects on nutritional value of legumes

Limited data suggests that some heavy metals inducesubstantial reduction in the nutritional quality of the seeds interms of accumulation of starch, proteins, amino acids, andminerals. It has been reported that As interferes in the uptakeand accumulation of minerals in seeds and shoots (Paivokeand Simola 2002) and may alter nutritional composition (Tuand Ma 2005). Paivoke and Simola (2002) reported that As(12.5 to 73.3 mg of sodium arsenate/kg dry weight of soil)caused interference in mineral nutrient balance of Zn, Mg,and Mn in peas. Similarly, in pea, growing in 2.5mM cadmiuma decrease in starch content of its seeds was observed,however, the protein content remained unaffected (Dewanand Dhingra 2004). In case of Phaseolus vulgaris L. plantssupplemented with different Pb and Cd concentrations (2, 4,6, 8 g Kg-1 for lead and 1.5, 2.0, 2.5, 3.0 g Kg-1 for cadmium),total soluble sugars, starch content as well as soluble proteinscontent decreased as concentration of metals was increasedin comparison of control plants. However, the total free aminoacid content was increased with increasing concentration ofheavy metals (Bhardwaj et al. 2009). In case of chickpea grownin As (5mg/kg of dry soil), there was a significant inhibition inthe accumulation of seed reserves such as starch, proteins,sugars, and minerals as compared to the controls, whichindicated that As application markedly reduced the quality ofthe chickpea seeds (Malik et al. 2011).4. Antioxidative Defense mechanisms

Heavy metals cause oxidative stress by damaging thecells and disrupting the cellular homeostasis by the enhancedgeneration of toxic reactive oxygen species (ROS). The ROSproduced during stress are harmful for the plants and canpose a threat to cells by damaging membranes, nucleic acidsand chloroplast pigments (Chen and Goldsbrough 1994,Dra,_zkiewicz et al. 2004). The plants possess anti-oxidativesystems to protect themselves against the damage producedby ROS. This system is composed of antioxidant enzymes:ascorbate peroxidase (APOX), glutathione reductase (GR),superoxide dismutase (SOD), catalase (CAT) and non-enzymatic compounds (ascorbic acid, glutathione,carotenoids, -tocopherol) (Gill and Tuteja 2010).4.1 Antioxidative Enzymatic systems

There is evidence that in pea plants exposed to Cd2+,the antioxidant system might play a role in detoxificationmechanisms (Dixit et al. 2001). Cupric stress (50 uM and 75uM) induced changes in antioxidant enzymes GPX and CATactivities of Phaseolus vulgaris. L plants. GPX (guaiacolperoxidase, EC 1.11.1.7) activity was decreased in 50 µM Cu-stressed leaves whereas 75 µM of CuSO4 resulted in anincrease of enzyme activity while CAT (catalase, EC 1.11.1.6)activity was stimulated at 50 µM CuSO4 but remained thesame at 75 µM CuSO4 (Bouazizi et al. 2010). It was reportedthat in pea plants that there was a decrease in catalase, SOD,


and guaiacol peroxidase activities when treated with CdCl2(0-50 mM). No significant changes in the glutathione reductaseactivity were shown by the treated plants (Sandalio et al.2001). Dixit et al. (2001) also reported the effects of 4 and40uM cadmium on the antioxidants and antioxidant enzymesin the pea roots and leaves, separately. The results indicatedthat the levels of lipid peroxidation and H2O2 increased inboth the roots and leaves. Activities of SOD, APX, GST andGR were more at 40 uM concentration while GPOX decreasedin the roots. Aluminium phytotoxicity causes oxidative stressin developing green gram seedlings and a significant increasein lipid peroxidation, peroxide content accompanied by adecrease in catalase activity (Panda et al. 2003). However,superoxide dismutase, peroxidase and glutathione reductaseactivities increased with increasing aluminium concentrations.Both the contents of glutathione and ascorbate decreasedwith the elevated metal concentrations. In another experimentthe effect of aluminium on lipid peroxidation, superoxidedismutase, catalase, and peroxidase activities in root tips ofsoybean (Glycine max) were investigated (Cakmak and Horst1991). Soybean seedlings treated with Al (AlCI 3)concentrations ranging from 10 to 75 µM showed theenhancement of lipid peroxidation in the crude extracts of theroot tips, the activities of SOD and peroxidase increased whilecatalase decreased. The effects of cadmium 5 uM and zinc 100uM on the antioxidant enzyme activities in bean (Phaseolusvulgaris) were reported (Chaoni et al.1997). Lipid peroxidationwas enhanced in all plant organs of the plant and the catalaseactivity was decreased in both roots and leaves but not instems. Mercury toxicity in alfaalfa (Medicago sativa) bytreating the plants with 0–40 µM HgCl2 for 7 d resulted inoxidative stress (Zhou 2007). It was observed that treatmentwith Hg2+ increased the activities of NADH oxidase andlipoxygenase (LOX) and damaged the biomembrane lipids.There was enhancement in the total activities of APX, PODand CAT. Several antioxidative metabolites such as ascorbateand glutathione (GSH) differentially accumulated in leaves.

Table:1 Location and function of nonenzymatic antioxidants in plant cellAntioxidant Location in the plant Function α –tocopherol Chloroplast envelope, thylakoid membranes and plastoglobuli. Deactivating the photosynthesis-derived ROS and scavenging

lipid peroxyl radicals in thylakoid membranes Ascorbic Acid Usually higher in photosynthetic cells and meristems (and some

fruits) and highest in mature leaves with fully developed chloroplast Powerful water soluble antioxidant, prevent or minimize the damage caused by ROS.

Glutathione Cell compartments like cytosol, ER, vacuole, mitochondria, chloroplasts, peroxisomes and in apoplast

Role in antioxidative defense, regulation of sulfate transport, signal transduction, detoxification of xenobiotics and the expression of stress-responsive genes

Carotenoids Leaves, fruits and floral parts Photoprotective role in addition to scavenging of ROS. Proline Cytosol Osmoregulation, seed germination, membrane integrity, inhibition

of water loss and an antioxidant Salicylic Acid Cytosol Seed germination, stomatal closure, an antioxidant Flavonoids Leaves, floral parts, and pollens. Role as an antioxidant, flowers, fruits, and seed pigmentation,

protection against UV light, defence against phytopathogens role in plant fertility and germination of pollen.

4.2 Non enzymatic defense systems

The non enzymatic defense systems of the plantsinclude various molecules such as glutathione, proline,-tocopherols, carotenoids and flavonoids. Variousantioxidants like cysteine, proline, ascorbic acid and non-protein thiols also play an important role in detoxification oftoxic metal ions (Singh and Sinha 2005). Their involvement indefense against metals in described below in legumes.4.2. a. -tocopherol (Vitamin E)

It is the major vitamin E compound found in leafchloroplasts, where it is primarly located in the chloroplastenvelope, thylakoid membranes and plastoglobuli. (Table.1).It is responsible for deactivating the photosynthesis-derivedreactive oxygen species and thus preventing the propagationof lipid peroxidation by scavenging lipid peroxyl radicals inthylakoid membranes. The alpa-tocopherol levels are verysensitive to environmental stresses and change differentiallydepending on the magnitude of the stress and species-sensitivity to stress. Recently, it has been found that oxidativestress activates the expression of genes responsible for thesynthesis of tocopherols in higher plants (Wu et al. 2007).Srivastava et al. (2005) reported a general induction in-tocopherol content in Anabaena doliolum under NaCl andCu2+ stress. The effects of lead, copper, cadmium and mercuryon the content of chlorophyll, proline, retinol, -tocopheroland ascorbic acid were investigated in 17-day-old beanseedlings (Phaseolus vulgaris L.) A significant increase inthe levels of -tocopherol was indicated, also increase inproline and ascorbic acid was reported (Zengin andMunzuroglu 2005).4.2.b. Ascorbic acid (Vitamin C)

Ascorbic acid (ASC) is the most abundant, powerfuland water soluble antioxidant acts to prevent or in minimizingthe damage caused by ROS in plants. It also occurs in all plant

1 0 Journal of Food Legumes 26(3 & 4), 2013

tissues, usually being higher in photosynthetic cells andmeristems in and some fruits. Its concentration is reported tobe highest in mature leaves with fully developed chloroplastand with highest chlorophyll. Usually, ASC remains availablein reduced form in leaves and chloroplast under normalconditions (Smirnoff 2000). Studies report that the ASC contentof the roots and shoots of two cultivars of pigeonpea (Cajanuscajan) decreased with an increasing concentration (MadhavaRao and Sresty 2000) of Zn and Ni. The effect of ascorbic acidon soybean seedlings grown on medium containing a highconcentration of copper were investigated (Golan-Goldhirshet al. 1995) and reported that ascorbic acid prevented theentry of Cu into the plant roots and did not let copper toxicitysigns. There are some reports where a decrease in the ascorbicacid in the roots and nodules of Glycine max under Cd stresshas also been observed (Balestrasse et al. 2004). Cd alsodecreases the ascorbic acid content in the leaves ofA. thaliana and P. sativum (Romero-Puertas et al. 2007).4.2.c.Glutathione

Glutathione is one of the crucial metabolites in plants,which is considered as most important intracellular defenseagainst ROS induced oxidative damage. It generally occursabundantly in reduced form (GSH) in plant tissues and ismostly localized in all cell compartments like cytosol,endoplasmic reticulum, vacuole, mitochondria, chloroplasts,peroxisomes as well as in apoplast and plays a central role inseveral physiological processes, including regulation ofsulfate transport, signal transduction, conjugation ofmetabolites, detoxification of xenobiotics and the expressionof stress-responsive genes (Mullineaux et al. 2006). GSH playsa key role in the antioxidative defense system by regeneratinganother potential water soluble antioxidant like ASC, via theASC-GSH cycle (Foyer and Halliwell 1976). With increase instress, GSH concentrations usually decline and redox statebecomes more oxidized, leading to degradation of the plantsystem (Tausz et al. 2004). During heavy metal stress, GSHconcentration in the cell elevates. For example, increasedconcentration of GSH has been observed with the increasingCd concentration in P. sativum (Metwally et al.2005) andV. mungo (Molina et al. 2008). On the other hand, Srivastavaet al. (2005) reported an appreciable decline in GR activity andGSH pool under Cu stress in Anabaena dolicum andsignificantly higher increase under salt stress.4.2.d. Carotenoids

Carotenoids are the protective pigments that are foundin plants and microorganisms. These are lipid solubleantioxidants playing many functions in plant metabolismincluding oxidative stress tolerance. A decrease in carotenoidand chlorophyll contents in V. mungo plants with increasingCd concentration was observed (Rai et al. 2004, Singh et al.2008). In H. vulgare seedlings also, a reduction in carotenoidscontent was observed under Cd-stress (Demirevska-Kepovaet al. 2006).

4.2.e.Proline

Proline accumulation, accepted as an indicator ofenvironmental stress, is also considered to have importantprotective roles.Some authors have suggested that prolineacts as an antioxidant in Cd-stressed cells and therebyimproves metal tolerance (Sharma and Dietz 2006,Siripornadulsil et al. 2002). Others have reported that manyplants have been reported to accumulate proline (Pro) whenexposed to heavy metals (Alia and Saradhi 1991, Talanova etal. 2000). However, the precise mechanism and the functionalsignificance of proline accumulation in plants under heavymetal stress have not been elucidated to date. Costa and Morel(1994) have suggested that proline accumulation in plantsunder Cd stress is induced by a Cd imposed decrease of theplant water potential. However, proline maintains the waterbalance under Cd stress thereby suggesting that proline-mediated alleviation of water deficit stress could substantiallycontribute to the Cd tolerance of the plant. But the directconclusive evidence as to the role for the water potential inheavy metal-induced proline accumulation is still lacking. Arecent study has shown that proline alleviates Cd toxicity bydetoxifying ROS, and increasing the activity of SOD and CATand glutathione content (Xu et al. 2009). Rai (2002) suggeststhat the possible role of proline against heavy metals is byforming chelates with the metals. There are indications thatproline forms a proline-metal complex and protects the activityof glucose-6-phosphate dehydrogenase and nitrate reductaseagainst inhibition by Cd and Zn (Sharma et al.1998). Apartfrom acting as an heavy metal alleviator, proline also acts asan important cytoplasmic osmoticum, a scavenger of freeradicals, source of nitrogen and carbon for post stress growth,a stabilizer of membranes, machinery for protein synthesisand a sink for energy to regulate redox potential (Rai et al.2004). Muneer et al. (2011) reported that proline contentincrease at all concentrations of cadmium exposure in Vignaradiata and maximum increase was found at 0.50 mM whichwas about 119 to 120%. In Cajanus cajanand Vigna mungothere was an accumulation of proline under heavy metals(Co, Cd. Zn and Pb) treatment (Alia and Saradhi 1991). Similarresults were observed in case of Cajanus cajan when givenaluminium treatment (Bhamburdekar and Chavan 2011).4.2.f. Phenolics

Salicylic acid is an important signal molecule mediatingmany biotic and environmental stress-induced physiologicalresponses in plants. The role of SA in regulating Hg-inducedoxidative stress was investigated in the roots of alfalfa(Medicago sativa) by Zhou et al. 2006. It was seen that theplants pretreated with 0.2mM SA for 12 h and subsequentlyexposed to 10 µM Hg2+ for 24 h attenuated toxicity to the rootand also decreased lipid peroxidation in root cells. Thissuggests that exogenous SA may improve the tolerance ofthe plant to the Hg toxicity. Flavonoids, a related group ofphenolics, occur widely in the plant kingdom, and are

Kaur & Nayyar : Heavy metal toxicity to food legumes: effects, antioxidative defense and tolerance mechanisms 1 1

commonly found in leaves, floral parts, and pollens. Theyusually accumulate in the plant vacuole as glycosides, butthey also occur as exudates on the surface of leaves andother aerial plant parts. Flavonoids are suggested to havemany functions in flowers, fruits, and seed pigmentation,protection against UV light, defence against phytopathogens(pathogenic microorganisms, insects, animals), role in plantfertility and germination of pollen and, molecules in plant-microbe interaction. Apart from the above roles, flavonoidshave as antioxidative activity (Brown et al.1998). Besideshaving the function of ROS scavenging , flavonoids are ableto function as chelators for metals, depending on the molecularstructure (Brown et al.1998) and hence can take part in plantdefence. In Arabidopsis thaliana, the relation betweenflavonoids and heavy metal tolerance were investigated. BothArabidopsis wild type and mutant lines with a defect inflavonoid biosynthesis were grown on media containingdifferent heavy metals. Results revealed that root length andseedling weight were reduced in mutants more than in thewild type when grown on cadmium, while on zinc only rootlength was affected (Keilig and Muller 2009).5. Tolerance mechanisms

Heavy metals in the plant environment operate as stressfactors that cause physiological strain and in doing so theyreduce the plant vigour and totally inhibit the plant growth inextremes However, plants have evolved several physiologicalmechanisms which enable them to tolerate metal toxicity (Baker1987). The development of metal tolerance in plants is a majorway to reduce the harmful effects of excessive exposure toheavy metal ions (Tyler et al.1989). There are various potentialcellular and other mechanisms available for metaldetoxification and tolerance in higher plants (Hall 2002), whichhave been reported to function in legumes.5.a. Role of Arbuscular mycorrhizal fungi

Mycorrhizal association is a symbiotic non-pathogenicrelationship between plant roots and fungal hyphae with afungal connection between the soil and the root (Harley andSmith 1983). It has been reported that the host plant receivessupport from AM fungi, with the help of its symbioticassociation, in the aspect of uptake of phosphorus and othernutrients, enhancement of growth hormones, increase ofprotein content, increase of lipid, sugars, amino acid levels,increase of tolerance to heavy metals, increase of salinitytolerance, and resistance to root-borne pathogens(Upadhyaya et al. 2010). Recently, the symbiotic associationwith mycorrhizal fungi has been proposed as one of the majormechanisms of plant HM-tolerance (Hall 2002, Joachimet al. 2009). However, alleviating heavy metal toxicity by AMFcolonization can vary to a large extent, depending on whichheavy metal is involved, its concentration in the soil, the fungalsymbiosis partner and the conditions of plant growth (Turnau1998).

There are manystrategies adopted byAM which canalleviate heavy metalthreats in mixedculture systems and,thus, from the foodchains (Joschim et al.2009). These includethe immobilisation ofmetal compounds,precipitation ofp o l y p h o s p h a t egranules in the soil,adsorption to chitin inthe fungal cell wallsand chelation ofheavy metals inside the fungus (Joachim et al. 2009). Generally,AM binds to heavy metals beyond the plant rhizosphere byreleasing an insoluble glycoprotein commonly known asglomalin (Gonzalez- Chavez et al. 2004). The roles of AM aresummarized in the Fig.5.

Numerous studies have indicated that AMF candecrease the metal uptake of the host plants, thus protectingthem against HMs toxicity (Leyval et al. 1997). Many heavymetal contaminated sites are reported to have mycorrhizae(Weissenhorn and Leyval 1993).This indicates that these fungihave evolved a HM-tolerance and that they may play a role inthe phytoremediation of the site (Khan et al. 2000).Mycorrhizae were found to ameliorate the toxicity of tracemetals in polluted soils growing in soybean and lentil plants(Jamal et al. 2002). Increased heavy metal tolerance of plantsby dual inoculation of an arbuscular mycorrhizal fungi andnitrogen-fixer Rhizobium bacterium was reported in cowpea(Al-Garni 2006). The effects of dual inoculation with arbuscularmycorrhizal (AM) fungus and Rhizobium (N-fixing bacteria,NFB) on the host plant cowpea Vigna sinensis in pot cultureswere investigated at six concentrations of Zn (0.0-1000 mg/kgdry soil) and Cd (0.0-100 mg/kg dry soil). The study providesevidence for benefits of NFB to AM fungi in the protection ofhost plants against the detrimental effects of heavy metalsand provides the mechanisms for metal tolerance againstthem.A greenhouse pot experiment was done to investigatethe effects of the colonization of arbuscular mycorrhizal fungus(AMF) Glomus mosseae on the growth and metal uptake ofthree leguminous plants (Sesbania rostrata, Sesbaniacannabina, Medicago sativa) grown in multi-metalcontaminated soil (Lin et al. 2007). The results revealed thatAMF colonization increased the growth of the legumes therebyindicating that AMF colonization increased the plant’sresistance to heavy metals. The effect was also enhanced onthe formation of root nodules and N and P uptake increased,which may be due to the heavy metal tolerance mechanismsconferred by the AMF.

Fig: 5 Steps for alleviating heavymetal stress adopted by AM fungi


5.b. Role of metallothioneins and phytochelatins

Metallothioneins (MT’s) belong to a family of cysteine-rich low molecular weight metal-binding proteins generallyinduced during the metal stress (Corbett and Goldsbrough2002). Metallothioneins generally form complexes with heavymetal ions and are present in almost all forms of life and havea role in protecting cells from the deleterious effects of highconcentration metal ions. The function of MT is to detoxifynon-essential metals such as mercury, cadmium and essentialmetals such as zinc and copper.

Phytochelatins (PCs), a type of MT’s, are synthesizedin plants in response to heavy metal stress and due to variousmetals. PCs consist of only the three amino acids: Glu, Cysand Gly, the Glu, and Cys residues linked through a g-carboxylamide bond(Cobbet 2000).Recent research indicatesthat PCs are present in a wide variety of plant species and insome microorganisms. They are structurally related toglutathione (GSH, g-Glu-Cys-Gly) and were presumed to bethe products of a biosynthetic pathway. In addition, a numberof structural variants, for example, (g-Glu-Cys)n-b- Ala, (g-Glu-Cys)n-Ser, and (g-Glu-Cys)n-Glu, have been identified insome plant species (Rauser 1999, Zenk 1996).

Activation of the detoxicative-phytochelatin system wasobserved in the cytosol of root cells of three legume species,Vicia faba, Pisum sativum, and Phaseolus vulgaris when theywere exposed to lead ions (Piechalak et al. 2002). This systemwas composed of phytochelatins (PCs) in roots of V. faba,homophytochelatins (hPCs) in P. vulgaris roots, and bothPCs and hPCs in P. sativum roots.5.c. Organic acids and amino acids

Some amino acids, particularly histidine and proline,also play very important roles in the chelation of metal ionsboth within plant cells and in the xylem sap (Rai 2002). Kerkeband Krämer (2003)have reported that in Alyssum lesbiacumand Brassica juncea , an enhanced release of Ni into the xylemis associated with concurrent release of histidine from anincreased root free His pool. Other amino acids such as citrate,malate and histidine are potential ligands for heavy metalsand could play a role in tolerance and detoxification (Rauser1999). Citrate, malate and oxalate have been involved intransport of metal ions through the xylem and vacuolarsequestering (Rauser 1999). It is reported that citric acid to bea major Cd2+ ligand at low Cd2+ concentrations (Wagner 1993)and has been shown to form complexes with Ni2+ in Ni-hyperaccumulation plants (Sagner et al. 1998). It is alsosuggested that malate is a cytosolic zinc chelator in zinc-tolerant plants (Mathys 1977). Kramer et al.(1996) reportedthat the significant and proportional change in amino acid ororganic acid concentration elicited by a change in metalexposure was shown by histidine response in plants thataccumulate nickel. The presence of different concentrationsof organic acids among various ecotypes of metal-tolerant

plants in their natural habitat has deemed these substancesas likely cellular chelators (Rauser 1999).5.d. Polyamines

Polyamines (PAs) are nitrogenous compounds presentin all living cells. They are not only involved in various cellularprocesses like growth promotion and cell division but also inthe inhibition of ethylene production and senescence (Tiburcioet al.1997). They influence a variety of growth anddevelopment processes in plants which have been suggestedto be a class of plant growth regulators and to act as secondmessengers (Evans and Malmberg 1989, Kakkar and Sawhney2002). The polyamines are cations due to protonation atcytoplasmic pH, i.e. putrescine2+, spermidine3+, and spermine4+,which accounts for their binding ability to nucleic acids (Flinkand Pettijohn 1975).It has been reported that the levels ofpolyamines and the activities of their biosynthetic enzymesin plants increase under environmental stresses (Evans andMalmberg 1989). Polyamine contents are highly altered inresponse to the exposure to heavy metals. For example, theresponse of different polyamines to Cd treatment stronglyvaried in Phaseolus vulgaris in an organ-specific manner.Putrescine increased in root, hypocotyl, and epicotyl whereasspermidine increased in hypocotyl, decreased in leaves, anddid not change in roots.In soybean phospholipids, usingmembrane vesicles (Weinstein et al. 1986). Tadolini et al. (1984)showed that polyamines inhibit lipid peroxidation when boundto the negative charges on the vesicle surface. In addition,polyamines namely, spermine, spermidine, putrescine, andcadaverine have been demonstrated to scavenge free radicalsin vitro (Drolet et al.1986). Furthermore, polyamines blockone of the major vacuolar channels, the fast vacuolar cationchannel, and their accumulation could decrease ionconductance at the vacuolar membrane to facilitate metal ioncompartmentation (Bru¨ggemann et al.1998). Their roles inmetal tolerance remain to be explored in detail.

Conclusion

Heavy metal contaminations seriously threaten theproductivity of plants and particularly the legumes which areimportant atmospheric nitrogen fixers and an excellent sourceof protein to both animals and human beings. These metalsprove to be deleterious for the legume growth and physiology,and ultimately enter the food chain to affect human population.In spite of presence of diverse tolerance mechanisms to toxicmetals, legumes suffer due to their cultivation in contaminatedsoils. The knowledge about metal tolerance mechanismsgained from model plants such as Arabidopsis needs to beexplored in legumes too to induce tolerance to metals. Variousmechanisms involving phytochelatins, thiols, transportersbased in plasma membrane and tonoplast need to bemanipulated through genetic means to enhance the metaltolerance in legumes.


Acknowledgement

The Financial assistance in the form of fellowship fromUniversity Grants Commission, New Delhi, to the first authoris gratefully acknowledged.

References

Athar R and Ahmad M. 2002. Heavy metal toxicity in legume –microsymbiont system. Journal of Plant Nutrition.25:369-386.

Al-Garni SMS. 2006. Increased heavy metal tolerance of cowpea plantsby dual inoculation of an arbuscular mycorrhizal fungi and nitrogenfixer rhizobium. African Journal of Biotechnology.5:133-142.

Ahmad E, Almas Z, Mohammad SK and Mohammad O.2012. Heavymetal Toicity to Symbiotic Nitrogen-Fixing microorganism andHost Legumes.In Toxicity of heavy metals to legume andbioremediation. Eds.A.Zaidi,PA Wani and MS Khan.Pp 248.

Ahmad MSA, M Hussain, S Ijaz and AK Alvi. 2008. Photosyntheticperformance of two mung bean (Vigna radiata (L.) wilczek) cultivarsunder lead and copper stress. International Journal of Agricultureand Biology.10: 167–72.

Alia and Saradhi PP. 1991. Proline accumulation under heavy metalstress.Journal of Plant Physiology 138:554-558.

Al-Qurainy Fahad 2009. Toxicity of Heavy Metals and Their MolecularDetection on Phaseolus vulgaris (L.) Australian Journal of Basic &Applied Sciences.3:3025

Al-Rumaih MM, Rushdy SA and Warsy AS. 2001. Effect of cadmiumchloride on seed germination and growth characteristics of cowpea,Vigna unguiculata L. plants in the presence and absence of gibberellicacid. Saudi Journal of Biological Sciences 8:41-51.

Al-Yemeni and Mohammed-Nasser. 2001. Effect of cadmium, mercuryand lead on seed germination and early seedling growth of Vignaambacensis L. Indian Journal of Plant Physiology 6: 147-151.

Angelov MT, Tsonev A, Uzunova K and Gaidardjieva.1993. Cu2+ effectupon photosynthesis, chloroplast structure, RNA and proteinsynthesis of pea plants. Photosynthetica 28: 341-350.

Antipchuk AF, Rangelova VN and Tantsurenko FV. 2000. Effects ofheavy metals and reclaimerson formation and functioning of legume– rhizobial symbiosis. Mikrobiologi Chnii-Zhurnal 62:44-50.

Arora NK, Khare E, Singh S and Maheshwari DK. 2010.Effect ofaluminium and heavy metals on enzymes of nitrogen metabolismof fast and slow growing rhizobia under explanta conditions. WorldJournal of Microbiology and Biotechnology 26:811–816.

Atici O, H Outcu and OF Algur. 2005. Effect of putrescine on inducingsymbiosis in chickpea and vetch inoculated with commercial orindigenous strains of Rhizobium. Symbiosis.38: 163-174.

Aydinalp C and Marinova S. 2009. The effects of heavy metals on seedgermination and plant growth on alfalfa plant (Medicago sativa).Bulgarian Journal of Agricultural Science15:347-350.

Babich H and Stotzky G. 1978. Effects of cadmium on the biota:Influence of environmental factors. Advances in AppliedMicrobiology 23:55–117.

Baker AJM.1987. Metal tolerance.New Phytologist .106:93-111.

Bakkaus E, Gouget B, Gallien JP, Khodja H, Carrot H, Morel JL andCollins R. 2005. Concentration and distribution of cobalt in higherplants: the use of micro-PIXE spectroscopy. Nuclear Instrumentsand Methods. 231:350–356.

Balestrasse,KB, Gallego SM and Tomarol ML. 2004. Cadmium-induced

senescence in nodules of soybean (Glycine max L.) plants.Plantand Soil.262: 373–381.

Barceló J and Poschenrieder CM. 1999. Structural and ultrastructuralchanges in heavy metal exposed plants. In. Heavy Metal Stress inPlants, from Molecules to Ecosystems. (Eds Prasad MNV andHagemeyer J ). Springer Verlag, Berlin.Pp183-205.

Barcelo J, Vazquez MD and Poschenrieder CH. 1987. Structural andultrastructural disorders in cadmium-treated bush bean plants(Phaseolus vulgaris L.). New Phytologist 108:37–49.

Baszynski T, Wajda L, Krol M, Wolinska D, Krupa Z and Tukendorf A.1980. Photosynthetic activities of cadmium-treated tomato plants.Plant Physiology 48:365–370.

Bera AK, Kanta-Bokaria AK and Bokaria K. 1999.Effect of tanneryeffluent on seed germination, seedling growth and chloroplastpigment content in Mungbean (Vignaradiata LWilczek).Environment and Ecology 17:958–961.

Bhardwaj P, Chaturvedi AK and Prasad P. 2009. Effect of enhancedlead and cadmium in soil on physiological and biochemical attributesof Phaseolus vulgaris L. Nature and Science7:63-75.

Bhat MT, Ansari MY, Choudhary S, Aslam R and Alka. 2011. SynergisticCytotoxic Stress and DNA Damage in Clover (Trifolium repens )Exposed to Heavy Metal Soil from Automobile Refining Shops inKashmir-Himalaya. ISRN Toxicology2011:1-7.

Bhamburdekar SB and Chavan PD. 2011. Effect of Some Stresses onFree Proline Content During Pigeonpea (Cajanas cajan) SeedGermination. Journal of Stress Physiology & Biochemistry.7: 235-241.

Bianucci E, Fabra A and Castro S. 2011.Cadmium Accumulation andTolerance in Bradyrhizobium spp. (Peanut Microsymbionts).Current Microbiology 62:96–100.

Bibi M and Hussain M. 2005.Effect of copper and lead on photosynthesisand plant pigments in black gram (Vigna mungo (L.)Hepper).Bulletin of Environmental Contamination and Toxicology74:1126–33.

Blaylock MJ and Huang JW. 2000. Phytoextraction of metals.Phytoremediation of toxic metals: using plants to clean up theenvironment. (Eds. Raskin I and Ensley BD). John Wiley and Sons,Toronto.Pp303.

Böddi B, Oravecz AR and Lehoczki E. 1995.Effect of cadmium onorganization and photoreduction of protochlorophyllide in dark-grown leaves and etioplast inner membrane preparations of wheat.Photosynthetica 31:411-420.

Bouazizi H, Jouili H, Geitmann A and Ferjani EEI. 2010. Copper toxicityin expanding leaves of Phaseolus vulgaris L.: antioxidant enzymeresponse and nutrient element uptake. Ecotoxicology andEnvironmental Safety 73:1304–1308.

Broos K, Beyens H and Smolders E. 2005. Survival of rhizobia in soil issensitive to elevated zinc in the absence of the host plant. SoilBiology and Biochemistry 37:573–579.

Brown JE, Khodor H, Hider RC and Rice-Evans CA. 1998. Structuraldependence of flavonoid interactions with Cu2+ ions: implicationsfor their antioxidant properties. Biochemical Journal330: 1173-1178.

Brüggemann LI, Pottosin I I and Schönknecht G. 1998. Cytoplasmicpolyamines block the fast-activating vacuolar cation channel. thePlant Journal16:101–105.

Brun LA, Maillet J, Hinsinger P and Pepin M. 2001.Evaluation ofcopper availability to plants in copper-contaminated vineyard soils.Environmental Pollution 111: 293–302.


Brynhildsen L and Rosswall T. 1997. Effects of metals on the microbialmineralization of organic acids. Water, Air, and Soil Pollution 94:45–57.

Budnikov G. 1998. Heavy metals in the ecological monitoring in watersystems.Educational Journal of Trorosovsk. 5: 23-29 (In Russian).

Cobbett C and Godsbrough P. 2002. Phytochelatins andmetallothioneins: Roles in heavy metal detoxification andhomeostatis. Annual Review of Plant Biology.53:159-82.

Cobbett CS. 2000. Phytochelatins and heavy metal tolerance inplants.Current Opinion in Plant Biology.3:211-216.

Cakmak I, Horst WJ and Bangruth F. 1989. Effect of Zinc NutritionalStatus on Growth, Protein Metabolism and Levels of Indole-3-acetic acid and other phytohormones in bean (Phaseolus vulgarisL.). Journal of Experimental Botany.40:405-412.

Cakmak I and Horst WJ. 1991. Effect of aluminum on lipid peroxidation,superoxide dismutase, catalase and peroxidase activities in root tipsof soybean (Glycine max) .Physiolgia Plantarum. 83: 463-468.

Cargnelutti D, Tabaldi LA, Spanevello RM, Jucoski GO, Battisti V,Redin M, Linares CEB, Dressler VL, Flores MM, Nicoloso FT,Morsch VM and Schetinger MRC. 2006. Mercury toxicity inducesoxidative stress in growing cucumber seedlings. Chemosphere65:999–1006.

Cervantes C, Campos-Garcia J, Debars S, Gutierrez-Corona F, Loza-Tavera H, Carlos-Tarres-Guzman M and Moreno-Sanchez R. 2001.Interaction of chromium with Microgenesis and plants. FEMSMicrobiology Reviews 25:335-347.

Chaudri AM, McGrath SP, Giller KE, Reitz E and Suerbeck DR. 1993.Enumeration of indigenous Rhizobium leguminosarum biovartrifolii in soils previously treated with metal contaminated sewagesludge. Soil Biology and Biochemistry .25:301–309

Chaoni A, Mazhoudi S, Groebal MH and Ferjani EI. 1997. Cadmium andzinc induction of lipid peroxidation and effects on antioxidantenzyme activities in bean (Phaseolus vulgaris L.). Plant Science127:139-147 .

Chaudri AM, Allain CM, Barbosa-Jefferson VL, Nicholson FA, ChambersBJ and McGrath SP. 2000. A study of the impacts of Zn and Cu ontwo rhizobial species in soils of a long term field experiment. PlantSoil 22:167–179.

Chen GH and Goldsbrough PB.1994. Increased activity of c-glutamylcysteine synthetase in tomato cells selected for cadmiumtolerance. Plant Physiology 106:233–239.

Chen YX. He YF, Yang Y, Yu YL, Zheng SJ, Tian GM, Luo YM andWeng MH. 2003. Effect of cadmium on soybean in contaminatedsoils. Chemosphere.50:781-7.

Cheng SP. 2003. Effects of heavy metals on plants and resistancemechanisms.Environmental Science and Pollution Research 10:256-264.

Chugh LK and Sawhney SK. 1996.Effect of cadmium on germination,amylases and rate of respiration of germinating pea seeds.Environmental Pollution 92:1-5.

Chugh, LK. and SK. Sawhney. 1999. Photosynthetic activities of Pisumsativum seedlings grown in presence of cadmium. Plant Physiologyand Biochemistry.37: 297-303.

Clijsters H and Assche F. 1985. Inhibition of photosynthesis by heavymetals. Photosynthesis Research 7:31–40.

Costa G and Morel JL. 1994. Water relations, gas exchange and aminoacid content in Cd-treated lettuce. Plant Physiological andBiochemistry 32:561-570.

Cox RM. 1988.The sensitivity of pollen from various coniferous andbroad-leaved trees to combinations of acidity and trace metals.New Phytologist 109: 193-201.

Cunningham SD, Shann JR, Crowley DE and Anderson TA. 1997.Phytoremediation of contaminated water and soil. (Eds. KrugerEL, Anderson TA and Coats JR). ACS symposium series 664,American Chemical Society, Washington.Pp2-19.

Dan T, Hale B, Johnson D, Conard B, Stiebel B and Veska E. 2008.Toxicity thresholds for oat (Avena sativa L.) grown in Ni-impactedagricultural soils near Port Colborne, Ontario, Canada. CanadianJournal of Soil Science 88:389–398.

Das P, Samantaray S and Rout GR. 1997. Studies on cadmium toxicityin plants:a review.Environmental Pollution 98:29-36.

De Carvalho MM, Edwards DG, Asher CJ and Andrew CS. 1982.Effectsof aluminium on nodulation of two Stylosanthes species grown innutrient solution. Plant and Soil 64:141-152.

de Vries W, Lofts S, Tipping E, Meili M, Groenenberg JE and Schütze G.2002. Impact of soil properties on critical concentrations ofcadmium, lead, copper, zinc, and mercury in soil and soil solution inview of ecotoxicological effects. Reviews of EnvironmentalContamination and Toxicology 191:47–89.

Demirevska–Kepova K, Simova–Stoilova L, Stoyanova ZP and FellerU. 2006. Cadmium stress in barley: growth, leaf pigment, andprotein composition and detoxification of reactive oxygen species.Journal of Plant Nutrition 29:451-468.

Dewan MM and HR Dhingra. 2004. Cadmium partitioning and seedquality in two varities of pea and their hybrid as influenced byrhizopheric cadmium. Indian Journal of Plant Physiology 9:15-20.

di Toppi LS and Gabbrielli R. 1999. Response to Cadmium in HigherPlants.Environmental and Experimental Botany 41: 105-130.

Dixit V, Pandey V and Shyam R .2001.Differential oxidative responsesto cadmium in roots and leaves of pea (Pisum sativum L cv.Azad).Journal of Experimental Botany. 52:1101-1109.

DraÛzkiewicz M, Sko _ ´rzyn´ska-Polit E , Krupa Z.2004. Copper-induced oxidative stress and antioxidant defence in Arabidopsisthaliana. BioMetals .17: 379–387.

Drolet G, Dumbroff EB, Legge RL and Thompson JE.1986.Radicalscavenging properties of polyamines.Phytochemistry.25:367-371.

Duan C and Wang H. 1995. Studies on the cell gene-toxicity of heavymetals to beans and micro-nuclear techniques. Acta Botanica Sinica37:14-24 (In Chinese with English abstract).

Ebbs SD and Kochian LV. 1997. Toxicity of zinc and copper to Brassicaspecies: implications for phytoremediation. Journal ofEnvironmental Quality 26:776–781.

Egharevba and Omoregie H.2010. Effect of Cadmium on Seed Viabilityof Vigna unguiculata, Ethnobotanical Leaflets:14:413-419.

Evans PT and Malmberg RL. 1989. Do polyamines have roles in plantdevelopment? Annual Review of Plant Physiology and PlantMolecular Biology. 40:235–269.

Feng J, Shi Q, Wang X, Wei M, Yang F and Xu H. 2010. SiliconSupplementation Ameliorated the Inhibition of Photosynthesis andNitrate Metabolism by Cadmium (Cd) Toxicity in Cucumis sativusL. Scientia Horticulturae 123:521-530.

Finnegan PM and Chen W. 2010. Arsenic toxicity: The effects onplant metabolism.Frontiers in Physiology.3:182-238

Flink I and Pettijohn DE. 1975.Polyamines stabilise DNAfolds. Nature. 253:62–63.


Fontes RLS and Cox FR. 1998. Zinc toxicity in soybean grown at highiron concentration in nutrient solution. Journal of Plant Nutrition21:1723–1730.

Foyer CH and Halliwell B. 1976. The presence of glutathione andglutathione reductase in chloroplasts: a proposed role in ascorbicacid metabolism. Planta 133:21-25.

Ghosh M and Singh SP. 2005.A review on phytoremediation of heavymetals and utilization of its byproducts. Applied Ecology andEnvironmental Research 3:1-18.

Gimeno-García E, Andreu V and Boluda R. 1996.Heavy metals incidencein the application of inorganic fertilizers and pesticides to ricefarming soils.Environmental Pollution 92:19 –25.

Gill SS and Tuteja N. 2010. Reactive oxygen species and antioxidantmachinery in abiotic stresstolerance in crop plants t Physiologyand Biochemistry.48 :909-930.

Gincchio R, Rodriguez PH, Badilla-Ohlbaum R, Allen HE and Lagos GE.2002. Effect of soil copper content and pH on copper uptake ofselected vegetables grown under controlled conditions.Environmental Toxicology Chemistry 21:1736–1744.

Golan-Goldhirsh A,Mozafar A and Oerlli JJ. 1995. Effect of ascorbicacid on soybean seedlings grown on medium containing a highconcentration of copper. Journal of Plant Nutrition 18:1735-1741.

Gomez-Arroyo S, Cortés-Eslava J, Bedolla-Cansino RM, Villalobos-Pietrini R, Calderón-Segura ME and Ramírez-Delgado Y. 2001.Sisterchromatid exchanges induced by heavy metals in Vicia faba. Journalof Plant Biology 44:591-594.

Gonzalez-Chavez MC, Carrillo-Gonzalez R, Wright SF and NicholsKA. 2004. The role of glomalin, a protein produced by arbuscularmycorrhizal fungi, in sequestering potentially toxic elements.Environmental Pollution 130:317–323.

Gupta YP. 1987. Anti-nutritional and toxic factors in food legumes:areview. Plant foods for human nutrition.37:201-228.

Hall JL. 2001. Cellular mechanisms for heavy metal detoxification andtolerance.Journal of Experimental Botany.56:1-11.

Han FX, Sridhar BBM, Monts DL and Su Y. 2004.Phytoavailability andtoxicity of trivalent and hexavalent chromium to Brassica juncea LCzern. New Phytologist 162:489–499.

Harley H. and SE Smith.1983.Mycorrhizal symbiosis. Academic Press,London

Heckman JR, Angle JS and Chaney RL. 1987. Residual effects of sewagesludge on soybean II. Accumulation of soil and symbiotically fixednitrogen.Journal of Environmental Quality 16:117–124.

Hirsch PR, Jones MJ, McGrath SP and Giller KE. 1993. Heavy metalsfrom past applications of sewage sludge decrease the genetic diversityof Rhizobium leguminosarum biovar trifolii populations. SoilBiology and Biochemistry 25:1485–1490.

Hossain MA, Hasanuzzaman M and Fujita M. 2010. Up-Regulation ofAntioxidant and Glyoxalase Systems by Exogenous Glycinebetaineand Proline in Mung Bean Confer Tolerance to Cadmium Stress.Physiology and Molecular Biology of Plants16:259-272.

Huang CY, Bajaj FA and Vanderhoef LN. 1974. The inhibition of soybeanmetabolism by cadmium and lead. Plant Physiology 54:122-124.

Israr M, Sahi S, Datta R and Sarkar D. 2006.Bioaccumulation andphysiological effects of mercury in Sesbania drummonii.Chemosphere 65:591–598.

Jamal A, Ayub N and Usman Mand Khan AG. 2002. Arbuscularmycorrhizal fungi enhance zinc and nickel uptake from

contaminated soil by bean and lentil. International Journal ofPhytoremediation.4:205–221.

Johnson MS and Eaton J. 1980.Environmental contamination throughresidual trace metal dispersal from a derelict lead-zinc mine. Journalof Environmental Quality 9:175–179.

Joschim HJ, Makoi R and Ndakidemi PA. 2009. The agronomic potentialof vesicular-arbuscular mycorrhiza (AM) in cereals– legumemixtures in Africa. African Journal of Microbiology Research.3 :664-675.

Kamel HA. 2008. Lead accumulation and its effect on photosynthesisand free amino acids in Vicia faba grown hydroponically.AustralianJournal of Basic and Applied sciences.3:438-446

Kakkar, R.K. and Sawhney V.K. 2002.Polyamine research in plants- achanging perspective. Phyiologia Plantarum 116 : 281-292.

Karina BB, Benavides MP, Gallego SM and Tomaro ML. 2003. Effectof cadmium stress on nitrogen metabolism in nodules and roots ofsoybean plants. Functional Plant Biology 30:57–64.

Keilig K and Ludwig-Muller J. 2009. Effect of flavonoids on heavymetal tolerance in Arabidopsis thaliana seedlings. Botanical Studies50:311-318.

Kerkeb L and Kra¨mer U .2003.The role of free histidine in xylemloading of nickel in Alyssum lesbiacum and Brassica juncea.PlantPhysiology.131:716–724.

Khan AG, Kuek C, Chaudhry TM and Khoo CS, and Hayes WJ.2000.Roleof plants, mycorrhizae and phytochelators in heavy metalcontaminated land remediation. Chemosphere 41:197–207.

Khan RM and Khan MM. 2010. Effect of varying concentration ofnickel and cobalt on the plant growth and yield of chickpea. AustralianJournal of Basic and Applied Sciences 4:1036-1046.

Kristen U, Hoppe U and Pape W. 1993. The pollen tube test: a newalternative to draize eye irritation assay. Journal of the Society ofCosmetic Chemists44:153-162.

Krupa Z and Baszynski T. 1995. Someaspects of heavy metals toxicitytowards photosynthetic apparatus direct and indirect effects onlight and dark reactions. Acta Physiologie Plantarum 17:177–190.

Kukier U, Peters CA, Chaney RL, Angle JS and Roseberg RJ. 2004. Theeffect of pH on metal accumulation in two Alyssum species. Journalof Environmental Quality 33:2090–2102.

Kumar G and Tripathi R. 2007. Lead induced cytotoxicity andmutagenecity in Grass Pea. Turkish Journal of Biology 32:73-78.

Leyval C, Turnau K, Haselwandter K .1997. Effect of heavy metalpollution on mycorrhizal colonization and function: Physiological,ecological and applied aspects. Mycorrhiza.7: 139–153.

Li HF, Gray C, Mico C, Zhao FJ and McGrath SP. 2009.Phytotoxicityand bioavailability of cobalt to plants in a range of soils.Chemosphere 75:979–986.

Li Z, McLaren RG and Metherell AK. 2004. The availability of nativeand applied soil cobalt to ryegrass in relation to soil cobalt andmanganese status and other soil properties. New Zealand Journal ofAgricultural Research 47:33–43.

Lin AJ, Zhang XH, Wong MH. 2007. Increase of multi-metal toleranceof three leguminous plants by arbuscular mycorrhizal fungicolonization.Environmental Geochemistry and Health 29:473–481.

Liu D, Jiang W and Gao X. 2003. Effect of cadmium on root growth,cell division and nucleoli in root tip cells of garlic. Plant Biology47:79-83.


Liu D, Jiang W and Li M. 1992. Effects of cadmium on root growth andcell division of the root tip of garlic (Allium sativum L.). ActaScientiae Circumstantiae 12:439-446 (In Chinese with Englishabstract).

Madhava Rao KV, Sresty TVS .2000.Antioxidative parameters in theseedlings of pigeonpea (Cajanus cajan (L.) Millspaugh) in responseto Zn and Ni stresses. Plant Sci. 157:113-128

Maksymiec 2007.Signaling responses in plants to heavy metal stress.ActaPhysiologie Plant arum.29:177–187.

Maksymiec W and Baszyn´ski T. 1996. Chlorophyll ûuorescence inprimary leaves of excess Cu-treated runner bean plants depends ontheir growth stages and the duration of Cu action. Journal of PlantPhysiology 149:196–200.

Maksymiec W. 1997.Effect of copper on cellular processes in higherplants. Photosynthetica 34:321–342.

Malik JA, Goel S, Sandhir R and Nayyar H. 2011. Uptake and distributionof arsenic in chick pea:Effects on seed yield and seed composition.Communications in soil science and plant analysis. 42:1728-1738

Mandal SM and Bhattacharyya RN. 2007. Heavy metal toxicity onseed germination of four pulses. International Journal of PlantSciences 2:124-127.

Mascher R,B Lippmann,S Holzinger and H Bergmann. 2002. Arsenatetoxicity:Effects on oxidative stress response molecules andenzymes in red clover plants.Plant Science.163:961-969.

Mathys W. 1977.The role of malate, oxalate, and mustard oil glucosidesin the evolution of zinc-resistance in herbage plants. PhysiologiaPlantarum. 40:130–136.

McCarthy MC, Romero-Puertas JM, Palma LM, Sandalio FJ, CorpasM,Gómez LA and Del Río .2001. Cadmium induces senescencesymptoms in leaf peroxisomes of pea plants. Plant, Cell andEnvironment 24:1065–1073.

Mcilveen WD and Cole HJr. 1974. Influence of heavy metals onnodulation of red clover. Phytopathology 64:583-589.

Metwally A, Safronova VI, Belimov AA and Dietz KJ. 2005. Genotypicvariation of the response to cadmium toxicity in Pisum sativum L.Journal of Experimental Botany 56:167-178.

Mo W and Li M. 1992. Effects of Cd2+ on the cell division of root tipin bean seedlings. Bulletin of Botany 9:30-34 (In Chinese withEnglish abstract).

Moftah AE. 2000. Physiological response of lead polluted tomato andegg plant to the antioxidant ethylene diurea. Menufiya Journal ofAgricultural Research 25:933–955.

Molina AS, Nievas C, Chaca MVP, Garibotto F, Gonza´lez U, MarsaSM, Luna C, Gime´nez MS and Zirulnik F. 2008. Cadmium-inducedoxidative damage and antioxidative defense mechanisms in Vignamungo L. Plant Growth Regulation 56:285-295.

Moustakas MT, Lanaras L, Symeonidis S and Karataglis 1994. Growthand some photosynthetic characteristics of field grown Avenasativa under copper and lead stress. Photosynthetica 30: 389-396.

Mullineaux MP, Karpinski S and Bakerlogy NR. 2006. Spatial Dependencefor Hydrogen Peroxide-Directed Signaling in Light-Stressed Plants.American Society of Plant Biologists 141:346–350.

Mumthas S,Chidambaram AA, Sundaramoorthy P and Ganesh KS.2010.Effect of Arsenic and Manganese on Root Growth and CellDivision in Root Tip Cells of Green Gram (Vigna radiata L.). Journalof Agricultural and Food 22:285– 297.

Muneer S, Qadri TN, Mahmooduzaffarand Siddiqi TO. 2011.Cytogenetic and biochemical investigations to study the response

of Vigna radiata to cadmium stress. African Journal of Plant Science5:183–192.

Nieboer E and Richardson DHS.1980. The replacement of the non-descript term “heavy metals” by a biologically and chemicallysignificant classification of metals ions. Environmental Pollution1:3-26.

Oladele EO, Odeigah PGC and Taiwo IA. 2013. The genotoxic effectof lead and zinc on bambara groundnut (Vigna subterranean). AfricanJournal of Environmental Science and Technology 7:9-13.

Ouzounidou G, Giamparova M, Moustakas M and Karataglis S. 1995.Responses of maize (Zea mays L.) plants to copper stress. I. Growth.Environmental and Experimental Botany 35:167–176.

Paivoke A. 1983. The long term effects of zinc on the growth anddevelopment, chlorophyll content and nitrogen fixation of thegarden pea (Pisum sativum cv. Dipple Maj). Annales Botanici Fennici20:205-213.

Paivoke AE and LK Simola. 2002. Arsenate toxicity to Pisum sativum:Mineral nutrients, chlorophyll content and phytaseactivity.Ecotoxicology and Environmental safety.49:111-121.

Pal SC. 1996. Effect of heavy metals on Legume-Rhizobiumsymbiosis.Developments in Plant Soil Sciences.70:21-29

Panda SK, Singha NB and Khan MH.2003. Does aluminiumphytotoxicity induce oxidative stress in green gram(Vigna radiata)Bulgarian Journal of Plant Physiology. 29:77–86

Pandey N and Sharma CP. 2002.Effect of heavy metals Co2+, Ni2+, andCd2+ on growth and metabolism of cabbage. Plant Science 163:753–758.

Parr PD and Taylor JrFG. 1982.Germination and growth effects ofhexavalent chromium in Orocol TL (a corrosion inhibitor)on Phaseolus vulgaris. Environment International 7:197-202.

Patra M and Sharma A. 2000.Mercury toxicity in plants. BotanicalReview 66: 379–422.

Pätsikkä E, Kairavuo M, Šeršen F, Aro EM and Tyystjärvi E. 2002.Excess copper predisposes photosystem II to photoinhibition invivo by outcompeting iron and causing decrease in leafchlorophyll. Plant Physiology129: 1359-1367.

Peralta JR, Gardea-Torresdey JL, Tiemann KJ, Gomez E, Arteaga S andRascon E. 2001. Uptake and effects of five heavy metals on seedgermination and plant growth in alfalfa (Medicago sativa) L. Bulletinof Environmental Contamination and Toxicology66:727-734.

Peterson CA and Rauser WE. 1979. Callose deposition andphotoassimilate export in Phaseolus vulgaris exposed to excesscobalt, nickel and zinc. Plant Physiology 63:1170-1174.

Piechalak A, Tomaszewska B, Baralkiewicz D, Malecka A.2002.Accumulation and detoxification of lead ions in legumes.Phytochemistry 60: 153–162.

Radha J, Srivastava S, Solomon S, Shrivastava AK and Chandra A.2010.Impact of excess zinc on growth parameters, cell division,nutrient accumulation, photosynthetic pigments and oxidative stressof sugarcane (Saccharum spp.). Acta Physiologiae Plantarum 32:979-986.

Rahman H, Sabreen S, Alam S and Kawai S. 2005.Effects of nickel ongrowth and composition of metal micronutrients in barley plantsgrown in nutrient solution. Journal of Plant Nutrition 28: 393–404.

Rahoui S, Chaoui A and El Ferjani E. 2008. Differential sensitivity tocadmium in germinating seeds of three cultivars of faba bean (Viciafaba L.). Acta Physiologiae Plantarum 30: 451-456.


Rai V, Vajpayee P, Singh SN and Mehrotra S. 2004. Effect of chromiumaccumulation on photosynthetic pigments, oxidative stress defencesystem, nitrate reduction, proline level and eugenol content ofOcimum tenuiflorum L. Plant Science 167:1159-1169.

Rai VK. 2002. Role of amino acids in plant responses to stresses.Biologia Plantarum 45: 481–487.

Ralph PJ and Burchett MD. 1998. Photosynthetic responseof Halophila ovalis to heavy metal stress.EnvironmentalPollution 103: 91-101.

Rao Ramani IV. 1979. Measurement and characterization of someheavy metals Hg, Pb, Cd, and Cu in the aquatic environment of theKalu River. M.Sc. Thesis of the University of Bombay.India.

Rauser WE. 1995. Phytochelatins and related peptides: structure,biosynthesis, and function. Plant Physiology 109: 1141–1149.

Rauser WE. 1999. Structure and function of metal chelators producedby plants: the case for organic acids, amino acids, phytin andmetallothioneins. Cell Biochemistry and Biophysics 31: 19–48.

Reichman S. 2007. The potential use of the legume-rhizobium symbiosisfor the remediation of arsenic contaminated sites.Soil Biology andBiochemistry 39: 2587-2593.

Ritambhara T and Girjesh K. 2010. Genetic loss through heavy metalinduced chromosomal stickiness in Grass pea. Caryologia 63: 223-228.

Romero-Puertas MC, Corpas FJ, Rodriguez-Serrano M, Gomez M, delRío LA and Sandalio LM. 2007. Differential expression andregulation of antioxidative enzymes by Cd in pea plants. Journal ofPlant Physiology 164: 1346–1357.

Rother JA, Millbank JW, Thornton I .1983.Nitrogen fixation by whiteclover (Trifolium repens) in grasslands on soils contaminated withcadmium, lead and zinc. Journal of Soil Sciences 34: 127–136.

Sagner S, Kneer R, Wanner G, Cossin JP,Dues-Neumann B, Zenk MH.1998. Hyperaccumulation, complexation and distribution of nickelin Sebertia acuminata.Phytochemistry 47:339–347.

Salt DE, Prince RC, Pickering IJ and Raskin I. 1995.Mechanisms ofcadmium mobility and accumulation in Indian mustard. PlantPhysiology 109:1427-1433.

Samantaray S, Rout GR and Das P. 1997. Tolerance of rice to nickel innutrient solution. Biologia Plantarum 40:295–298.

Sandalio LM, Dalurzo HC, Gómez M, Romero-Puertas MC and del RíoLA. 2001. Cadmium-induced changes in the growth and oxidativemetabolism of pea plants. Journal of Experimental Botany 52:2115–2126.

Schickler H and Caspi H. 1999.Response of antioxidative enzymes tonickel and cadmium stress in hyperaccumulator plants of the genusAlyssum. Physiologia Plantarum 105:39–44.

Scoccianti V, Crinelli R, Tirillini B, Mancinelli V and Speranza A. 2006.Uptake and toxicity of Cr(III) in celery seedlings. Chemosphere64:1695-1703.

Sengar RS and Pandey M. 1996.Inhibition of chlorophyll biosynthesisby lead in greening Pisum sativum leaf segments. Plant Biology38:459–62.

Seregin IV and Ivanov VB. 2001.Physiological aspects of cadmium andlead toxic effects on higher plants. Russian Journal of PlantPhysiology 48:523-544.

Shafiq M, Iqbal MZ and Athar M. 2008.Effect of lead and cadmium ongermination and seedling growth of Leucaena leucocephala.Journalof Applied Science and Environmental Management 12:61- 66.

Shanker AK, Cervantes C, Loza-Tavera H and Avudainayagam S.2005.Chromium toxicity in plants. Environment International31:739–753.

Sharma P and Dubey RS. 2005. Lead toxicity in plants. Brazilian Journalof Plant Physiology 17:35–52.

Sharma SS and Dietz KJ. 2006. The significance of amino acids andamino acid-derived molecules in plant responses and adaptation toheavy metal stress. Journal of Experimental Botany 57:711–726.

Sharma SS, Schat H and Vooijs R. 1998.In vitro alleviation of heavymetal-induced enzyme inhibition by proline. Phytochemistry49:1531–1535.

Sheoran IS, HR Singal and R Singh. 1990. Effect of cadmium and nickelon photosynthesis and enzymes of the photosynthetic carbonreduction cycle in pigeon pea (Cajanus cajan L.). PhotosynthesisResearch 23:345–351.

Shi G, Liu C, Cai Q, Liu Q and Hou C. 2010. Cadmium Ac- cumulationand Tolerance of Two Safflower Cultivars in Relation toPhotosynthesis and Antioxidantive Enzymes.Bulletin ofEnvironmental and Contamination Toxicology 85: 256-263.

Shi GR and Cai QS. 2008. Photosynthetic and anatomic responses ofpeanut leaves to cadmium stress. Photosynthetica 46:627-630.

Siddiqui S, Meghvansi M, Wani M and Jabee F. 2009. Evaluating cadmiumtoxicity in the root meristem of Pisum sativum L. Acta PhysiologiaePlantarum 31:531–536.

Singh N, Ma LQ, Srivastava M and Rathimasabapathi B. 2006. Metabolicadaptations to arsenic induced oxidative stress in Pteris vittata Land Pteris ensiformis L.Plant Science 170: 274-282.

Singh S and Sinha S. 2005.Accumulation of metals and its effects inBrassica juncea (L.)Czern. (cv. Rohini) grown on variousamendments of tannery waste. Ecotoxicology and EnvironmentalSafety 62: 118-127.

Siripornadulsil S, Traina S, Pal D, Verma S and Sayre RT. 2002. MolecularMechanisms of Proline-Mediated Tolerance to Toxic Heavy Metalsin Transgenic Microalgae. Plant Cell 14: 2837-2847.

Smimoff N .2000.The role of active oxygen in the response of plantsto water deficit and desiccation. New Phytologist. 1125: 27-58.

Smiri M, Chaoui A and El Ferjani E. 2009. Respiratory metabolism inthe embryonic axis of germinating pea seed exposed to cadmium.Journal of Plant Physiology 166: 259-269.

Sresty T, Rao VS and Madhava KV. 1999. Ultrastructural alterations inresponse to zinc and nickel stress in the root cells of pigeonpea.Environmental and Experimental Botany 41: 3-13.

Srivastava AK, Bhargava P and Rai LC. 2005. Salinity and copper-induced oxidative damage and changes in antioxidative defensesystem of Anabaena doliolum. World Journal of Microbiology andBiotechnolology 22:1291-1298.

Stan V, Gament E, Corena CP, Voaides C, Dusa M and Plopeanu G.2011. Effects of heavy metal from polluted soils on the Rhizobiumdiversity.Notulae Botanicae Horti Agrobotanici Cluj-Napoca 39:88–95.

Sterritt RM and Lester JN. 1980. Interactions of heavy metals withbacteria. Science of the Total Environment 14:5–17.

Stoyanova D and Chakalova E. 1990.The effect of cadmium on thestructure of photosynthetic apparatus in Elodea canadensis Rich.Plant Physiology 16:18-26 (In Bulg.).

Szalontai B, Horváth LI, Debreczeny M, Droppa M and Horváth G.1999. Molecular rearrangements of thylakoids after heavy metalpoisoning, as seen by Fourier transform infrared (FTIR) and electron


spin resonance (ESR) spectroscopy. Photosynthesis Research61: 241-252.

Tadolini B, Cabrini L, Landi L, Varani E and Pasquali P.1984. Biochemicaland Biophysical Research Communications 122: 550-555.

Talanova VV, Titou AF and Boeva NP. 2000. Effect of increasingconcentrations of lead and cadmium on cucumber seedlings. BiologiaPlantarum 43: 441-444.

Turnau K.1998. Heavy metal uptake and arbuscular mycorrhyizadevelopment of Euphorbia cyparissias on zinc wastes in SouthPoland.Acta Societatis Botanicorum Poloniae 67: 105-113.

Tausz M, Sircelj H and Grill D. 2004. The glutathione system as a stressmarker in plant ecophysiology: is a stress response concept valid?Journal of Experimental Botany 55: 1955—1962.

Thomas F, Malick C, Endreszl EC and Davies KS. 1998. Distinctresponses to copper stress in the halophyte, Mesembryan-themumcrystallium. Physiologia Plantarum 102: 360–368.

Tiburcio AF, Ailabella T, Borrell A and Masgrau C. 1997. Polyaminemetabolism and its regulation.Physiologia Plantarum 100: 664-674.

Tu C and LQ Ma.2005. Effects of arsenic on concentration anddistribution of nutrients in the fronds of arsenic hyperaccumulatorPteris vittata L .Environmental Pollution. 135: 333-340.

Tuna AL , B Bürün,Yokaû and E Çoban. 2002. The effect of heavymetals on pollen germination and pollen tube length in tobaccoplant. Turkish Journal of Biology 26: 109-113

Tyler G, Pahlsson AM, Bengtsson G, Baath E, Tranvik L. 1989. Heavymetal ecology and terrestrial plants, microorganisms andinvertebrates: a review. Water, Air Soil Pollution 47: 189-215.

Upadhyaya H, Panda SK, Bhattacharjee MK and Dutta S. 2010. Roleof Arbuscular Mycorrhiza in heavy metal tolerance inplants:Prospects for phtoremediation. Journal of Phytology.2: 16–2 7

Vajpayee P, Tripati RD, Rai UN, Ali MB and Singh SN. 2000. Chromiumaccumulation reduces chlorophyll biosynthesis, nitrate reductaseactivity and protein content of Nymphaea alba . Chemosphere41:1075-1082.

Van Assche, and Clijters H.1990. Effect of metals on enzyme activityin plants. Plant Cell Environment 13: 195–206.

Varga A, Martinez RMG, Zaray G and Fodor F.1999. Investigation ofeffects of cadmium, lead, nickel and vanadium contamination onuptake and transport process in cucumber plants by TXRFspectrometry,Spectrochim. Acta Biologica. 54:1455-1466.

Vazquez M, Poschenrieder CH and Barcelo J. 1989. Pulvinus structureand leaf abscission in cadmium-treated bean plants (Phaseolusvulgaris). Canadian Journal of Botany 67: 2756–2764.

Vazquez MD, Poschenrieder CH and Barceio J. 1987. Chromium VIinduced structural and ultrastructural changes in bush bean plants(Phaseolus vulgaris L.). Annuals of Botany 59: 427-438.

Vershey SRK and Varshey CK.1981.Effect of SO2 on Pollen germinationand pollen tube growth .Environmental Pollution. 24: 87-92

Vigue GT, Pepper IL, Bezdicek DF .1981. The Effect of Cadmium onNodulation and Nitrogen Acetylene Fixation by Dry BeansPhaseolus vulgaris. Journal of Environmental Quality 10: 87-90.

Wagner GJ.1993.Accumulation of cadmium in crop plants and itsconsequences to human health.Advances in Agronomy 51: 173-212.

Wani PA, Khan MS and Zaidi A. 2007.Impact of heavy metal toxicityon plant growth, symbiosis, seed yield and nitrogen and metal uptakein chickpea. Australian Journal of Experimental Agriculture 47:712–720.

Warne MS, Heemsbergen D, Stevens D, McLaughlin M, Cozens G,

Whatmuff M, Broos K, Barry G, Bell M, Nash D, Pritchard D andPenney N. 2008. Modeling the toxicity of copper and zinc salts towheat in 14 soils. Environmental Toxicology and Chemistry27:786–792.

Weinstein LH, Kaur-Sawhney R, Rajam MV, Wettlaufer SH, GalstonAW. 1986. Cadmium-induced accumulation of putrescine in oatand bean leaves. Plant Physiology 82: 641–645

Weissenhorn I, Leyval C and Berthelin J.1993. Cd-tolerant arbuscularmycorrhizal (AM) fungi from heavy-metal polluted soils. PlantSoil 157: 247–256.

Wu G, Wei ZK and Shao HB. 2007. The mutual responses of higherplants to environment: physiological and microbiological aspects.Biointerface. 59: 113-119.

Xiong ZT and YH Peng. 2001. The effects of pollen germination andtube with special reference to low concentration exposure.Ecotoxicology and Environmental Safety. 48: 51-55.

Xu J, Chai T, Zhang Y, Lang M and Han L. 2009. The cation-effluxtransporter BjCET2 mediates zinc and cadmium accumulationin Brassica juncea L.leaves. Plant Cell Reports 28:1235–1242.

Yadav SS, Shukla R and Sharma YK.2009.Nickel toxicity on seedgermination and growth in radish (Raphanus sativus) and itsrecovery using copper and boron. Journal of Environmental Botany30: 461-6.

Yakovleva ZM. 1984. The effect of metal oxides on symbiosis betweenRhizobium trifolii and clover plants. Microbiologiya 53:308-312.

Yang D.1991.Effects of heavy metal ions on the structure and functionof photosynthetic membranes of high plants. Chinese Bulletin ofBotany 8:26-29 (In Chinese with English abstract)

Yau, P.Y., Loh, C.F. and Azmil, I.A.R. 1991. Copper toxicity of clove(Syzygium aromaticum (L.)Merr.and Perry) seedlings. MARDIResearch Journal 19:49-53.

Younis M. 2007. Responses of Lablab purpureus-Rhizobium symbiosisto heavy metals in pot and field experiments.World Journal ofAgricultural Sciences 3: 111–122.

Zengin FK and Munzuroglu O. 2005. Effects of some heavy metals oncontent of chlorophyll, proline and some antioxidant chemicals inbean (Phaseolus Vulgaris l.) Seedlings.Acta Biologica CracoviensiaSeries Botanica 2:157–164.

Zenk MH.1996.Heavy metal detoxification in higher plants: a review.Gene 179: 21–30.

Zhang SS, Zhang HM, Qin R, Jiang WS and Liu DH. 2009. Cadmiuminduction of lipid peroxidation and effects on root tip cells andantioxidant enzyme activities in Vicia faba L. Ecotoxicology18:814–823.

Zhang WH and Tyerman SD. 1999. Inhibition of water channels byHgCl2 in intact wheat root cells. Plant Physiology 120:849–858.

Zhang H, S Zhang, Q meng, J Zou, W Jiang and D Liu. 2009. Effects ofAlumiunium on Nucleoli in root tip cells,root growth and theantioxidant defense system in Vicia faba L.Acta BiologicaCracoviensia Series Botanica 51: 99–106.

Zhao Sheng Zhou, Kai Guo, Abdelrahman Abdou Elbaz and Zhi MinYang. 2006. Salicylic acid alleviates mercury toxicity by preventingoxidative stress in roots of Medicago sativa. Environmental andExperimental Botany 65:27–34.

Zhou ZS, Huang SQ, Guo K, Mehta SK, Zhang PC and Yang ZM. 2007.Metabolic adaptations to mercury-induced oxidative stress in rootsof Medicago sativa L. Journal of Inorganic Biochemistry 101: 1–9.

Zornoza P, Robles S and Martin N. 1999.Alleviation of nickel toxicityby ammonium supply to sunflower plants. Plant and Soil 208: 221–226.


Assessment of genetic diversity at molecular level in mungbean (Vigna radiata (L.)Wilczek)S. K. GUPTA, R. BANSAL, U. J. VAIDYA and T. GOPALAKRISHNA

Nuclear Agriculture and Biotechnology Division, Bhabha Atomic Research Centre Trombay, Mumbai-400 085, India;E-mail: [email protected](Received : August 20, 2013 ; Accepted : October 19, 2013)

ABSTRACT

Mungbean (Vigna radiata (L.) Wilczek) also known as greengram is an important food legume crop and provides aninexpensive source of dietary protein. In this study, geneticdiversity in 29 elite mungbean genotypes was assessed usingmungbean SSR markers. Total 30 SSR markers (15 genomicSSR and 15 EST-SSR) were used in the study and 19 SSRmarkers (10 EST-SSR and 9 genomic SSR) were foundpolymorphic among the mungbean genotypes. Each polymorphicSSR markers yielded 2 to 3 alleles and total 44 alleles weregenerated with an average of 2.3 alleles/locus. Polymorphicinformation content of the SSR markers ranged from 0.07 to0.61 with an average of 0.27. SSR markers showed highdiscrimination power and a combination of only six SSRmarkers was sufficient to distinguish 27 genotypes out of 29mungbean genotypes. Cluster analysis grouped the 29mungbean genotypes into three main clusters and genotypeswere mostly grouped based on their pedigree. Result of PrincipalCoordinate Analysis (PCO) was comparable with the clusteranalysis. This study report that cultivated mungbean has anarrow genetic base and emphasizes the need to explore andexploit additional source of genetic variation in mungbeanbreeding programs.

Key words: EST-SSR, Genetic diversity, genomic SSR, mungbean,Vigna radiata

Mungbean (Vigna radiata (L.) Wilczek) also known asgreen gram is an important food legume and provides animportant and inexpensive source of dietary protein to thepeople of Asia. It is a self-pollinated diploid crop (2n = 22)with a genome size of about 560 Mb (Arumuganathan andEarle, 1991). Mungbean belongs to the genus Vigna in thetribe Phaseoleae, which include other important grain legumeslike cowpea (V. unguiculata), blackgram (V. mungo) and azukibean (V. angularis). The productivity of mungbean has notincreased significantly since last decade. The main reason forthis has been attributed to lack of genetic variability, poorharvest index and susceptibility to biotic and abiotic stresses(Poehlman, 1991). Despite its economic importance, littleattention has been paid to improvement of mungbeancompared to other grain legumes such as pigeonpea, chickpeaand soybean. There is urgent need to improve the breedingstrategies in mungbean to sustain and improve theproductivity.

The assessment of genetic diversity is a prerequisiteand important step for the improvement of any crop plant.The estimation of genetic diversity is invaluable in selectionof diverse parental combinations to generate segregatingprogenies with maximum genetic variability and introgressingdesirable traits from diverse or wild germplasm into thecultivars to broaden the genetic base (Barrett and Kidwell1998, Thompson et al. 1998). Earlier, genetic diversity studieswere mostly carried out based on morphological charactersand isozyme markers. But, limited availability, lowpolymorphism and high influence of environmental factorson the expression limited the use of morphological andbiochemical markers. Molecular markers provide an alternativeand important tool for genetic analysis as they are numerous,selectively neutral and allow screening at any growth stage(Soller and Beckmann 1983).

Assessment of the genetic variation in mungbean hasbeen carried out using different types of molecular markersincluding RAPD (Santalla et al. 1998, Lakhanpaul et al. 2000),AFLP (Bhat et al. 2005), ISSR (Reddy et al. 2008) and SSR(Gwag et al. 2010). RAPD and AFLP markers have theadvantage that both are random markers and did not requireany prior sequence information for their implementation.However, RAPD is less reproducible and AFLP is laborintensive and time consuming technique, making them lessuseful for genetic studies. Another genotyping techniquecalled microsatellite or SSR markers, which detect sequencevariation in the tandem repeats of 2 to 6 base pairs, are apowerful tool for genetic analysis (Tautz and Renz 1984). SSRsare the marker of choice for genetic studies because of theirhypervariability, codominant nature, locus specificity and highreproducibility. SSR markers has been used for geneticdiversity studies in many legumes including soybean (Brown-Guedira et al. 2000), chickpea (Shukla et al. 2011), pigeonpea(Dutta et al. 2011), cowpea (Asare et al. 2010; Gupta andGopalakrishna 2010), common bean (Burle et al. 2010) andblackgram (Gupta and Gopalakrishna 2009).

The current study was conducted with the aim ofassessing the genetic diversity in elite mungbean genotypesunder cultivation or being used in Indian breeding programsusing SSR markers.


MATERIALS AND METHODS

Plant material and DNA extraction: A total of 29mungbean genotypes used for studying the genetic diversityare given in Table 1. Total genomic DNA was extracted fromone week old seedling using the modified CTAB Method.The quality of DNA was checked on 1% agarose gel and thequantity was determined using UV spectrophotometer.

SSR marker analysis: Total 30 mungbean SSR markers,which include 15 genomic SSR markers (Tangphatsornruanget al. 2009; Table 2) and 15 EST-SSR markers (Gupta et al.2012; Table 3) were used to evaluate the genetic variationamong 29 mungbean genotypes. PCR reactions were performedin 25 µl volume containing 10 mM Tris-HCl (pH 9.0), 50 mMKCl, 1.5 mM MgCl2, 0.2 mM of each dNTP, 0.5 unit Taq DNApolymerase (Jonaki, Hyderabad, India), 50 ng template DNA,and 20 ng each of forward and reverse primers. PCRamplifications were performed in an Eppendorf Mastercycler(Eppendorf, Hamburg, Germany) using the following thermal

profile:1 cycle of 950C for 2 min, followed by 34 cycles of 940Cfor 30 sec, 55-600C for 30 sec, 720C for 30 sec and a finalextension of 720C for 7 min. The PCR products were mixedwith an equal amount of loading buffer (98% formamide, 10mM EDTA, 0.1% bromophenol blue, 0.1% xylene cyanol), anddenatured for 3 min at 950C. About 5 µl of each reaction mixturewas loaded on a 6% denaturing polyacrylamide gel containing7 M urea in 1X Tris-borate-EDTA (TBE) buffer. Electrophoresiswas performed at a constant power of 50 W for about 2 h in aSequi-Gen GT Sequencing system (Bio-Rad, USA). Gels werestained using the silver staining protocol as described byGupta and Gopalakrishna (2010).

Statistical analysis: Allelic variation was calculated fromthe frequencies of genotypes at each locus as the polymorphicinformation content (PIC). PIC of each SSR marker wascalculated by applying the formula of Anderson et al. (1993):

PIC = 1 – (Pij)2, where Pij is the frequency of the jh allele for

ith locus. The gene diversity and observed heterozygosity forthe SSR markers was calculated using Power Marker v3.25

Table 1. Details of mungbean genotypes used in the study

S. No. Genotypes Pedigree Origin* Year of release 1 Pusa Baisakhi Selection from T 44 IARI, New Delhi 1971 2 S-9 BR-2 X type-21 IARI, New Delhi 1984 3 Pusa Ratna - IARI, New Delhi 2005 4 TM96-2 Kopergaon X TARM-2 BARC, Mumbai 2007 5 Pusa Vishal Selection from NM-92 IARI, New Delhi 2000 6 PS-16 Selection from Iran germplasm P596 - 1978 7 Pusa-105 Selection from exotic line M 178 IARI, New Delhi 1983 8 COGG-912 MGG 336 X COGG 902 TNAU, Coimbatore 2005 9 Pusa 9072 Pusa-106 X 10-215 IARI, New Delhi 1995 10 PDM-139 ML20/19 X ML 5 IIPR, Kanpur 1990 11 Pusa-9531 Selection from NM 9473 IARI, New Delhi 2000 12 AKM-1009 - PKV, Akola - 13 BPMR-145 JL-781 X Mungi MKV, Parbhani 2001 14 AKM-8802 MH-1 X PIMS-4 PKV, Akola 1997 15 Vaibhav KDM-1 X TARM-18 - 2001 16 AKM-9904 BM-4 X PS-7 PKV, Akola 2009 17 TAP-7 Mutant of S-8 BARC, Mumbai 1982 18 AKM-9911 BM-86 X MH PKV, Akola 2007 19 TARM-1 RUM-5 X TPM-1 BARC, Mumbai 1996 20 TMB-37 Kopergaon X TARM-2 BARC, Mumbai 2005 21 TARM-2 RUM-5 X TPM-1 BARC, Mumbai 1994 22 Mulmarada Local selection from Maharashtra Maharashtra - 23 Kopergaon Selection from bulk local germplasm Maharashtra 1976 24 TARM-18 PDM-54 X TARM-2 BARC, Mumbai 1996 25 EC-634637 Collection from AVRDC Australia - 26 EC-634638 Collection from AVRDC India - 27 AKM10-1 - PKV, Akola - 28 AKM10-7 - PKV, Akola - 29 V. radiata var. sublobata Wild relative of mungbean India -

*IARI: Indian Agricultural Research Institute; BARC: Bhabha Atomic Research Centre; TNAU: Tamil Nadu Agriculture University; IIPR: IndianInstitute of Pulses Research; PKV: Dr. Panjabrao Deshmukh Krishi Vidyapeeth; MKV: Marathwada Krishi Vidyapeeth

Gupta et al., : Assessment of genetic diversity at molecular level in mungbean (Vigna radiata (L.) Wilczek) 2 1

software (Liu and Muse 2005). Cluster analysis was performedusing the software NTSYSpc version 2.0 (Rohlf 1998). Datawere entered in a binary data matrix as discrete variables andpair-wise similarities were obtained using the Dice’s similaritycoefficients. The matrices of similarity coefficients weresubjected to unweighted pair group method with arithmeticaverage (UPGMA) to estimate the genetic relatedness amongthe genotypes and generate the dendrogram. Finally, Principalcoordinate analysis (PCO) was carried out to highlight theresolving power of the ordination using NTSYSpc program.

RESULTS AND DISCUSSION

All 30 SSR markers were successfully amplified acrossmungbean genotypes and 19 (63%) SSR markers were foundpolymorphism. Number of alleles ranged from two to threeand 19 polymorphic SSR markers generated 44 alleles with anaverage of 2.3 alleles/locus. PIC of the genomic SSR markersranged from 0.07 to 0.42 with an average of 0.21 (Table 2) andfor EST-SSR markers varied from 0.07 to 0.61 with an average

of 0.32 (Table 3). The gene diversity for genomic SSR markersranged from 0.07 to 0.43 and observed hetrozygosity rangedfrom 0 to 0.07. Similarly, gene diversity for the EST-SSR markersranged from 0.03 to 0.63 and observed hetrozygosity rangedfrom 0 to 0.17. The UPGMA analysis based on 19 polymorphicSSR markers grouped the 29 mungbean genotypes into threemain clusters with Dice’s similarity coefficient ranging from0.31 to 1.0 (Fig. 1). The cluster I consisted of three genotypes(Pusa Baisakhi, TM96-2, and Vaibhav). Cluster II had 16genotypes (S-9, Pusa Vishal, AKM 10-1, Pusa Ratna, Pusa-9531, Pusa-105, Pusa-9072, TAP-7, AKM-1009, AKM-9911,TARM-1, TARM-2, PDM-139, AKM 10-7, TMB-37 andTARM-18) and Cluster III comprised of nine genotypes(Mulmarada, PS-16, BPMR-145, AKM-8802, Kopergaon, EC-634638, COGG-912, AKM-9904 and EC-634637). Wildmungbean V. radaita var. sublobata was clearlydistinguishable from the cultivated genotypes and formedthe separate group.

Principal coordinate analysis (PCO) based on genetic

Table 2. Details of genomic SSR markers used for genetic diversity study in mungbean

Marker name Primer sequence (5’….3’) Repeat motif Na* He* H0* PIC

VR029 F:GAAAGAAGCCAAACAAAACAGG R:TGGCAGAGAAGGTAAATAAGGG

(TAG)12 2 0.07 0.00 0.07

VR084 F: GAGCCACTTTGCCATATTTCT R:ATTCTCCATTGTTCTCGTTCTC

(GA)17 2 0.27 0.03 0.24

VR099 F:ATACTTCGATCCGACCACTAGG R:CAAAGACAGGAGGAGAACAAGG

(TA)14 2 0.24 0.00 0.24

VR102 F: CATGTGAGCTACCCTTTCAACA R: CAAGGACTGCTATATCCAAGGC

(AC)10 3 0.39 0.07 0.34

VR111 F: TGCATCTTTATTGAGTTCCGTG R: GTTTTGGGGTGAATGTTGGATA

(TCTT)7 1 - - -

VR135 F: GCCCAGATTTGTTCATCCTAGA R: ACTGTTTTGAGTGGGGAAAAGA

(TCA)7 1 - - -

VR140 F: GGTGTTGTTGTTGAGGAATGAA R: AACATTGAGGACCCACATATCC

(TA)10 3 0.43 0.03 0.42

VR147 F: CCATGTGTGTGAATGTGAGTGA R: CCTTTGATTTTGTGGGATGTGT

(TG)10 1 - - -

VR212 F: AAACCAAAACGTAAGATCAGGG R: ATAGAAAGAAGTTGGCGCAGAA

(TAA)7 1 - - -

VR216 F: TTCCCTGTGTCCTTATATGTCC R: GAGGATAGTGAATTTTGAAGGC

(CA)10 1 - - -

VR326 F: GATGGCTCTGCATTGAAACC R: GATCTTCCCAACTTTCCCTCTC

(AGAGA)4 2 0.21 0.03 0.18

VR357 F: GCCCGATGTCCTAGCTTTTAG R: CCTCAAAACAATCAGAACTCTCG

(ATTT)5 2 0.07 0.00 0.07

VR375 F: TCTCAGCATCTGTGGTGGTAGT R: AGAATCCAACAACTCCTGCTTC

(GTT)8 2 0.18 0.00 0.18

VR390 F:AGAATACAGAGAACCTGATACTTGGTC R: AATGGCTATGCAAATGGTAGGT

(GCA)7 1 - - -

VR400 F: ATCATAGATAGGGGACCAACCC R: ATCTTAGGGAGTCTTCGAGGGA

(CAT)8 3 0.13 0.00 0.13

Average 1.8 0.22 0.02 0.21

*Na: number of alleles; He: expected heterozygosity; H0: Observed heterozygosity


similarity metrics was also used to depict the geneticrelationship among mungbean genotypes. The first two eigenvectors accounted for 41.8 % of the total molecular variation,with each component individually contributing 30.7 % and11.1 %, respectively. In PCO analysis also most of thegenotypes were grouped in a single large cluster and wildmungbean genotype V. radiata var. sublobata was placed asan outgroup (Fig. 2).

In this study, SSR markers detected a low level of geneticdiversity in mungbean. Each polymorphic SSR marker detectedtwo to three alleles with an average of 2.3 alleles/locus and nocorrelation between the level of polymorphism and SSR repeatnumber was observed. The polymorphism level observed inthe study were comparable to those reported earlier formungbean (Gwag et al. 2006, Somta et al. 2008) and chickpea(Choudhary et al. 2006), but was less compared to otherlegumes including blackgram (Gupta and Gopalakrishna 2009),cowpea (Li et al. 2001, Gupta and Gopalakrishna 2010), azukibean (Wang et al. 2004) and pigeonpea (Odeny et al. 2007). Inthis study, EST-SSR markers were found to have higher PICvalue (average PIC score 0.32, Table 3) compared to genomic

SSR markers (average PIC score 0.21, Table 2). Highpolymorphism of EST-SSR markers also has been observed inother studies (Dutta et al. 2011). Since, EST-SSR polymorphismrepresent the functional variation, highly polymorphic EST-SSR markers identified in this study would be a valuableresource for mungbean genetic analysis. The gene diversity,often referred to as expected heterozygosity, for thepolymorphic SSR markers ranged from 0.03 to 0.63, indicatingthe presence of low genetic diversity in the Indian mungbean.The presence of very low observed hetrozygosity (average0.02) in mungbean is expected because mungbean is a selfpollinated crop. In this study, SSR markers showed highdiscriminating power and only six SSR markers (VrEST9,VrEST19, VrEST14, VrEST15, VR102 and VR140) were sufficientto differentiate all 29 mungbean genotypes except TARM-1and TARM-2. SSR markers have been shown to be useful indiscrimination of genotypes in many other species includinglegumes (Gupta and Gopalakrishna 2009, 2010) and cereals(Russell et al. 1997, Eujayl et al. 2001).

Cluster analysis based on SSR data distributed the 29mungbean genotypes into three main clusters and most of

Table 3. Details of EST-SSR markers used for genetic diversity study in mungbean

Marker name Primer sequence (5’….3’) Repeat motif Na* He* H0* PIC VrSSR01 F:ACCTCTCTTCTCGACCCCAC

R:GGGTTGCATGGTAAGACTGC (TC)6 2 0.24 0.00 0.24

VrSSR04 F: CTGATTCAGCCTCAGGTTCC R: CACCGCTAAGATGCTCACAA

(CT)5 1 - - -

VrSSR05

F: GGGCCAGTGACAAATGAGAG R: TCTCGTTTGTGGTGGTTGAG

(AGA)6 2 0.13 0.00 0.07

VrSSR08

F: CGGTTCGTCCGTCTTACAAT R: TGGTTCTCGTCTTTCCAAGG

(TTA)6 1 - - -

VrSSR09

F:TCCATTTTAGCCAATGAGGC R:GTGTGAATGAGCAGAAGCCA

(GAT)5 3 0.50 0.00 0.53

VrSSR10

F: TTTTTCTTCCTGACCGATGG R: TCCATGGGCTATATGTGCAA

(AT)6 1 - - -

VrSSR12

F:TCCCTCTCCCACCTTCTTCT R:GATGCAGATTGTTGCCTTGA

(AT)6-(AG)8 2 0.18 0.00 0.18

VrSSR14

F:AGCGTCGTAGGGAGAAAATG R:GCTAGAGGGATGCTTCACCA

(GT)7 3 0.47 0.00 0.47

VrSSR15 F:CATGACCGAGAAGACAAGCA R:CCACAACAAATCCAAGAGCA

(AT)8 3 0.63 0.03 0.61

VrSSR16

F: TCTCCATCCCCATCTTCATC R: GGAGAGATCTGCGACCTTTG

(TGTA)4 1 - - -

VrSSR17

F:AACTTCGTCCTGCGCTTAAA R:AGCATGACCACACCAATCAA

(TGTT)5 2 0.03 0.03 0.07

VrSSR19

F:AAATGTTCGTGGAATCCTGC R:TTTCTTGTCCCTGAGTTCCAA

(TA)5 2 0.48 0.17 0.41

VrSSR27

F:AGGGAGCAGAATAAGAGG R:GTGAGAACTGAGAAGATTGG

(GAA)5 2 0.28 0.00 0.24

VrSSR28

F:CCAATTTACAAAGCCTAAAC R:CATTTTTGGTTACAGATTCA

(TC)5 2 0.30 0.00 0.39

VrSSR30

F: TCTACCTGGTTCCAGTCTTT R: GCCAATAGCAAATACAGACA

(GA)5 1 - - -

Average 1.9 0.32 0.02 0.32 *Na: number of alleles; He: expected heterozygosity; H0: Observed heterozygosity

Gupta et al., : Assessment of genetic diversity at molecular level in mungbean (Vigna radiata (L.) Wilczek) 2 3

the genotypes were grouped based on their pedigree. Forexample, cultivars TARM-1 and TARM-2 which are selectionsfrom the same cross were placed together and Australiangenotype EC-634638 showed least similarity with Indiangenotypes. Similarly, V. radiata var. sublobata, a wild relativeof mungbean, showed least similarity with cultivatedgenotypes and was placed as a separate group. The results ofthe PCO analysis congruent well with the cluster analysis andmost of the genotypes were grouped in a single large cluster(Fig. 2). In the study, clustering of large number of genotypesin a single group indicated the narrow genetic base of cultivatedmungbean in India. Similar observations have been madeearlier using RAPD (Lakhanpaul et al. 2000) and AFLP (Bhatet al. 2005) markers. Most of the present day mungbeancultivars have been developed by repeated use of fewcultivars/lines known to have wider adaptability or otheragronomically important traits leading to low level of genetic

diversity in the cultivated gene pool. Narrow genetic baseincreases vulnerability to pathogens/pest epidemic andreduces genetic gain from selection. Therefore, additionalsource of genetic variation should be introduced intomungbean breeding programs. Wild species are well knownsource of novel alleles which can be utilized in plant breedingto improve the yield and other agronomically importantcharacters (Tanksley and McCouch 1997). Wild mungbean, V.radaiat var. sublobata, carries many useful agronomicallyimportant traits including resistance to most destructivestorage pests called bruchid beetles (Callosobruchuschinensis and C. maculatus). Therefore, this sub-speciesshould be exploited in breeding programs to broaden thegenetic base and further increase the genetic variability inmungbean breeding lines and cultivars.

This study showed that genic and genomic SSR markerswere effective in detecting the genetic variation in mungbean

Figure 1. Dendrogram showing genetic similarity among mungbean genotypes based on SSR data usingDice's similarity coefficients and UPGMA clustering analysis

Figure 2. Two-dimensional Principal Coordinate Analysis (PCO) of 29 mungbean genotypes based on SSR data.The number plotted represents individual genotypes and correspond to the one listed in Table 1.


and could be used for genetic analysis in mungbean. Theresult showed the presence of narrow genetic diversity in theIndian mungbean genotypes and would help the mungbeanbreeders in the selection of suitable parents for breedingpurposes and genetic mapping studies.

ACKNOWLEDGEMENTS

Authors thank Dr. K. S. Reddy, NA&BTD, BARC,Mumbai and Dr. S. E. Pawar, Consultant, MDFVPL, DharaDivision, New Delhi for providing the mungbean seed material.

REFERENCES

Anderson JA, Churchill GA, Autrique JE, Tanksley SD and Sorrells ME.1993. Optimizing parental selection for genetic linkage maps.Genome 36: 181-186.

Arumuganathan K and Earle ED. 1991. Nuclear DNA content of someimportant plant species. Plant Molecular Biology Report 9: 208-218.

Asare AT, Gowda BS, Galyuon IKA, Aboagye LL, Takrama JF andTimko MP. 2010. Assessment of the genetic diversity in cowpea(Vigna unguiculata L. Walp.) germplasm from Ghana using simplesequence repeat markers. Plant Genetic Resources 8: 142-150.

Barrett BA and Kidwell KK. 1998. AFLP-based genetic diversityassessment among wheat cultivars from the Pacific Northwest.Crop Science 38: 1261-1271.

Bhat KV, Lakhanpaul S and Chadha S. 2005. Amplified FragmentLength Polymorphism (AFLP) analysis of genetic diversity inIndian mungbean [Vigna radiata ( L.) Wilczek] cultivars. IndianJournal of Biotechnology 4: 55-64.

Brown-Guedira GL, Thompson JA, Nelson RL and Warburton ML.2000. Evaluation of genetic diversity of soybean introductions andNorth American ancestors using RAPD and SSR markers. CropScience 40: 815-823.

Burle ML, Fonseca JR, Kami JA and Gepts P. 2010. Microsatellitediversity and genetic structure among common bean (Phaseolusvulgaris L.) landraces in Brazil, a secondary center of diversity.Theoretical and Applied Genetics 121: 801-813.

Choudhary S, Sethy NK, Shokeen B and Bhatia S. 2006. Developmentof sequence-tagged microsatellite site markers for chickpea (Cicerarietinum L.). Molecular Ecology Notes 6: 93-95.

Dutta S, Kumawat G, Singh BP, Gupta DK, Singh S, Dogra V, Gaikwad K,Sharma TR, Raje RS, Bandhopadhya TK, Datta S, Singh MN,Bashasab F, Kulwal P, Wanjari KB, Varshney RK, Cook DR andSingh NK. 2011. Development of genic-SSR markers by deeptranscriptome sequencing in pigeonpea [Cajanus cajan (L.)Millspaugh]. BMC Plant Biology 11: 17.

Eujayl I, Sorrells M, Baum M, Wolters P and Powell W. 2001. Assessmentof genotypic variation among cultivated durum wheat based onEST-SSRs and genomic SSRs. Euphytica 119: 39-43.

Gupta SK and Gopalakrishna T. 2009. Genetic diversity analysis inblackgram [Vigna mungo (L.) Hepper] using AFLP and transferablemicrosatellite markers from azuki bean [Vigna angularis (Willd.)Ohwi & Ohashi]. Genome 52: 120-128.

Gupta SK and Gopalakrishna T. 2010. Development of unigene-derivedSSR markers in cowpea (Vigna unguiculata) and their transferabilityto other Vigna species. Genome 53: 508-523.

Gupta SK, Bansal R, Vaidya UJ and Gopalakrishna T. 2012.Development of EST-derived microsatellite markers in mungbean[Vigna radiata (L.) Wilczek] and their transferability to otherVigna species. Indian Journal of Genetics and Plant Breeding 72:468-471.

Gwag JG, Chung JW, Chung HK, Lee JH, Ma KH, Dixit A, Park YJ, ChoEG, Kim TS and Lee SH. 2006. Characterization of newmicrosatellite markers in mung bean, Vigna radiata (L.). MolecularEcology Notes 6: 1132-1134.

Gwag JG, Dixit A, Park YJ, Ma KH, Kwon SJ, Cho GT, Lee GA, Lee SY,Kang HK and Lee SH. 2010. Assessment of genetic diversity andpopulation structure in mungbean. Genes & Genomics 32: 299-308.

Lakhanpaul S, Chadha S and Bhat KV. 2000. Random amplifiedpolymorphic DNA (RAPD) analysis in Indian mung bean (Vignaradiata (L.) Wilczek) cultivars. Genetica 109: 227-234.

Li C-D, Fatokun CA, Ubi B, Singh BB and Scoles GJ. 2001. Determininggenetic similarities and relationships among cowpea breeding linesand cultivars by microsatellite markers. Crop Science 41: 189-197.

Liu K and Muse SV (2005) PowerMarker:an integrated analysisenvironment for genetic marker analysis. Bioinformatics 21: 2128-2129.

Odeny DA, Jayashree B, Ferguson M, Hoisington D, Crouch J andGebhardt C. 2007. Development, characterization and utilizationof microsatellite markers in pigeonpea. Plant Breeding 126: 130-136.

Poehlman JM. 1991. The Mungbean. Oxford and IBH Publication,New Delhi.

Reddy KS, Souframanien J, Reddy KS and Dhanasekar P. 2008. Geneticdiversity in mungbean as revealed by SSR and ISSR markers. Journalof food Legumes 21: 15-21.

Rohlf FJ. 1998. NTSYS-Pc:Numerical taxonomy and multivariateanalysis system, version 2.0. Exeter publications, Setauket, NewYork.

Russell J, Fuller J, Young G, Thomas B, Taramino G, Macaulay M,Waugh R, and Powell W. 1997. Discriminating between barleygenotypes using microsatellite markers. Genome 40: 442-450.

Santalla M, Power JB and Davey MR. 1998. Genetic diversity in mungbean germplasm revealed by RAPD markers. Plant Breeding 117:473-478.

Shukla N, Babbari A, Prakash V, Tripathi N, and Saini N. 2011. Moleculardiversity analysis in some promising lines of chickpea using SSRmarkers. Journal of Food Legumes 24: 320-323.

Soller M and Beckmann JS. 1983. Genetic polymorphism in varietalidentification and genetic improvement. Theoretical and AppliedGenetics 67: 25–33.

Somta P, Musch W, Kongsamai B, Chanprame S, Nakasathien S, ToojindaT, Sorajjapinun W, Seehalak W, Tragoonrung S and Srinives P.2008. New microsatellite markers isolated from mungbean (Vignaradiata (L.) Wilczek). Molecular Ecology Resources 8: 1155-1157.

Tangphatsornruang S, Somta P, Uthaipaisanwong P, Chanprasert J,Sangsrakru D, Seehalak W, Sommanas W, Tragoonrung S and SrinivesP. 2009. Characterization of microsatellites and gene contentsfrom genome shotgun sequences of mungbean (Vigna radiata (L.)Wilczek). BMC Plant Biology 9: 137.

Tanksley SD and McCouch SR. 1997. Seed banks and molecularmaps:unlocking genetic potential from the wild. Science 277: 1063-1066.

Tautz D and Renz M. 1984. Simple sequences are ubiquitous repetitivecomponents of eukaryotic genome. Nucleic Acids Research 12:4127-4138.

Thompson JA, Nelson RL and Vodkin LO. 1998. Identification ofdiverse soybean germplasm using RAPD markers. Crop Science 38:1348-1355.

Wang XW, Kaga A, Tomooka N and Vaughan DA. 2004. Thedevelopment of SSR markers by a new method in plants and theirapplication to gene flow studies in azuki bean [Vigna angularis(Willd.) Ohwi & Ohashi]. Theoretical and Applied Genetics 109:352-360.


Effectiveness and efficiency of Gamma rays and Ethyl Methane Sulphonate (EMS)in mungbeanKULDEEP SINGH and M.N. SINGH

Department of Genetics and Plant Breeding, Institute of Agricultural sciences, Banaras Hindu University, Varanasi221005; Uttar Pradesh, India; E-Mail: [email protected](Received : July 17, 2013 ; Accepted : November 25, 2013)

ABSTRACT

Studies on effectiveness and efficiency of gamma rays, EMSand their combination treatments were performed in twocultivars, HUM-12 and IPM-99-125 of mungbean. Thetreatments included three doses of gamma rays, namely, 200Gy, 400 Gy and 600 Gy; three concentrations of EMS i.e., 0.02M, 0.04 M and 0.06 M and three combination treatments viz.,200 Gy + 0.02 M, 400 Gy + 0.02 M and 600 Gy + 0.02 M.Mutagenic effectiveness and efficiency were calculated basedon the biological damage in terms of pollen sterility andlethality in M1 and spectrum of chlorophyll mutants (Chlorina,Albina, Xantha, Viridis and Maculata) in M2 generation. Theresults indicated that the mutagenic effectiveness usuallydecreases with the increase in dose/concentration of mutagens.Among the mutagens, EMS was most effective followed bycombination of treatments in both the cultivars, however, gammarays showed less effectiveness. Similarly, efficiency alsodecreases with increasing dose/concentration of mutagen withslight variation depending upon its method of estimation andcultivars used. The cultivar, HUM-12 scored high values ofeffectiveness and efficiency as compared to IPM 99-125 andthus may be exploited for observing high frequency of mutants.

Key words: EMS , Gamma rays, Mungbean, Mutagenic effectivenessand efficiency

Mungbean (Vigna radiata L. Wilczek) is one of theimportant short duration grain legumes which may be grownin different seasons (Kharif, rabi and spring/summer) in ourcountry. The available varieties of mungbean have low yieldpotential (250 - 400 kg/ha) and restricted variability with respectto various economic traits. The induced mutations may beexploited for creating genetic variability for yield (Singh &Yadav 1987, Wani and Khan 2006), yield components, planttype and resistance to diseases and pests (Singh 1981). Theusefulness of a mutagen in mutation breeding depends notonly on its mutagenic effectiveness (mutations per unit doseof mutagen), but also on its mutagenic efficiency (mutation inrelation to undesirable and desirable changes / damage likelethality, injury etc.)

In the present investigation, an effort has been made tostudy the frequency and spectrum of macro-mutations alongwith the mutagenic effectiveness and efficiency of differentdoses of gamma rays, EMS and combined treatments in M1and M2 generations.


The 500 uniform, dry and healthy seeds of eachtreatment of two cultivars of mungbean (Vigna radiata L.Wilczek), namely, HUM 12 (Malaviya Janchetna) and IPM 99-125 (Meha) were treated to 60Co gamma rays at 200 Gy, 400 Gyand 600 Gy doses at NBRI, Lucknow. Three samplescomprising of 500 seeds each were pre-soaked in distilledwater for six hours and treated with ethylmethane sulphonate(EMS) at three concentrations i.e., 0.02 M, 0.04 M and 0.06 Mfor six hours in phosphate buffer (pH 7.0). Three samples of500 seeds each were first irradiated with gamma rays at 200Gy, 400 Gy and 600 Gy doses and then immersed in 0.02 MEMS solution in the same manner as described above. AfterEMS treatment, the seeds were washed in running tap waterfor six hours to eliminate the residual effect of the chemical. Atotal of 20 treatments including two controls (HUM 12 andIPM 99-125) were sown in randomized block design (RBD)with three replications accommodating 160 seeds perreplication (480 seeds over replications) in 8 rows of 3 meterlength with spacing of 30 x 15 cm between and within rows,respectively at Agricultural Research Farm, Institute ofAgricultural Sciences, Banaras Hindu University, Varanasiduring summer, 2006. The remaining 20 seeds of each treatmentalong with control were allowed to germinate on moist blottingpaper put in Petri dishes at room temperature (25-28 oC) andobservations on germination and shoot length were taken on8th day old plant to measure seedlings injury. The M2generation was raised from individual plants following plant-to-progeny method during Kharif, 2006. The frequency andspectrum of chlorophyll mutations per 100 M2 plants werescored at the seedling stage following the classification ofGustafsson (1940). Both mutagenic effectiveness andefficiency were determined using the formulae given byKonzak et al (1965).

Mutagenic effectiveness = Msf / t.c or Msf / kR (Gy) orMsf / kR(Gy) .t. c

Mutagenic efficiency = Msf / L or Msf / Swhere,Msf = Percentage of families segregating for chlorophyll

mutationst = Period of treatment with chemical mutagen


c = Concentration of chemical mutagen in terms ofpercentage

kR (Gy) = Kilo Roentgen (Gray) of physical mutagenL = Percentage of lethality in M1

S = Percentage of sterility in M1


Different biological parameters like germination,seedling height, plant survival, pollen sterility and ovulesterility were recorded in M1 generation. In M2 generation, thetreated as well as control progenies were screened forchlorophyll mutations during the first four weeks after

germination. Mutation frequency was calculated aspercentage of mutants obtained in M2 families divided bytotal M2 families for chlorophyll mutations in each treatment.

Some definite patterns regarding various biologicalparameters were recorded in M1 generation (Tables 1). Thecombination treatment of gamma rays and EMS was foundmore effective than either of the doses of mutagens alone.The effectiveness and efficiency of each mutagen usuallydecreased with the increase in doses, as higher doses ofgamma rays, EMS and combination treatments causedreduction in all the biological parameters including pollen/ovule fertility. Similar results have been also reported earlierwith different mutagens in mungbean (Rakshit and Singh 2001,

Table 1. Effect of mutagenic treatments on biological parameters such as germination, seedling height, plant survival, pollenfertility and ovule fertility in M1 generation in mungbean cv. Malaviya Janchetna (HUM 12) and Meha (IPM 99-125)

Malaviya Janchetna (HUM 12) Meha (IPM 99-125) Treatment Germination

(%) Seedling

height(cm) Plant

survival (%)

Pollen fertility

(%)

Ovule fertility

(%)

Germination (%)

Seedling height

(cm)

Plant survival

(%)

Pollen fertility

(%)

Ovule fertility

(%) Control 100 4.28 100 100 100 100 6.99 100 100 100

Gamma rays (Gy) 200 Gy 86.25 3.57 85.02 91.62 91.24 86.71 5.63 83.50 91.25 92.49 400 Gy 69.67 3.25 65.53 85.64 84.99 79.69 5.51 77.40 86.08 84.39 600 Gy 63.11 2.95 59.88 82.61 80.07 69.67 4.28 66.23 83.22 75.16

EMS (M) 0.02 M 81.96 3.43 78.53 87.65 88.05 85.21 2.90 79.58 87.82 86.45 0.04 M 48.71 2.97 45.03 81.60 81.40 55.61 2.56 52.05 82.32 75.16 0.06 M 33.22 2.45 30.05 74.93 72.42 44.08 1.86 42.31 74.90 70.14

Gamma rays (Gy) +EMS (M) 200 Gy+0.02 M 71.58 2.90 67.77 85.84 86.78 76.44 2.40 73.56 86.08 84.75 400 Gy+0.02 M 46.39 2.70 44.40 81.52 80.08 49.68 1.72 45.18 81.94 75.01 600 Gy+0.02 M 29.61 2.30 27.85 73.61 72.04 42.36 1.70 41.14 74.72 67.28

Table 2. Frequency and spectrum of chlorophyll mutations induced by mutagenic treatments in M2 generation in mungbean cv.

Malaviya Janchetna (HUM 12) and Meha (IPM 99-125)

Malaviya Janchetna (HUM 12) Meha (IPM 99-125) Frequency (%) Frequency (%)

Mutagenic treatment

Total no. of

seedlings Albina Xantha Chlorina Viridis Maculata

Total mutation frequency

(%)

Total no. of

seedlings Albina Xantha Chlorina ViridisMaculata

Total mutation frequency

(%) Control 1210 - - - - - - 1240 - - - - - -

Gamma rays (Gy) 200 Gy 1115 - - 0.36 - - 0.36 1141 - 0.18 - - - 0.18 400 Gy 1137 0.18 - 0.35 - - 0.53 1128 - 0.18 0.26 - - 0.44 600 Gy 1052 - 0.38 - 0.19 0.28 0.85 1057 0.09 0.38 0.19 - - 0.66 EMS (M) 0.02 M 1137 - 0.35 - 0.35 - 0.70 1145 - - 0.35 - 0.18 0.53 0.04 M 1113 0.18 0.45 0.18 - - 0.81 1087 0.18 0.46 0.18 - - 0.82 0.06 M 1097 - 0.46 0.27 - 0.18 0.91 1117 - 0.18 0.45 - 0.27 0.90

Gamma rays (Gy) + EMS (M) 200 Gy+0.02M 1107 - 0.36 0.45 - - 0.81 1129 - 0.44 - 0.27 - 0.71 400 Gy+0.02M 1085 - 0.46 0.37 - 0.18 1.01 1097 0.27 0.37 0.46 - - 1.10 600 Gy+0.02M 1138 0.37 0.35 0.44 - 0.18 1.34 1107 - 0.54 - - 0.45 0.99 Total mutation frequency %

0.73 2.81 2.42 0.54 0.82 7.32 - 0.54 2.73 1.89 0.27 0.90 6.33

Singh & Singh : Effectiveness and efficiency of Gamma rays and Ethyl Methane Sulphonate (EMS) in mungbean 2 7

Baisakh et al.2004, Tah 2006), urdbean (Singh et al.1999, Rakshitand Singh 2001, Thilagavathi and Mullainathan 2009, Jain andKhandelwal 2009) and cowpea (Ahmad 1999).

In the present study, genotypic differences in relationto frequency of chlorophyll mutation were evident in M2generation. The cultivar, HUM 12 revealed higher frequencyof chlorophyll mutations than Meha indicating thereby thatHUM 12 has higher mutagenic sensitivity than Meha. Fivetypes of chlorophyll mutations, such as albina (white leaves-without chlorophyll, lethal), xantha (yellow-bright, (lethal),chlorina (yellowish green mostly survive up to 30 days),viridis (light green) and maculata (yellowish green spots onleaves) could be observed in seedling stage in M2 generation.However, the frequency of xantha mutant was the highest of2.81 and 2.73, followed by chlorina, 2.42 and 1.89 in HUM 12and Meha, respectively (Table 2).

The data presented in Table 3 indicated that theeffectiveness of both the mutagens and the response ofcultivars were varying. EMS was most effective followed bycombination treatments and gamma rays. These results are inconformity with the findings of earlier workers (Prasad 1972,Gupta and Yashvir 1975, Kharkwal 1998, Auti and Apparao2008, Mishra and Singh 2013). The gamma rays showedminimum effectiveness as compared to all other treatments. Incase of efficiency, combination treatments were found to bemore efficient followed by EMS and gamma ray treatments.The gamma rays, 200 Gy and 400 Gy exhibited less efficiencyas compared to all other treatments.

REFERENCES

Ahmad John S. 1999. Mutation frequency and chlorophyll mutationsin parents and hybrid of cowpea following gamma irradiation. IndianJournal of Genetics and Plant Breeding 59: 357-361.

Auti SG and Apparao BJ. 2008. Mutagen induced variability in proteincontent of mungbean. Journal of Food Legumes 21: 161-162.

Baisakh B, Senapati N and Singh B. 2004. Improvement in geneticarchitecture of mungbean. En. Eco 22 : 141-43.

Gupta PK and Yashvir. 1975. Induced mutation in foxtail millet. I.chlorophyll mutation induced by gamma rays, EMS and DES.Theoretical and Applied Genetics 45: 242-249.

Gustafsson A. 1940. The mutation system of chlorophyll apparatus.Lunds Univ. Arrskr. N.F. Adv 36: 1-40.

Jain SK and Khandelwal V. 2009. Mutagenic effect of EMS and DMS onfrequency and sopectrum of chlorophyll and other macro mutationsin blackgram. Journal of Food Legumes 22: 264-268.

Kharkwal MC. 1998. A comparison of mutagenic effectiveness andefficiency of physical and chemical mutagens. Indian Journal ofGenetics and Plant Breeding 58: 159-167.

Konzak CP, Nilan RA, Wagner J and Foster RJ. 1965. Efficient chemicalmutagenesis. Radiation Botany (Suppl) 5: 49-70.

Mishra D and Singh B. 2013. Prediction of M2 macro and micro-mutation frequency based on M1 effect in greengram (Vigna radiata(L.) Wilczek) IOSR Journal of Agriculture and Veterinary Science2: 1-4.

Prasad MVR. 1972. A comparison of mutagenic effectiveness andefficiency of gamma rays, EMS, NMU and NG. Indian Journal ofGenetics and Plant Breeding 32: 360-367.

Rakshit Sujay and Singh VP. 2001 Chemosensitivity studies in mungbeanand urdbean. Indian Journal of Pulses Research 14: 112-115

Singh DP. 1981. Breeding for resistance to diseases in green gram andblackgram. Theoretical and Applied Genetics 59: 1-10.

Singh V.P and Yadav R.D.S. 1987 Induced macro- and micro- mutationsin mungbean. In proceeding of symposium on crop improvement,Ludhiana (eds. Gill et al).Crop Improvement Society of Indiapp.115-116

Singh VP, Singh M and Lal JP. 1999. Mutagenic effects of gamma raysand EMS on frequency and spectrum of chlorophyll and macro-mutations in urdbean. Indian Journal of Genetics and Plant Breeding59: 141- 143.

Table 3. Mutagenic effectiveness and efficiency of physical and chemical mutagens in mungbean cv. HUM12 and IPM 99-125

Malaviya Janchetna (HUM 12) Meha (IPM 99-125) Mutagenic treatment Lethality %

L Pollen

sterility % S

Mutated families %

Msf

Mutagenic effectiveness Msf / Gy or t.c. or Gy.t.c

Mutagenic efficiency

Msf / L Msf / S

Lethalilty % L

Pollen sterility%

S

Mutated families

% Msf

Mutagenic effectiveness

Msf / Gy or t.c. or Gy.t.c.

Mutagenic efficiency Msf / L Msf / S

Control - - - - - - - - - - Gamma rays (kR)

200 Gy 13.75 8.38 0.36 0.018 0.026 0.043 13.29 8.75 0.18 0.009 0.014 0.021 40 kR 30.33 14.36 0.53 0.013 0.017 0.037 20.31 13.92 0.44 0.011 0.022 0.032 600 Gy 36.89 17.39 0.85 0.014 0.023 0.049 30.33 16.78 0.66 0.011 0.022 0.032 Average 26.99 13.38 0.58 0.015 0.022 0.043 21.31 13.15 0.43 0.010 0.019 0.031 EMS (M) 0.02 M 18.04 12.35 0.70 0.470 0.038 0.057 14.79 12.18 0.53 0.356 0.036 0.044 0.04 M 51.29 18.40 0.81 0.272 0.015 0.044 44.39 17.68 0.82 0.276 0.018 0.046 0.06 M 66.78 25.07 0.91 0.204 0.013 0.036 55.92 25.10 0.92 0.202 0.016 0.036 Average 45.37 18.61 0.81 0.315 0.022 0.046 38.31 15.32 0.75 0.278 0.023 0.042

Gamma rays (Gy) + EMS (M) 200 Gy + 0.02 M 28.42 14.16 0.81 0.027 0.029 0.057 23.56 13.92 0.71 0.024 0.031 0.051 400 Gy + 0.02 M 53.61 18.48 1.01 0.017 0.018 0.055 50.32 18.06 1.10 0.018 0.023 0.061 600 Gy + 0.02 M 70.39 26.39 1.33 0.015 0.019 0.050 57.64 25.08 0.99 0.011 0.017 0.039

Average 50.80 19.68 1.05 0.200 0.023 0.054 43.84 19.02 0.93 0.018 0.024 0.050


Thilagavathi C and Mullainathan L. 2009. Isolation of macro mutantsand mutagenic effectiveness, efficiency in blackgram (Vigna mungo(L.) Hepper). Global Journal of Molecular Sciences 4: 76-79.

Tah PR. 2006. Studirs on gamma rays induced mutations in mungbean(Vigna radiata (L.) Wilczek). Asian Journal of Plant Sciences 5:

61-70.

Wani MR and Khan S. 2006. Estimates of genetic variability inmutated populations and the scope of selection for yield attributesin Vigna radiata (L). Wilczek. Egyptian Journal of Biology 8: 1-6.


Combining Ability Analysis in Medium Duration CGMS Based Hybrid Pigeonpea(Cajanus cajan (L.) Millsp.,)M. P. MESHRAM, A.N. PATIL and ABHILASHA KHARKAR

Pulses Research Unit, Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola-444 104, Maharashtra, India ;E-mail : [email protected](Received : November 08, 2012; Accepted : November 12,2013)

ABSTRACT

Forty eight hybrids were developed by using six A2 cytoplasmbased CGMS lines and eight diverse restorers and their hybridswere evaluated with an objective to estimate the nature of geneaction for yield and yield contributing characters. Predominanceof non additive gene action was observed for almost all thecharacters including seed yield except plant height which wasunder the influence of additive gene action. None of the parentsexhibit significant gca effects for all the characters under study,however among the lines AKCMS 10A, AKCMS 13AandAKCMS 09A and among the testers AKPR 8, AKPR 359 andAKPR 292 were identified as potential parents as they exhibitedsignificant gca effects for most of the important traits. Amongthe hybrid combinations AKCMS 09A x AKPR 8, AKCMS 10Ax ICPR 2740, AKCMS 11Ax AKPR 319, AKCMS 09A x AKPR374 and AKCMS 06A x AKPR 359 might be exploited for theimprovement of respective traits as found to possess desirablegenes for most of the important characters including seed yield.

Key words : General Combining Ability, CGMS, Heterosis,Pigeonpea, Specific Combining Ability

Pigeonpea (Cajanus cajan (L.) Millsp.) is the secondimportant pulse crop in India . It is grown in about 4.09 millionhectares with a production of 3.27 million tonnes of grains(Anonymous 2010-11). Endowed with several uniquecharacteristics, it finds an important place in the farmingsystems adopted by small farmers in a larger number ofdeveloping countries. Seed protein content in pigeonpea(approximately 21%) compares well with that of other importantgrain legumes. In hybrid breeding programme, successdepends upon the choice of parents and a clear knowledgeabout gene action governing specific trait.

Identification of genetic male sterility in pigeonpea(Reddy et.al, 1978 and Wallis et.al, 1981) has opened newvistas for commercial exploitation of hybrid vigour in this crop.Several GMS based pigeonpea hybrids were released forcommercial cultivation by ICRISAT and various SAU’sHowever, the technology suffers from a major technicalbottleneck when it comes to a large scale seed production.The need of rouging out 50% of the fertile plants from thefemale parent was costly and skill oriented operation whichescalated seed cost.

To overcome the inherent problems associated withGMS system, Cytoplasmic Genetic Male Sterility (CGMS)

system were developed using various wild relatives ofpigeonpea. These include A1 derived from C. sericus(Ariyanayagam et.al 1995), A2 from C. scarabaeoides (Saxenaand Kumar, 2003), A3 from C. volubilis (Wanjari et.al. 2001)and A4 from C. cajanifolius (Saxena et.al. 2005). Tikkaet.al.1997 identified and developed a CGMS based line GT288A and released the first commercial hybrid GTH 1.Combining ability analysis helps to choose suitable parentsfor hybridization and provides valuable information regardingcross combinations to be exploited commercially. Therefore,present study was undertaken to estimate combining abilityfor seed yield and other traits in pigeonpea using cytoplasmicgenic male sterile lines having A2 cytoplasm.


The present investigation comprising of six mediumduration cytoplasmic genetic male sterile lines based on A2cytoplasm viz., AKCMS 06A, AKCMS 07A, AKCMS 09A, ,AKCMS 10A, AKCMS 11A, AKCMS 13A and eightgenetically diverse restorers viz., AKPR-210, AKPR-319,AKPR-359, AKPR-292, ICPR-2740, AKPR-372, AKPR-374 andAKPR-8 were crossed in Line x Tester fashion during Kharif2010 at Pulses Research Unit, Dr. Panjabrao Deshmukh KrishiVidyapeeth, Akola (M.S.). The resultant 48 hybrids along withtheir 14 parents and one standard check PKV TARA weresown in a completely randomized block design in tworeplications during Kharif 2011. Each plot consisted of singlerow of 4m.length spaced at 60 x 30 cm. Recommended packageof practices were adopted for optimum crop growth and fullphenotypic expression

Five competitive plants were selected randomly fromeach plot for recording observations on plant height, numberof primary branches plant-1, number of pods plant-1, shellingpercent, pod length, 100 seed weight and seed yield plant-1.Days to 50 % flowering, days to maturity and fertilityrestoration on visual basis were recorded on plot basis. Thedata were analyzed for combining ability following Kempthorne(1957). Relative heterosis, heterobeltiosis as well as standardheterosis were estimated and tested by working out thestandard errors by Hays et al. (1955).


The relative importance of general and specific


combining ability is assessed by estimating the componentsof variance by gca and sca ratio. The information on geneeffects controlling inheritance of various traits is very essentialto evaluate the usefulness of parents while formulating thebreeding programme. In the present study, the analysis ofvariance revealed that the ratio of variance due to GCA to thevariance due to SCA was less than one for most of the importantcharacters including seed yield except plant height indicatingthese traits are under the influence of non additive gene actionand these characters could be improved through heterosisbreeding while, the plant height can be improved by pedigreebreeding as it is under the influence of additive gene action..The above findings are in agreement with the earlier reportsof Sunil Kumar et.al (2003), Reddy Sekhar et.al (2004), SameerKumar et.al (2009), Beekham and Umaharan (2010) and Shobhaand Balan (2010).

The ANOVA showed highly significant differences forthe major characters, indicating the presence of sufficientvariability in the experimental materials selected. The variancedue to female lines exhibited highly significant differences fordays to 50% flowering , days to maturity , plant height andseed yield while, male lines exhibited significant differencesfor days to 50% flowering and days to maturity. The variancefor line x tester were significant for days to 50% flowering,days to maturity, 100 seed weight, number of pods per plant,shelling per cent including seed yield per plant.

Per cent contribution of line, testers and line into testersto the crosses (Table 1) revealed that a greater contribution oflines to the performance of crosses was observed for days to50% flowering, days to maturity 100 seed weight, number ofpods per plant, plant height, length of pod and seed yieldwhile, the contribution of testers to the performance of crosseswere found to be significant only for shelling per cent indicatingthe significant contribution of maternal parents with morefavorable alleles contributing to the number of pods per plant,100 seed weight and seed yield per plant. The contribution oflines and testers were also found equally important for thedevelopment of primary branches. This shows that the averagegeneral combiners may give high performance. Similar resultswere also reported by Pandey and Singh (2002).

The GCA effects of parents (Table 2) revealed thatamong the female parents AKCMS 10A was good generalcombiner for seed yield along with earliness while, AKCMS13A was found to be good general combiner for days to 50%flowering, days to maturity, plant height, primary branches,

length of pod but not for the seed yield. Similarly the AKCMS09A also found to be good general combiner for shelling percent, plant height and seed yield. None of the lines showedgeneral combining ability effect in positive direction for numberof pods per plant.

Among the testers, AKPR 8 was good general combinerfor days to 50 % flowering, days to maturity, shelling per cent,pod length and seed yield. The testers AKPR 210, AKPR 319,AKPR 359 showed negative general combining ability effectfor earliness hence these parents could be utilized forexploitation of early maturing genotypes while, the testersAKPR 359, ICPR 2740 and AKPR 372 showed gca effect inpositive direction for 100 seed weight and dwarfness. AKPR292 showed good general combining ability only for the seedyield in positive direction.

Since none of the parents showed good gca effect forall the traits under study, the lines AKCMS 10A, AKCMS13Aand AKCMS 09A and among the testers AKPR 8, AKPR359 and AKPR 292 may be given importance in the choice ofthe parents based on the overall gca effects. Besides, thelines or testers showing good gca effect for particular yieldcomponent may be used in hybridization programme with linesor testers having good gca for other trait.

The estimates of specific combining ability revealed that15 of the 48 crosses exhibited significant positive sca effectsfor seed yield per plant. The estimates of top fifteen hybridsshowing high sca effects for seed yield along with their per seperformance (Table 3) revealed that the crosses having highper se performance also showed high sca effect for seed yieldin a positive direction therefore per se performance may beconsidered along with the sca effect while selecting thehybrids. Similar results also reported by Yadav et.al (2008).

Among the best 15 high yielding hybrids, only onehybrid exhibited significant sca effect in desirable directionfor days to 50% flowering whereas five hybrids for maturity,eight hybrids for 100 seed weight, nine hybrids for number ofpods per plant and seven hybrids for shelling per cent exhibitedsignificant sca effect in desirable direction. None of the hybridsexhibited significant sca effect for plant height, number ofprimary branches per plant and for length of pod.

Among the top fifteen hybrids based on high sca effectfor yield, the hybrid combination AKCMS 09A x AKPR 8having the highest mean yield per plant also exhibited highestsca effect in positive direction for seed yield and showed

Sources of variation Days to 50% Flowering

Days to Maturity

100 Seed Weight

Number of Pods Plant-1

Shelling (%)

Plant Height (cm)

Number of Branches Plant-1

Pod Length (cm)

Seed yield Plant-1

Lines 84.16% 39.76% 18.76% 16.35% 8.54% 55.26% 15.89% 20.31% 38.12%

Testers 6.04% 26.68% 12.31% 12.26% 16.98% 7.45% 15.82% 4.56% 5.92%

Lines x Testers 9.80% 33.57% 68.93% 71.38% 74.47% 37.29% 68.29% 75.13% 55.96%

Table 1. Per cent contribution of lines, testers and line x testers to crosses

Meshram et al., : Combining ability analysis in medium duration CGMS based hybrid Pigeonpea (Cajanus cajan (L.) 3 1

Table 2. General combining ability effects of parents

Parents Days to 50% Flowering

Days to Maturity

100 Seed Weight


Shelling (%)

Plant Height (cm)

Number of Branches Plant-1

Pod Length (cm)

Seed yield Plant-1

Lines AKCMS 06A 3.958 * 3.219 ** -1.074 ** -10.328 ** -1.452 ** -2.083 ** -0.573 ** -0.062 ** -6.991 ** AKCMS 07A 3.708 * 2.406 ** -0.680 ** -8.953 ** -1.765 ** -6.646 ** 0.115 0.021 ** -5.503 ** AKCMS 09A 4.458 * 1.469 ** -0.068 ** 6.822 3.229 ** -7.646 ** -0.448 ** -0.016 ** 5.353 ** AKCMS 10A -6.854 ** -3.344 ** 0.807 ** 15.159 -0.777 ** 7.667 0.052 -0.023 ** 6.216 ** AKCMS 11A 0.583 -1.719 ** 0.726 ** 2.922 1.429 * 14.542 0.302 0.034 ** 1.409 AKCMS 13A -5.854 ** -2.031 ** 0.289 ** -5.622 ** -0.665 ** -5.833 ** 0.552 * 0.046 ** -0.484 ** Testers AKPR 210 -1.083 ** -1.677 ** -0.424 ** -1.211 ** -0.806** 3.854 0.031 0.002 -2.489 ** AKPR 319 -0.250 ** -0.677 ** -0.932 ** -11.828 ** 2.519 * -6.063 ** -0.635 ** -0.009 ** -2.297 ** AKPR 359 -0.333 ** -1.844 ** 0.476 ** -1.711 ** -2.756 ** 2.104 -0.135 ** 0.003 -1.755 ** AKPR 292 2.167 1.906 ** -0.282 ** 18.289 -4.256 ** 3.021 0.531 -0.014 ** 3.045 * ICPR 2740 1.417 3.323 ** 0.951 ** -1.228 ** -0.215 ** -1.646 ** 0.531 -0.006 ** 0.078 AKPR 372 -0.167 ** 1.656 ** -0.157 ** 2.972 0.46 -2.313 ** 0.198 -0.006 ** -0.172 ** AKPR 374 0.333 0.24 0.476 ** -2.945 ** 1.127 0.271 -0.052 ** -0.014 ** 1.303 AKPR 8 -2.083 ** -2.927 ** -0.107 ** -2.336 ** 3.927 ** 0.771 -0.469 ** 0.044 ** 2.286 * Line 25.51 7.23 0.569 94.319 3.475 75.773 0.063 0.001 29.32 Tester 0.9 4.562 0.35 63.433 6.73 1.923 0.011 -0.001 3.847

**- Significant at 1% level *- Significant at 5% level

Table 3. Top Fifteen Specific cross combinations for seed yield per plant and other yield components

**- Significant at 1% level *- Significant at 5% levelWhere, L1-AKCMS 06A, L2-AKCMS 07A, L3-AKCMS 09A, L4-AKCMS 10A, L5-AKCMS 11A, L6-AKCMS 13A, T 1-AKPR 210,T2-AKPR, 319 T3-AKPR 359 T4-AKPR 292 T5- ICPR 2740 T6- AKPR 372 T7- AKPR 374 T8- AKPR 8

Cross Seed yield Plant-1

Average Seedyield

Plant-1

Days to 50%

Flowering

Days to Maturity

100 Seed Weight


Shelling (%)

Plant Height (cm)

Number of Branches

Plant-1

Pod Length

(cm)

Plant Fertility

(%) L3xT8 11.639 ** 41.5 0.708 -3.635 ** 2.401 ** -3.364 15.845 ** -5.271 -0.219 -0.125 100 L5xT4 10.574 ** 37.25 -0.167 3.719 ** 3.882 ** 10.111 16.526 ** 6.792 1.031 -0.067 100 L4xT5 10.234 ** 38.75 0.021 -4.073 ** 3.018 ** 21.091 ** 7.684 ** 5.833 1.781 0.131 98 L5xT2 9.366 ** 30.7 -3.25 -3.698 ** -0.468 27.128 ** 8.993 ** 14.375 -0.302 0.078 100 L3xT7 8.722 ** 37.6 -1.708 1.781 * 0.668 ** 19.545 ** 11.586 ** 4.729 0.365 -0.017 98 L6xT5 8.384 ** 30.2 -1.979 -1.885 * -0.714 ** 25.872 ** -0.059 4.333 0.281 0.062 98 L4xT7 7.559 ** 37.3 -0.396 -0.49 2.793 ** 32.007 ** -1.807 -2.583 -1.135 -0.061 97 L3xT6 6.897 ** 34.3 0.792 1.781 * 0.351 41.628 ** 0.511 4.313 -0.385 0.025 84 L2xT6 5.553 ** 22.1 -4.958 * -0.656 -0.086 8.403 5.411 * -1.688 1.052 -0.013 78 L2xT2 5.178 ** 19.6 1.125 2.677 ** 1.589 ** 26.703 ** -2.589 0.563 -0.115 -0.01 98 L5xT3 5.174 ** 27.05 -0.167 -1.031 2.074 ** 4.911 1.843 0.708 -1.302 0.066 99 L1xT3 5.124 ** 18.6 -0.542 -1.969 * 0.774 ** 23.961 ** 0.543 3.833 1.573 0.013 98 L3xT4 4.33 * 34.95 1.458 3.531 ** -0.424 34.811 ** -7.605 ** -8.521 -1.219 0.083 97 L1xT1 4.057 * 16.8 0.208 1.365 0.474 1.961 -1.957 1.583 -0.594 -0.037 92 L4xT3 3.918 * 30.6 -0.229 2.594 ** -0.157 -0.626 12.168 ** 2.083 -0.052 -0.027 99

significant sca effect in positive direction for days to maturity,100 seed weight and shelling percentage. This hybrid alsoexhibit the highest heterosis, heterobeltiosis and standardheterosis over check PKV TARA among all the hybrids,therefore this hybrid can be best utilized for commercialexploitation. Fertility restoration is a crucial requirement forsuccessful hybrid synthesis using CGMS system in pigeonpea.The hybrid combination AKCMS 09A x AKPR 8 also restores100% fertility.

The hybrid AKCMS 10A A x ICPR 2740 exhibitedsignificant sca effect for five important traits viz., days tomaturity, 100 seed weight, number of pods per plant, shellingper cent and seed yield per plant. The hybrid AKCMS 11Ax

AKPR 319 showed significant sca for four important traitsviz., days to maturity number of pods per plant, shelling percent and seed yield. The hybrid AKCMS 09A x AKPR 374showed significant sca effect for 100 seed weight, number ofpods, shelling per cent and seed yield. Similarly, the hybridAKCMS 06A x AKPR 359 exhibited significant sca effect forfour important traits like days to maturity, 100 seed weight,number of pods and seed yield. All these combinations alsorestore plant fertility from 98 to 100 per cent.

Among all the top ranking 15 hybrids, thirteen hybridsexhibited significant heterosis over mid parent and heterosisover better parent whereas, 10 hybrids exhibited significantstandard heterosis over best check PKV TARA (Table 4).


Table 4. Top Fifteen Specific cross combinations with their heterosis, heterobeltiosis and standard heterosis for seed yield perplant with average yield and gca effects of their parents

**- Significant at 1% level *- Significant at 5% levelWhere L1- AKCMS 06A, L2 -AKCMS 07A, L3- AKCMS 09A, L4- AKCMS 10A, L5- AKCMS 11A, L6- AKCMS 13A, T1- AKPR 210 T2- AKPR319 T3- AKPR 359 T4- AKPR 292 T5- ICPR 2740 T6- AKPR 372 T7- AKPR 374 T8- AKPR 8

Cross sca for Seed yield Plant-1

Average Seed yield Plant-1 (g)

gca of parents Heterosis (%) Heterobeltiosis (%) Standard Heterosis (%)

L3xT8 11.639 ** 41.5 H x H 290.59 ** 245.83 ** 74.37 ** L5xT4 10.574 ** 37.25 L x H 80.61 ** 73.66 ** 56.51 ** L4xT5 10.234 ** 38.75 H x L 125.62 ** 93.75 ** 62.82 ** L5xT2 9.366 ** 30.7 L x L 82.74 ** 55.05 ** 28.99 * L3xT7 8.722 ** 37.6 H x L 179.55 ** 113.03 ** 57.98 ** L6xT5 8.384 ** 30.2 L x L 53.89 ** 21.29 * 26.89 * L4xT7 7.559 ** 37.3 H x L 98.14 ** 86.50 ** 56.72 ** L3xT6 6.897 ** 34.3 H x L 94.61 ** 31.92 ** 44.12 ** L2xT6 5.553 ** 22.1 L x L 13.33 -15 -7.14 L2xT2 5.178 ** 19.6 L x L 46.27 ** 42.03 * -17.65 L5xT3 5.174 ** 27.05 L x L 57.27 ** 36.62 ** 13.66 L1xT3 5.124 ** 18.6 L x L 30.99 27.4 -21.85 * L3xT4 4.33 * 34.95 H x H 127.69 ** 62.94 ** 46.85 ** L1xT1 4.057 * 16.8 L x L 35.76 21.74 -29.41 ** L4xT3 3.918 * 30.6 H x L 76.88 ** 53.00 ** 28.57 *

Therefore along with the sca effects of the hybrids, theirheterosis, heterobeltiosis, standard heterosis and per seperformance may be considered while, selecting the besthybrid combinations for their potential use in hybrid breedingprogramme. Similar inference was also drawn by Sameer Kumaret.al. (2009).

Therefore among the hybrid combinations, AKCMS 09Ax AKPR 8, AKCMS 10A x ICPR 2740, AKCMS 11Ax AKPR319, AKCMS 09A x AKPR 374 and AKCMS 06A x AKPR 359might be exploited for the improvement of respective traits asfound to possess desirable genes for most of the importantcharacters including seed yield.

An examination of gca effects of the parents and scaeffects of the resultant hybrids specially for seed yield revealedthat it may not be possible to find a definite trend in all thehybrids. Amarnath and Subrahmanyam (1992) suggested thatthe crosses with high sca effects could be much useful if theywere accompanied by high gca effects of parents involvedindicating the major role of additive gene action complimentingfor the expression of the traits. In the present study the parentsinvolving the crosses AKCMS 09A x AKPR 8 and AKCMS09A x AKPR 292 for seed yield, AKCMS 11A x AKPR 319 fordays to maturity, AKCMS 10A x ICPR 2740 and AKCMS 11Ax AKPR 359 for 100 seed weight, AKCMS 09Ax AKPR 8 andAKCMS 11A x AKPR 319 for shelling per cent had high gcaeffects of the parents and also produced high sca effects.Some of the cross combinations having the parents with highx low and low x high gca effects also produced significant scaeffects as observed in the crosses AKCMS 11A x AKPR 292,AKCMS 10A A x ICPR 2740, AKCMS 09A x AKPR 374 forseed yield, AKCMS 07A x AKPR 372 for days to 50% flowering,AKCMS 09Ax AKPR 8, AKCMS 10A x ICPR 2740 for maturity

, AKCMS 11A x AKPR 292, AKCMS 09A x AKPR 374, AKCMS07A x AKPR 319 for 100 seed weight, AKCMS 11A x AKPR292, AKCMS 09A x AKPR 374 for shelling per cent. High scaeffects of high x low gca combinations might be due tocomplementary non additive inter-allelic interactions and hencecould be used in heterosis breeding. In some of the crosseshaving high sca effects, both the parents were poor generalcombiners were crossed. Such situation was noticed in thecrosses of AKCMS 11A x AKPR 319, AKCMS 13A x ICPR2740, AKCMS 07A x AKPR 372, AKCMS 07A x AKPR 319 forseed yield, AKCMS 09A x AKPR 8, AKCMS 07A x AKPR 319for 100 seed weight, AKCMS 10A x ICPR 2740, AKCMS 10Ax AKPR 359 for shelling per cent and all the hybridcombinations which had significant sca for number of podswere produced by poor general combiner. This indicates thepresence of non additive gene effects in these crosscombinations. This was in agreement with the earlier reportsof Baskaran and Muthiah(2007), Shobha and Balan (2010) andThiruvengadam and Muthiah (2012).

The studies on combining ability indicated that amongthe lines AKCMS 10A, AKCMS 13A and AKCMS 09A andamong the testers AKPR 8, AKPR 359 and AKPR 292 may begiven importance in the choice of the parents based on theoverall gca effects which can be used in multiple crossingprogramme. Based on the sca effects, per se performance,heterosis over mid parent, better parent and standard heterosisfor seed yield and their significant response to other relatedtraits, the hybrids AKCMS 09A x AKPR 8, AKCMS 10A xICPR 2740, AKCMS 11Ax AKPR 319, AKCMS 09A x AKPR374 and AKCMS 06A x AKPR 359 could be commerciallyexploited for development of high yielding hybrids inpigeonpea.

Meshram et al., : Combining ability analysis in medium duration CGMS based hybrid Pigeonpea (Cajanus cajan (L.) 3 3

REFERENCES

Anonymous. 2011. Directorate of Economics and Statistics, Departmentof Agriculture and Cooperation. 2010-11.

Ariyanayagam RP, Ageshwar Rao A and Zaveri PP. 1995. Cytoplasmic-genic male sterility in interspecific matings of Cajanus. Crop Science35: 981-985.

Amarnath S and Subrahmanayam GS. 1992. Combining ability forseedling traits in chewing tobacco (Nicotiana tobacum) Annals ofAgricultural Research 13:330-334.

Baskaran K and Muthiah AR. 2007. Combining ability studies inpigeonpea. Legume Research 30: 67-69.

Beekham AP and Umaharan. 2010. Inheritance and combining abilitystudies of pod physical and biochemical quality traits in vegetablepigeonpea. Euphytica 176:36-47.

Hays, H.K., Immer, I.R. and Smith, D.C. 1955. Heterosis in methods ofPlant Breeding. Mcgraw-Hill Book Company Inc. New Yord: 52-65.

Kempthorne, O. 1957. An introduction to genetic statistics, John Wileyand Son Inc. Newyork, Champman and Hall Ltd. London, pp.468-470.

Kumar S, Lohithaswa HC and Dharamaraj PS. 2003. Combining abilityand stability analysis for grain yield, protein content and otherquantitative traits in pigeonpea. Journal of Maharashtra AgriculturalUniversities 28:141-144.

Pandey N and Singh NB. 2002. Hybrid vigour and combining ability in

long duration pigeonpea (Cajanus cajan (L) Millsp) hybridsinvolving male sterile lines. Indian Journal of Genetics 62(3) : 221-225.

Reddy BVS, Green JM and Bisen SS. 1978.Genetic male sterility inpigeonpea. Crop Science. 18:362-364.

Shobha D and Balan A. 2010. Combining Ability in CMS/GMS BasedPigeonpea (Cajanus cajan (L.) Millsp.,) Hybrids. Madras AgriculturalJournal., 97 (1-3): 25-28.

Saxena KB and Kumar RV 2003. Development of cytoplasmic nuclearmale-sterility system in pigeonpea using Cajanus scarabaeoides(L.) Thouars. Ind. J. Genet., 63(3): 225-229.

Saxena KB, Srivastava DP, Chauhan, YS and Masood Ali. (2005). Hybridpigeonpea. In: Masood Ali and Shiva Kumar

Tikka SBS, Parmar LD and Chavan RM. 1997. First record ofcytoplasmic genetic male sterility system in pigeonpea (Cajanuscajan (L.) Millsp.) through wide hybridization. GAU ResearchJournal. 22(2): 160-162.

Thiruvengadam V and Muthiah AR. 2012. Combining ability analysisfor yield and its components in pigeonpea using genetic malesterile lines Journal of Food Legumes 25(3):171-174.

Wanjari KB, Patil AN, Manapure P, Manjayya JG and Manish P. 2001.Cytoplasmic male sterility in pigeonpea with cytoplasm fromCajanus volubilis. Annals of Plant Physioogy. 13: 170-174.

Yadav AS, Tank CJ, Acharya S and Patel JB. 2008. Combining abilityanalysis involving Indo-African genotypes of pigeonpea. Journalof Food Legumes 21(2):95-98.


Genetic variability, character association and path analysis in clusterbean (Cyamopsistetragonoloba (L.) Taub)A. MANIVANNAN and C. R. ANANDAKUMAR

Centre for Plant Breeding and Genetics, TNAU, Coimbatore - 64510033, Tamil Nadu, India; Directorate of MaizeResearch, Pusa, New Delhi - 110 012, India, E mail : [email protected](Received : September 11, 2013 ; Accepted : December 04, 2013)

ABSTRACT

Clusterbean (Cyamopsis tetragonoloba (L.) Taub) is commonlyknown as Guar, is a valuable arid legume crop grown for itsgum, vegetable and also fodder. Very few efforts have made tounderstand the association of various yield components andtheir direct and or indirect influence on yield of clusterbean.In the present study forty two genotypes of clusterbean selectedfrom various genetic backgrounds with diverse geographicalorigin were used to study the association pattern amongmorphological traits and direct and indirect effect of these traitson productivity is also discussed. Number of pods per plant,cluster per plant, pods per cluster, and branches per plant hadpositive and significant correlation with seed yield per plant,whereas, cluster per pod, 100-seed weight, followed by seed perpod had positive and greater direct effects on seed yield perplant and pod length, branches per plant and days to maturityhad negative direct effect on seed yield per plant.

Key words: Correlation, Clusterbean, Genetic variability, Path analysis

Clusterbean (Cyamopsis tetragonoloba (L.) Taub) iscommonly known as Guar. It is a deep rooted annual aridlegume crop known for its drought tolerance and suitabilityfor various limited environments. India is the major guarproducer accounting for 80% of the world’s productionfollowed by Pakistan, USA and South Africa. In India, guar isbeing grown mainly in arid and semiarid regions of north-western states of Rajasthan, Gujarat, Haryana, Punjab, partsof Uttar Pradesh, Madhya Pradesh and Tamil Nadu coveringabout 3.34 million hectares with a production of 0.4 milliontonnes of guar seed. Rajasthan is the largest produceraccounting for 70% of total guar production followed byGujarat, Haryana and Punjab. The productivity of cluster beanranges from 474 kg/ha in Rajasthan to 1200 kg/ha in Haryana(Ahlawat et al. 2013). Cluster bean known for its endospermbound polysaccharide gum known as galactomannan, whichfetches high value in shale energy production field (frackingin petroleum industries), textile, paper, pharmaceutical,nutraceutical and cosmaceutical industries.

Very limited efforts have been made in cluster bean forgenetic improvement of seed yield through systematicbreeding programme. Yield is a complex trait influenced byvarious agro morphological and reproductive traits and hence,there is a need to study the association and their direct andindirect effects on seed yield. Correlation coefficient offers ameans of determining the important traits influencing the

dependent trait such as yield and it also helps in thedetermination of the selection criteria for simultaneousimprovement of various characters along with economic yield.Cluster bean for gum purpose is being introduced for largescale cultivation in Tamil Nadu recently. It will be more desirableto know the diversity of germplasm which will be suited toclimatic condition of Tamil Nadu. In the present study anattempt has been made to assess the factors determining seedyield in cluster bean through association analysis and pathcoefficient.


The experimental material consisted of 42 diverseclusterbean genotypes from from CCS HAU, Hisar, Haryana;Rajasthan Agriculture Research Institute, Swami KeshwanandRajasthan Agricultural University, Durgapur, Rajasthan;Sardarkrushinagar Dantiwada Agricultural University,Krushinagar, Gujarat; Indian Agricultural Research Institute,Pusa, New Delhi, local landraces from Rajasthan and TamilNadu which represents eco-geographical diverse areas ofIndia. Out of 42 genotypes, 36 are of grain type (gum purpose),five of vegetable type and only one is of forage type. Thematerial was grown in a randomized block design with tworeplications with spacing of 45 x 15 at Department of PlantBreeding and Genetics, Agricultural College and ResearchInstitute, Madurai. Each entry was sown in single row with arow length of 3m. Five plants were randomly selected fromeach entry and replication; and observations were recordedon twelve morphological as well as yield attributes includingseed yield as listed in Table 1.

The phenotypic and genotypic variances in terms oftheir coefficients, heritability, genetic advance as per cent ofmean, Correlation and path analysis was calculated followingstandard methods. The estimates of PCV and GCV wereclassified as low (<10%), medium (10-20%) and high (>20%) .Correlation coefficient between all possible pairs of charactersand path analysis using the seed yield as dependent characterwere estimated .


The analysis of variance showed that the genotypesdiffered significantly among themselves for all the charactersindicating the presence of adequate variability. The range(Table 1) was maximum for pods per plant followed by plant

Manivannan & Kumar : Genetic variability, character association and path analysis (Cyamopsis tetragonoloba (L.) Taub) 3 5

Characters Minimum Maximum Mean GCV PCV Heritability (%) GA (% of mean)

Plant height 45.35 94.60 69.76 10.45 16.50 40 13.63 Primary branches per plant 0.00 8.40 4.91 42.74 51.55 69 73.01 Secondary branches per plant 0.00 5.35 4.99 44.55 49.06 79 77.43 Clusters per plant 10.80 32.90 21.81 17.91 32.17 31 20.53 Pods per cluster 2.60 10.70 7.51 16.53 23.67 49 23.78 Pod length 5.26 12.88 6.56 25.30 26.21 93 50.32 Seeds per Pod 6.62 9.20 8.19 4.65 7.59 38 5.87 Pods per plant 21.20 132.10 77.00 19.77 36.25 30 22.22 Days to 50% flowering 23.50 34.50 25.84 11.44 11.72 95 22.98 Days to maturity 87.50 107.00 98.17 5.71 6.23 84 10.78 100-Seed weight 3.32 4.99 3.94 7.95 9.76 66 13.33 Seed yield per plant 5.76 25.95 15.18 18.84 31.71 35 23.06

Table 1. Estimation of genetic parameters for yield and its component characters in clusterbean.

* Significant at 0.05 level of probability ** Significance at 0.01 level of probabilityrG- Genotypic correlation , rP- Phenotypic correlationTraits - PH (Plant height), B/P (Branches per plant), 2B/P (Secondary branches per plant), C/P (Clusters per plant), P/C(Pods per cluster), PL (Podlength), S/P (Seeds per pod), P/P (Pods per plant) DFF (Days to fifty percent flowering), DTM (Days to maturity), 100 SW(100 seed weight), SPY(Seed yield per plant)

Table 2. Genotypic and Phenotypic correlation of various agro morphological traits of Clusterbean PH B/P 2B/P C/P P/C PL S/P P/P DFF DTM 100SW SPY PH rG 1 -0.488** -0.054 -0.691** 0.340* -0.027 0.160 -0.062 -0.002 -0.052 0.254 0.156 rP 1 -0.204 -0.030 0.064 0.405** 0.006 0.184 0.233 -0.029 0.0210 -0.009 0.338* B/P rG 1 1.003** 1.07** 0.120 -0.592** -0.431** 0.893** -0.310* -0.180 -0.465** 0.560** rP 1 0.528** 0.831** 0.127 -0.433** -0.142 0.679** -0.238 -0.167 -0.350* 0.492** 2B/P rG 1 1.021** 0.418** -0.666** 0.080 0.652** -0.135 -0.507** -0.617** 1.085** rP 1 0.642** 0.217 -0.185 -0.119 0.685** 0.012 -0.089 -0.099 0.639** C/P rG 1 -0.062 -0.597** -0.335* 0.838** -0.239 -0.318* -0.428** 0.581** rP 1 0.108 -0.287 -0.041 0.812** -0.119 -0.121 -0.192 0.668** P/C rG 1 -0.938** -0.564** 0.558** -0.345* 0.052 -0.829** 0.532** rP 1 -0.638** -0.205 0.471** -0.237 0.0230 -0.514** 0.505** PL rG 1 0.693** -0.920** 0.530** -0.041 0.874** -0.629** rP 1 0.505** -0.486** 0.502** -0.047 0.713** -0.336* S/P rG 1 -0.313* 0.274 0.044 0.541** 0.110 rP 1 -0.138 0.133 0.117 0.403** 0.060 P/P rG 1 -0.391* -0.450** -0.668** 0.823** rP 1 -0.203 -0.156 -0.318* 0.793** DFF rG 1 0.250 0.366* -0.233 rP 1 0.216 0.337* -0.110 DTM rG 1 -0.162 -0.127 rP 1 -0.077 -0.011 100 SW rG 1 -0.481** rP 1 -0.216 SPY rG 1 rP 1

height, cluster per plant and seed yield per plant. Variances interms of coefficient of variation indicated that there were littledifferences between phenotypic and genotypic variance forsome of the characters viz., pod length, days to maturity anddays to 50% flowering, indicating that these characters wereless affected by environment. On the other hand, characterssuch as seed yield per plant, number of pods per plant andplant height were influenced by the environment.

High heritability and high genetic advance as percentof mean was recorded for primary branches per plant,secondary branches per plant, pod length and days to fiftypercent flowering. High heritability and moderate geneticadvance as percent of mean was recorded for days to maturityand 100 seed weight. Similar results were obtained by Dass etal. (1973), Dabas et al. (1982), Singh et al. (2001), Saini et al.(2010) and Girish et al. (2012) for high heritability of branchesper plant, days to fifty percent flowering, days to maturity,


100 seed weight and pod length. High heritability with highgenetic advance showed the preponderance of additive geneeffect, hence simple selection for those characters should berewarding. Moderate heritability and high genetic advance aspercent of mean was recorded for cluster per plant, pods percluster and seed yield per plant. Moderate heritability andlow genetic advance as percent of mean was recorded forseed per plant. This showed high magnitude of non-additivegene action with less environmental influence.

Yield is a complex traits controlled by several simplyinherited traits. The correlation coefficients highlight thepattern of association among such yield components and helpsdetermine how a complex trait such as yield can be improved.Phenotypic and Genotypic correlations for all possiblecombinations are presented in Table 2. Seed yield per plantshowed positively significant correlation with pods per plant,cluster per plant, pods per cluster, and branches per plant atboth genotypic and phenotypic levels, the results obtainedfrom the present investigation are in strong agreement withfindings of Shah et al. (2000), Ibrahim et al. (2013), whoreported significantly positive correlation of yield with plantheight, pods cluster per plant, pods per plant and pod yieldper plant. Pod length and 100 seed weight exhibitedsignificantly negative correlation with seed yield per plant.This implied selection for seed yield may not be desirable ifwe look for test seed weight. Primary branches per plantshowed positive correlation with seed yield per plant, podsper plant and cluster per plant at the same time it hadsignificantly negative correlation with pod length, seeds perpod and 100 seed weight. Profuse branching plant typeproduced more yields and the same time individual seedparameter got compensated. 100 seed weight showed negativecorrelation with pods per plant, cluster per plant, pods percluster and branches per plant in terms of genotypic andphenotypic level, however it had positively significantcorrelation with pod length, seed per pod and days to fifty

percent flowering. It showed that seed weight mostly dependson quantity of seeds only. Plant height showed negativelysignificant correlation with branches per plant and clustersper plant in terms of genotypic correlation. It suggested tallerthe plant, lesser the cluster number and minimum number ofbranches. At the same time, plant height showed positivelysignificant correlation with seed yield plant in terms ofphenotypic correlation since number of pods per cluster waspositively correlated with plant height. Our results were inaccordance with findings of Sanghi and Sharma, (1964). Simplyby looking into correlation only we cannot determine the truerelationship of plant height and seed yield per plant, it has tobe tested further for their direct and indirect effect in pathanalysis.

The path coefficient analysis revealed direct andindirect effects of twelve characters on seed yield are presentedin Table 3. The residual effect was low (0.329), Residual effectwhich measures the effects of those variables not included inthe study was negligible, hence indicating the number ofcharacters chosen for the study were appropriate. The clusterper pod, 100-seed weight, followed by seed per pod hadpositive and greater direct effects on seed yield per plant atthe same time pod length, branches per plant and days tomaturity had negative direct effect on seed yield per plant andthese were in agreement with findings of Singh et al. (2002),Hingane and Navale (2008) and Girish et al. (2012). The indirectcontribution of 100 seed weight via primary branches per plant,seed per pod, pods per plant were positive and greater inmagnitude, however pod length and cluster per plants werenegative. Contribution of cluster per plant through pod length,secondary branches per plant were considerably positivevalues, days to maturity and plant height shown merelypositive values and rest of the characters shown negativeeffect only. The indirect contribution of pods per plant viacluster per plant, pods per cluster and pod length were positivebut it was negative in effect through 100 seed weight and

Residual effect: 0.329*Significant at 0.05 level of probability ** Significance at 0.01 level of probabilityTraits - PH (Plant height), B/P (Branches per plant), 2B/P (Secondary branches per plant), C/P (Clusters per plant), P/C(Pods percluster), PL (Pod length), S/P (Seeds per pod), P/P (Pods per plant) DFF (Days to fifty percent flowering), DTM (Days to maturity), 100SW(100 seed weight), SPY (Seed yield per plant)

PH B/P 2B/P C/P P/C PL S/P P/P DFF DTM 100SW Genotypic correlation

with SPY PH -0.1451 0.5366 -0.0255 -0.7303 0.0570 0.0576 0.1347 0.0313 -0.0004 0.0003 0.2397 0.1560 B/P 0.0708 -1.0995 0.4721 1.1309 0.0200 1.2673 -0.3627 -0.4501 -0.0501 0.0009 -0.4392 0.5600** 2B/P 0.0079 -1.1032 0.4705 1.0785 0.0700 1.4261 0.0669 -0.3289 -0.0218 0.0026 -0.5833 1.0850** C/P 0.1003 -1.1771 0.4804 1.0564 -0.0104 1.2786 -0.2822 -0.4226 -0.0387 0.0016 -0.4052 0.5810** P/C -0.0494 -0.1314 0.1967 -0.0658 0.1674 2.0092 -0.4741 -0.2811 -0.0558 -0.0003 -0.7837 0.5320** PL 0.0039 0.6507 -0.3133 -0.6307 -0.1570 -2.1416 0.5829 0.4640 0.0856 0.0002 0.8261 -0.6290** S/P -0.0232 0.4741 0.0374 -0.3544 -0.0943 -1.4839 0.8412 0.1580 0.0443 -0.0002 0.5114 0.1100 P/P 0.0090 -0.9814 0.3069 0.8853 0.0933 1.9706 -0.2635 -0.5042 -0.0632 0.0023 -0.6320 0.8230** DFF 0.0003 0.3410 -0.0635 -0.2527 -0.0578 -1.1346 0.2305 0.1972 0.1616 -0.0013 0.3461 -0.2330 DTM 0.0076 0.1984 -0.2385 -0.3361 0.0088 0.0869 0.0368 0.2270 0.0404 -0.0052 -0.1533 -0.1270 100SW -0.0368 0.5108 -0.2903 -0.4526 -0.1387 -1.8710 0.4550 0.3370 0.0592 0.0008 0.9456 -0.4810*

Table 3. The direct (diagonal) and indirect effects of some morphological traits on seed yield per plant of Clusterbean

Manivannan & Kumar : Genetic variability, character association and path analysis (Cyamopsis tetragonoloba (L.) Taub) 3 7

branches per plant. Higher order positive and greatercontribution of seed per pod through 100 seed weight wasobserved. 100 seed weight which had negative genotypiccorrelation with seed yield per plant, however it showedpositive direct effect on seed yield per plant in path analysis,this kind of negative correlation arouse because of negativeindirect effects of other traits like secondary branches perplant, pods per plant, cluster per plant, pod length through100 seed weight in path analysis. The same pattern wasobserved for seeds per pod and cluster per plant in comparisonof direct effect and correlation with seed yield per plant. Plantheight showed positive and significant phenotypic correlationwith seed yield per plant, however, direct effect of plant heightto seed yield per plant was negative. Our results were inagreement with previous research findings of shah et al. (2000)and Ibrahim et al. (2013). The conflict relationship betweenthe correlation and the path coefficient analysis is widelyobserved among the major crop plants, because correlationsimply measures the apparent mutual association betweenthe two traits without regard to the cause, whereas pathcoefficient specifies the causes and measures their relativeimportance. So, it may be concluded from these findings thatcorrelation alone may not give complete information but whenused in combine with path coefficient analysis will give abetter measure of cause and effect relationship existingbetween different pairs of characters. The results of presentinvestigation on direct effect of 100 seed weight, clusters perplant and seeds per pod on seed yield per plant indicatedinteresting fact that, traits having high direct effects notalways shown higher degree of correlation. Similar conclusionswere reported by many researchers viz., Dewey and Lu (1959)in crested wheatgrass, Phadnis et al. (1970) in chickpea, Singhand Mehndiratta (1970), Kurer (2007) in cowpea, Bhadru (2011)in pigeonpea and Chaubey et al. (2012) in faba bean.

From the above said discussion, it could be deducedthat the direct and indirect selection on the basis of traits viz.,number of clusters per plant, number of pods per cluster,number of seeds per pod and 100 weight in the genotypesunder study would be rewarding in improving the yield.

ACKNOWLEDGEMENTS

The work presented in this paper is a part of the Ph.Dwork carried out by A. Manivannan at Department of PlantBreeding & Genetics, Agricultural College & ResearchInstitute, Madurai, Tamil Nadu, India. The support providedby Indian Council of Agricultural Research (ICAR) byawarding ICAR- Senior Research Fellowship (ICAR-SRF) andalso granting study leave to him is gratefully acknowledged.

REFERENCES

Ahlawat A, Pahuja SK and Dhingra HR. 2013. Studies on interspecifichybridization in Cyamopsis species. African Journal of Agriculture8(27): 3590-3597.

Bhadru D. 2011. Character association and path analysis studies inpigeonpea. Journal of Food Legumes 24(1): 69-71.

Chaubey BK, Yadav, CB, Kumar K and Srivastava RK. 2012. Geneticvariability, character association and path coefficient analyses infaba bean. Journal of Food Legumes 25(4): 348-350.

Dabas BS, Mital SP and Arunachalam V.1982. An evaluation ofgermplasm accessions in guar. Indian Journal of Genetics and PlantBreeding 42: 56-59.

Dass S, Arora ND and Singh VP. 1973. Heritability estimates and geneticadvance for gum and protein content along with seed yield and itscomponents in clusterbean. Journal of Research, CCSHAU, Hisar3(1): 14-19.

Girish MH, Gasti VD, Thammaiah N, Kerutagi MG, Mulge R, ShantappaT and Mastiholi AB. 2012. Genetic divergence studies in clusterbean genotypes (Cyamopsis tetragonoloba (L.) Taub.). KarnatakaJournal of Agricultural Sciences 25: 245-247.

Hingane AJ and Navale PA. 2008. Path analysis in cluster bean. Journalof Maharashtra Agricultural University 33(3): 419-420.

Ibrahim EA, Abdalla AWH and Rahman MEA. 2013. Genotypic andphenotypic correlations between yield and yield components insome guar (Cyamopsis tetragonoloba L.) genotypes under rainfedcondition. African Journal of Agriculture 8(18): 1864-1871.

Morris JB. 2010. Morphological and reproductive characterization ofguar (Cyamopsis tetragonoloba) genetic resources regeneratedin Georgia, USA. Genetic Resources and Crop Evolution 57:985-993.

Rai S. 2010. Genetic variability studies in cluster bean (Cyamopsistetragonoloba L.) genotypes. M.Sc. Agric. Degree, HorticultureDepartment, University of Agricultural Sciences, University Library,UAS, Dharwad, Accession No Th10066.

Saini DD, Singh NP, Chaudhary SPS., Chaudhary OP and Khedar OP.2010. Genetic variability and association of component charactersfor seed yield in cluster bean [Cyamopsis tetragonoloba (L.) Taub.].Journal of Arid Legumes 7(1): 47-51.

Shah SA, Saleem MI, Hussain MA and Ahmad T. 2000. Unidirectionaland Alternate Pathway Impacts of Yield Components on GrainYield of Guar (Cyamopsis tetragonoloba L.). Pakistan Journal ofBiological Sciences, 3: 840-841.

Singh KB and Mehndiratta PD. 1970. Path analysis and selection indicesin cowpea (Vigna sinensis L.). Indian Journal of Genetics and PlantBreeding 30(2):471-475.

Singh J V, Chander S and Punia A. 2002. Studies on characters associationin cluster bean (Cyamopsis tetragonoloba (L.) Taub.). Journal ofPlant Improvement 4(1): 71-74.

Singh NP, Choudhary AK and Choudhary SPS. 2001.Variability andcorrelation studies in some genotypes of clusterbean. Advances inArid Legume Research 2(1): 14-18.


Genetic analysis for quantitative traits in pigeonpea (Cajanus Cajan L. Millsp.)C. K. CHETHANA, P. S. DHARMARAJ, R. LOKESHA1, G. GIRISHA, S. MUNISWAMY, YAMANURA,NIRANJANA KUMAR and D. H. VINAYAKA2

All India Co-ordinated Research Project on Pigeonpea, Agricultural Research Station, Gulbarga-585 101, Karnataka,India; 1Department of Genetics and plant Breeding, UAS, Raichur, Karnataka, India; 2Department of Agronomy,UAS, Raichur, Karnataka, India; E-mail: [email protected](Received : July 11, 2013 ; Accepted : October 29, 2013)

ABSTARCT

Six cytoplasmic-genetic male sterile lines with A2 (Cajanusscarabaeoides) and A4 (Cajanus cajanifolius) cytoplasm weremated with 13 testers in line × tester design during kharif 2010at the Agricultural Research Station, Gulbarga. The resultant78 hybrids were evaluated along with their parents and thestandard check (Maruti) in lattice design with two replicationsduring Kharif 2011. Combining ability analysis evincedpredominance of non-additive gene effects for all the charactersindicating relevance of heterosis breeding for improving yieldattributes in pigeonpea. The lines ICPA-2098. ICPA-2048-4 andGT-625A among female parents (A lines) and M-3(GRG-2009),LRG-41, Asha and TS-3 among the testers were good generalcombiners for seed yield and its direct components. Thirtynine hybrids showed significant positive sca effects for seedyield and its two or more component traits. The crosscombination ICPA-2098 x M-3(GRG-2009), GT-625A x WRP-1,ICPA-2048-4 x Maruti ICPA-2098 x Asha and GT-625A x BSMR-736 exhibited significant SCA effects coupled with higherstandard heterosis for seed yield and its attributes. Theseparental combinations can be potentially utilized in futurebreeding programmes for exploitation of hybrid vigour.

Key words: Combining ability, Heterosis, Hybrids, Lines, Testers

Pigeonpea is one of the major grain pulse crops of thetropics and sub tropics. Endowed with several uniquecharacteristics, it finds an important place in the farmingsystems adopted by small holders farmers in a larger numberof developing countries. Seed protein content in pigeonpea(approximately 21%) compares well with that of other importantgrain pulses. In hybrid breeding programme, success dependsupon the choice of parents and a clear knowledge of geneaction governing specific trait. The selection of suitableparents in any breeding programme is important to effectimprovements in quantitative characters like yield and itscomponents. The estimation of combining ability effectsprovides guidance in selecting best combiners forhybridization programme. Also, the nature and magnitude ofgene action involved in controlling yield and its componenttraits can be identified and quantified. Therefore, the presentinvestigation aimed to analyze combining ability for grain yieldand its component characters in pigeonpea. In this study, anattempt was made to assess the combining ability involving

six CGMS lines and 13 diverse testers crossed in line x testerdesign in pigeonpea.


The experimental material for the present investigationwas generated using six cytoplasmic-genetic male sterile lineswith having the background of Cajanus cajanifolius (A4)(Saxena et al. 2005) and Cajanus scarabaeoides (A2) (Tikkaet al. 1997) cytoplasm lines procured from ICRISAT andthirteen diverse testers selected from ARS, Gulbarga. Thecrosses were made in line x tester mating design during Kharif20010-11. The experiment was conducted at AgriculturalResearch Station, Gulbarga during 2011-12. Each female parent,male parent and 78 hybrids along with standard check Marutiwere grown in a lattice design with two replications. Eachgenotype was sown in two rows plots of 4.0 meter length atthe spacing of 90 x 60 cm. Recommended agronomical practiceswere adopted for optimum crop growth. Observations on fiverandomly selected competitive plants were recorded for daysto 50% flowering, days to maturity, pod bearing length (cm),plant height(cm), Number of primary branches/plant, Numberof secondary branches/plant, Number of pods/plant, seedyield/plant (g), Number of seeds/pod, seed yield/hectare (kg/ha) and 100 seed weight. The data were subjected to analysisof variance (Panse and Sukhatme 1967) and combining abilityanalysis (Kempthorne 1957).


Analysis of variance for combining ability revealed thatmean squares due to testers were significant for all thecharacters studied except for number of secondary branchesand number of seeds per pod while mean squares due to lineswere significant for characters viz., days to 50% flowering,days to maturity, pod bearing length (cm), Number of primarybranches/plant, Number of secondary branches/plant, Numberof pods/plant, Number of seeds/pod, seed yield/hectare (kg/ha) and 100 seed weight. The mean squares due to line x testerinteraction were significant for all characters studied exceptfor number of secondary branches and seed yield/plant.Thereby it is suggested that the variation in hybrids in respectof seed yield was strongly influenced by the testers. Themean squares due to testers were larger in magnitude for most

Chethana et al., : Genetic analysis for quantitative traits in pigeonpea (Cajanus Cajan L. Millsp.) 3 9

of the important yield attributes that those for lines indicatinggreater diversity amongst the testers as compared to lines.The analysis of variance for combining ability showed thatmean squares due to general and specific combining abilityeffects indicating involvement of both additive and non-additive gene action.

The mean sum of squares due to lines × testersinteractions were highly significant for seed yield and itscomponent characters that indicated the importance of scavariance, and consequently the non-additive genetic variationin the inheritance of these characters. This was furthersubstantiated by less than unity ratio of ó2gca/ó2sca. Theseresults were in agreement with the findings of Korgade et al.(2000), Sunil Kumar et al. (2003) and Reddy Sekhar et al. (2004).Vaghela et al.(2009), Sameer Kumar et al. (2009) Bharate et al.(2011) for seed yield/plant and other important yield attributesviz., pod bearing length, number of pods per plant and 100seed weight. Preponderance of non-additive genetic variancesuggested the relevance of heterosis breeding in pigeonpea.

A greater contribution of lines to the performance ofcrosses (Table 1) was observed for days to maturity, podbearing length, primary branches, secondary branches, seedyield/plant. The contribution of testers to performance ofcrosses has found superior for days to 50 % flowering, plantheight, number of pods/plant, number of seeds/pod and 100seed weight. The result of this investigation showed thatmaternal parents contributed more favourable genesresponsible for determining pod bearing length, primarybranches, secondary branches, seed yield/plant. Thecontribution of lines and testers were found equally importantfor the development of the yield and its attributing characters.This showed that average general combiner give high heteroticperformance and could be effectively used in heterosisbreeding programmes.

The nature and magnitude of combining ability effectshelps in identifying superior parents and their utilization inbreeding programme. Character-wise estimation of gca effectsof lines and testers are presented in Table 2. The gca effectsof parents revealed that ICPA-2098. M-3(GRG-2009), LRG-41and TS-3 were good general combiners for seed yield and itsdirect components (shown in Table 2). ICPA-2048-4, GT-625A,M-3 (GRG-2009) and Asha were good general combiner forseed yield/hectare, line ICPA-2098 and tester TAT-9903 fordays to 50 % flowering, line GT-625A and tester iCPL-87 for

days to maturity, line ICPA-2048-4 and tester LRG-41 forprimary and secondary branches/plant, line ICPA-2098 andtester TS-3 for pods/plant, line GT-625A and tester Laxmi forseeds/pod, line ICPA-2098 and tester M-3(GRG-2009) goodgeneral combiner for 100 seed weight.

A perusal of sca effects revealed that 16 crosses fordays to 50% flowering, 12 for days to maturity, three crossesfor pod bearing length, five for plant height, six for secondarybranches, 15 for number of pods/plant, 39 for seed yield/plant,Five for seed yield/hectare and 17 hybrids exhibited significantsca effect for the 100 seed weight (Table 3 )

The top three crosses exhibiting high specific combingability effects are listed in Table 5 along with their Per seperformance, standard heterosis and gca of the parents. Thecross combination ICPA-2098 x BSMR-736 was good specificcombiner for days to 50% flowering and maturity as it wasshowing highly significant negative sca effect. GT-308A xBSMR-736 for pod bearing length, GT-625A x Asha for plantheight, GT-308A x ICPL-87 and ICPA-2092 x LRG-41 for primaryand secondary branches respectively, GT-625A x BSMR-736for number of seeds/pod, ICPA-2098 x M-3 (GRG-2009) fornumber of pods/plant and for seed yield/plant, ICPA-2098 xAsha for Seed yield per hectare and GT-308A x TS-3R for 100seed weight.

The estimates of sca effects revealed that 39 hybridshad significant positive sca effects for seed yield/plant. Amongthese, three best crosses were selected on the basis of per seperformance for ascertaining their association with sca effectsof seed yield per plant and it attributes (Table 4). All the crossesselected on the basis of per se performance possessedsignificantly desirable sca effects for seed yield per plant andother important yield attributing characters viz., days to 50%flowering, number of branches/plant, number of pods/plant,seed yield/hectare and 100 seed weight. All these crossesshowed significant positive sca response to pods per plantand 100 seed weight indicating its direct effect for increasingseed yield.

Out of three crosses showing high mean and significantpositive sca effects for seed yield along with their per seperformance as well as gca effects of parents and theirsignificant response to other characters are presented in Table5. Out of three crosses showing high mean and significantpositive sca effects for grain yield, one crosses involved (ICPA-

Table 1. Percent contribution of lines, testers and line x testers to crossesSource of variation DF DM PBL (cm) PH (cm) PRB SCB NPPP NSPP SYPP (g) SY (kg//ha) SW (g)

Lines 25.02 50.90 31.99 7.90 37.27 46.01 13.87 73.64 8.46 8.87 12.66 Testers 40.69 17.59 26.82 29.77 30.30 11.79 19.29 6.32 16.00 18.21 29.00

Lines x Testers 34.30 31.51 41.18 62.33 32.44 42.20 66.84 20.04 75.54 72.92 58.35

DF= Days to 50 % flowering DM= Days to maturity PBL = Pod bearing length (cm). PH= Plant height (cm).PRB = No. of Primary branches. SCB= No. of Secondary branches NPPP= No. of pods/ plant.NSPP= No. of seeds/pod. SYPP= Seed yield/ plant SY= Seed yield/ha (kg) SW = 100-Seed weight (g)


Table 2. Estimates of gca effects of parents for different characters in pigeonpea

Sl. No. Parents DF DM PBL (cm) PH (cm) PRB SCB NPPP SYPP (g) NSPP SY (kg//ha) SW (g) 1. ICPA-2098 -3.04 ** 0.67 0.72 3.17 0.16 1.28 * 37.87 ** 11.91 ** -0.14 ** -33.48 11.91 ** 2. ICPA-2048-4 3.07 ** 4.51 ** -1.67 4.33 * 1.38 ** 4.71 ** 9.86 -2.55 -0.18 ** 188.99 ** -2.55 3. ICPA-2092 3.15 ** 1.86 ** -0.54 -0.83 0.65 3.19 ** 30.46 ** -1.57 -0.18 ** 32.83 -1.57 4. GT-625A -2.35 ** -10.49 ** 9.31 ** -2.61 -2.48 ** -5.11 ** -21.79 ** 1.14 0.78 ** -81.74 1.14 5. GT-307A -1.24 ** 2.17 ** -3.02 * 0.65 0.97 ** -1.62 * -24.19 ** -5.47 ** -0.14 ** 123.65 * -5.47 ** 6. GT-308A 0.42 1.28 * -4.81 ** -4.72 * -0.68 -2.45 ** -32.21 ** -3.46 * -0.14 ** -230.24 ** -3.46 * Testers

1. Asha 4.20 ** 0.87 -3.33 4.72 0.70 -1.73 4.37 -9.70 ** -0.01 227.14 ** -9.70 ** 2. BSMR-736 3.12 ** 2.78 ** -2.74 5.91 1.68 ** 0.52 -0.3 -9.10 ** -0.01 107.88 -9.10 ** 3. LRG-41 6.20 ** 5.37 ** -8.84 ** 7.12 * 2.42 ** 2.99 ** 19.70 ** 11.46 ** -0.01 35.67 11.46 ** 4. WRP-1 2.28 ** 2.45 ** 8.01 ** 5.61 -0.69 1.83 * 18.70 ** 3.68 -0.01 0.01 3.68 ns 5. TS-3R -2.30 ** -3.05 ** 3.09 -3.37 -0.85 -2.02 * -42.80 ** -7.03 ** 0.15 * -65.64 -7.03 ** 6. M-3 (GRG-2009) -0.47 -1.80 * 3.02 3.3 1.02 2.76 ** -36.80 ** 15.35 ** -0.10 287.14 ** 15.35 ** 7. Laxmi 0.62 3.12 ** 0.17 3.39 0.10 -0.98 8.2 -5.81 * 0.24 ** 36.39 -5.81 * 8. TAT-9903 -5.05 ** -1.72 * 1.08 -6.3 -1.89 ** -1.68 -19.63 ** -5.61 * -0.01 -57.68 -5.61 * 9. PG-12 -2.88 ** -2.55 ** -2.64 -10.56 ** -0.26 0.47 -6.13 -3.93 -0.10 -86.75 -3.93 10. GC-11-39 -1.80 ** -3.05 ** 3.87 * -0.58 0.07 -0.88 -12.30 * 1.84 0.07 -109.07 1.84 11. ICPL-87 -3.38 ** -3.55 ** -3.82 * -10.99 ** -1.42 ** -1.86 * -3.63 -6.92 ** -0.01 -263.61 ** -6.92 ** 12. TS-3 0.37 -1.38 2.29 5.01 -0.4 -0.84 37.87 ** 8.02 ** -0.01 14.91 8.02 ** 13. Maruti -0.88 2.53 ** -0.15 -3.25 -0.49 1.42 4.04 7.75 ** -0.18 * -126.38 7.75 **

*, **- significant at 5 % and 1% respectivelyDF= Days to 50 % flowering DM= Days to maturity PBL = Pod bearing length (cm). PH= Plant height (cm). PRB = No. of Primary branches. SCB=No. of Secondary branches NPPP= No. of pods/ plant. NSPP= No. of seeds/pod. SYPP= Seed yield/ plant SY= Seed yield/ha (kg) SW = 100 seed weight(g)

Table 3. Number of hybrids recorded significant desirable sca effects along with their range sca effects in pigeonpea

Character Range of sca effects No. of F1’ s showing desirable sca effects No. of F1’ s showing significant desirable sca effects

Days to flowering (no.), -6.54 to 8.96 33 16 Days to 80% maturity (no.), -9.67 to 9.14 34 12 Pod bearing length (cm) -17.58 to 12.43 39 03 plant height -18.11 to 20.19 34 05 No. of Primary branches -2.80 to 2.41 41 00 No. of secondary branches -5.86 to 9.15 35 06 No. of pods/ plant -124.39 to 176.18 34 15 Seed yield/ plant (g) -45.01 to 40.86 39 24 Seed yield per hectare (kg/ha) -570.33 to 890.3 37 05 100 Seed weight (g) -1.64 to 1.93 42 17

2098 x M-3(GRG-2009) high × high gca parents and theremaining three crosses (ICPA-2048-4 x Maruti, ICPA-2092 xTAT-9903 and ICPA-2092 x Laxmi) with high x low gca effectsof parents. These results were also in conformity with thoseof Baskaran and Muthian (2007). Better performance ofhybrids involving high x low or low x low general combinersindicated dominance x dominance (epitasis) type of geneaction. The crosses showing high sca effects involving onegood general combiner indicated additive x dominance typegene interaction which exhibit the high heterotic performancefor yield and related traits.

The above results suggested that the crosses havinghigh mean performance, positive sca effects for seed yield

and their significant response to other related traits hadnecessarily involved both or at least one parent as goodcombiner which could be commercially exploited for heterosisby taking advantage of high degree of natural out crossing inpigeon pea.

ACKNOWLEDGMENTS

Authors are thankful to National Food Security Mission,New Delhi and ICRISAT for provided seed materials for thepresent study and also as funding agency for the project.Also very much thankful to Dr. K. B. Saxena for criticalevaluation of manuscript.

Chethana et al., : Genetic analysis for quantitative traits in pigeonpea (Cajanus Cajan L. Millsp.) 4 1

REFERENCES

Baskaran K and Muthiah AR. 2007. Combining ability stidies inpigeonpea. Legume Research 30: 67-69.

Bharate BS, Wadikar PB. and Ghodke MK. 2011. Studies on combiningability for yield and its components in pigeonpea. Journal of FoodLegumes 24(2): 148-149.

Kempthorne O. 1957. An Introduction to Genetic Statistics. JohnWiley and Sons Inc., New York; Chapman and Hall, London. pp.545.

Khorgade PW, Wankhade RR. and Wanjari KB. 2000. Combining abilityanalysis in pigeonpea using male sterile lines. Indian JournalAgricultural Research 34: 112-116.

Panse VG. and Sukhatme PV. 1961. Statistical Methods for AgriculturalWorkers, ICAR Publication, New Delhi. pp. 359.

Sameer Kumar CV. Sreelaxmi C H. and Kishore Verma, P. 2009. Studieson Combining ability and heterosis in pigeonpea [Cajanus cajan(L.) Millsp.]. Legume Research 32(2): 92-97.

Saxena KB, Kumar RV, Dalvi VA, Mallikarjuna N, Gowda CLL, Singh

Table 4. Comparison of top three best crosses selected on the basis of specific combining ability effects for different characters

GCA effect of parents Characters Crosses SCA

effects P1 P2 Standard heterosis Per se Significant sca effects for

other traits ICPA-2098 x BSMR-736 -6.54 -3.04 3.12 -10.77 91.0 DTM. NPPP ICPA-2092 x PG-12 -6.23 3.15 -2.88 -7.69 91.5 DTM. PH. SYPP. SY. TW Days to 50%

flowering ICPA-2098 x Asha -5.62 -3.04 4.20 -7.69 93.0 DTM. NPPP ICPA-2098 x BSMR-736 -9.67 0.67 2.78 -2.51 143.5 DTM. SYPH ICPA-2092 x TS-3 -9.19 1.86 -1.38 -2.15 141.0 DF. SYPH Days to maturity GT-308A x M-3 (GRG-2009) -8.20 1.28 -1.80 -1.79 141.0 TW GT-308A xBSMR-736 12.43 -4.81 -2.74 51.39 60.8 DTM GT-308A x Maruthi 9.90 -4.81 -0.15 44.53 61.0 - Pod bearing

length (cm) GT-625A x LRG-41 9.86 9.31 -8.84 42.74 66.3 SYPH GT-625A x Asha 20.19 -2.61 4.72 16.89 202.5 DTF. PBL. SW. ICPA-2092 x PG-12 19.19 -0.83 -10.56 15.55 188.0 SW Plant height(cm) ICPA-2092 x GC-11-39 18.56 -0.83 -0.58 14.69 197.3 DTF. DTM. SYPP. SYPH. SW. GT-308A x ICPL-87 2.41 -0.68 -1.42 28.27 13.0 DTF. DTM. SYPP. SW. GT-307A x GC-11-39 2.26 0.97 0.07 25.09 16.0 DTF. NPPP. SYPP. SW. No .of Primary

branches ICPA-2092 x TAT-9903 2.24 0.65 -1.89 23.67 14.0 SB ICPA-2092 x LRG-41 9.15 3.19 2.99 36.26 31.0 NPPP.SYPP. ICPA-2098 x TS-3R 7.57 1.28 -2.02 -15.82 22.0 NPPP.

No. of Secondary branches GT-625A x Maruthi 7.03 -5.11 1.42 21.98 19.0 DTF. NPPP. SYPP. SYPH.

ICPA-2098 x M-3 (GRG-2009) 176.18 37.87 -36.80 60.63 585.0 NPPP.SYPP.SYPH.SW. ICPA-2048-4 x Maruthi 129.02 9.86 4.04 29.75 473.0 SB Number of

pods/plant GT-307A x ICPL-87 104.99 -24.19 -3.63 28.52 347.0 NPPP.SYPP. GT-625A x BSMR-736 0.25 0.78 -0.18 11.11 6.0 SY GT-625A x TS-3R 0.88 0.78 0.15 33.33 6.0 - No. seeds/plant GT-625A x Laxmi 0.30 0.78 0.24 22.27 6.0 - ICPA-2098 x M-3(GRG-2009) 40.86 11.91 15.35 80.85 170.0 DTF.NPPP.SYPH. GT-625A x WRP-1 29.31 1.14 3.68 59.57 136.0 NPPP Seed yield/ plant

(g) ICPA-2048-4 x Maruthi 27.92 -2.55 7.75 44.68 135.0 NPPP.SYPH.SW. ICPA-2098 x Asha 890.33 -33.48 227.14 46.38 2464.0 DTF.DTM. GT-625A x BSMR-736 540.07 -81.74 107.88 16.21 1947.0 PH. SYPP. SW. Seed yield

(kg/ha) ICPA-2048-4 x Maruthi 478.61 188.99 -126.38 14.7 1922.0 NPPP. SYPP.SW. GT-308A x TS-3R 1.93 -3.46 -7.03 47.43 13.5 - GT-308A x PG-12 1.8 -3.46 -3.93 38.34 12.1 - 100 seed weight

(g) GT-308A x LRG-41 1.33 -3.46 11.46 36.97 10.9 -

BB, Tikka SBS, Wanjari KB, Pandet LB, Paralkar LM, PatelMK, Shiying B, and Xuxiao Z. 2005. Hybrid breeding in grainlegumes – a success story of pigeonpea. In: Khairwal MC, Jain HK(eds) Proceedings of the international food legumes researchconference, NewDelhi, India

Sekhar M.R. Singh S.P. Mehra R.B. and Govil J.N. 2004. Combiningability and heterosis in early maturing pigeonpea [Cajanus cajan(L.) Millsp.] hybrids. Indian Journal of Genetics and Plant Breeding64 (3): 212 - 216

Sunilkumar, Lohithaswa HC. Dharmaraj PS. 2003. Combining abilityanalysis for grain yield, protein content and other quantitativetraits in pigeonpea. J. Maharashtra Agric. Univ. 28(2): 141-144.

Tikka SBS, Parmar LD and Chuahan RM. 1997. First record ofcytoplasmic genic male sterility system in pigeonpea (Cajanuscajan (L.) Millsp.) through wide hybridization. Gujarat AgriculturalUniversity. Research Journal 22:160-162.

Vaghela KO. Desai RT. Nizama J.R. Patel JD. and Sharma, V. 2009.Combining ability analysis in pigeonpea. Legume Research 32 (4):274-277.


Genetic variabilty and association studies in cowpea (Vigna unguiculata L. walp.)HASAN KHAN, K. P. VISHWANATHA and H.C. SOWMYA

Department of Genetics and Plant Breeding, College of Agriculture, GKVK, UAS, Bengaluru-65, Karnataka, India;E-mail: [email protected](Received : February 07, 2013 ; Accepted : December 02,2013)

ABSTRACT

Profound knowledge on variability of genetic material wouldbe of immense importance to any plant breeding programs. Inthe present study two segregating populations viz., C-152 x V-16 and C-152 x HC-03-02 were taken to assess the PCV, GCVand GAM, etc. The segregating populations of C-152 x V-16cross showed high PCV estimates for plant height, number ofbranches per plant, number of seeds per pod, seed yield perplant and number of pods per plant. But GCV estimate washigh for the traits like number of pods per plant and seed yieldper plant. Heritability in broad sense was high for test weight,number of branches per plant and seed yield. The GAMestimates were high for all the traits studied except number ofbranches per plant. Similarly, in another cross C-152 x HC-03-02, high PCV values were estimated for plant height, numberof branches per plant, seeds per pod, seed yield and number ofpods per plant. Whereas, GCV and heritability were high forplant height and test weight and GAM was high for all thetraits studied. Number of pods per plant and number of seedsper pod had significant positive correlation among themselvesin both the crosses studied. It may be inferred that these traitshave strong influence on seed yield per plant. Since, thecharacters are inter-correlated among themselves; selectionfor any one of the traits will result in the improvement of othertrait thereby, resulting in increased seed yield.

Key words: Biometrical traits, Cowpea, Heritability, Geneticadvance, Variability

Variability is the key factor for any selection program,which can be generated through various ways. To achieve orcreate variability, addition of some more diverse genotypeswith the available collection is necessary or creation of newvariability by other means is very much needed. Since theproductivity of cowpea is very low due to lack of high yieldingvarieties with resistance to biotic and a biotic stresses werethe major hindrance in achieving potential yield of cowpea.The morphological observations recorded in the field usuallywill be the sum total of genotypic as well as environmentaleffects. Hence, the diversity obtained from the field datashould be verified to ensure that the variability present is atgenotypic level.

Estimation of genetic variability parameters is theforemost step to be adopted in the source population if thebreeding program is aimed at improving economicallyimportant traits. The success of any crop improvement

program depends on the ability of the breeder to define andassemble the required genetic variability and select for yieldindirectly through yield associated and highly heritablecharacters after eliminating the environmental component ofphenotypic variation (Mather and Jinks, 1983).


The material used for the study includes three parentallines viz. C-152 (agronomically superior but susceptible forboth the diseases CpMV and BLB), V-16 (resistant to bacterialleaf blight disease) and HC-03-02 (resistant to cowpea mosaicvirus disease). They were selected based on the results ofevaluation under field conditions and in glass house screening.The experiment was carried out in summer; 2010.The parentallines were sown in the field for the purpose of hybridization.In case of parental lines five and in both F2 populations 250plants were selected randomly and observations on ninequantitative traits (days 50 per cent flowering, days tophysiological maturity, plant height, number of branches perplant, number of pods per plant, pod length, number of seedsper pod, test weight and seed yield per plant) were recordedon these plants.

The two F1 hybrids were sown along with their parentsduring kharif 2010, and true crosses were confirmed based onthe characters of male parents in F1. Dominant morphologicalcharacters viz., pigmentation on peduncle in V-16 andspreading growth habit of HC-03-02, which were not presenton female parent C-152 were used to identify the true F1s ofrespective crosses in F1 generation.

Seeds from true F1 plants from both the crosses werecollected and used to raise about 250 F2 individuals in boththe crosses during Rabi 2010. The morphologicalobservations and disease scoring for both diseases inrespective crosses were recorded. Seeds obtained from eachindividual F2 plants were collected and forwarded to F3generation.

Genetic variability parameter viz., mean, variance(Cochran and Cox, 1957), phenotypic coefficient of variation(PCV) and genotypic coefficient of variation (GCV) (Burton,1953), heritability (h2) (Hanson et al. 1956) and Genetic advance(GA) (Johnson et al. 1955) and correlation (Al-Jibouri et al.1958) among characters were calculated by following thestandard procedures with the help of MSTATC, Statistica 2(Statsoft Inc. 1999) and Genres software’s.

Khan et al., : Genetic variabilty and association studies in cowpea (Vigna unguiculata L. walp.) 4 3


The improvement of any character in a population isdepends upon the variability existing in the population. Hence,formulation of objectives in breeding programme should beessentially accompanied with the assessment of existingvariability in the segregating populations. In addition to thevariability analysis, correlation coefficient helps the breedersin determining the direction of selection and number ofcharacters to be considered in improving the yield and qualityattributing traits. The variability quantified by range includesinfluence of environment and genotype x environmentalcomponents of variation. Since, all these variations are notheritable it is appropriate to partition the phenotype variationinto heritable (genetic) and non-heritable (environmental)components, and thus, true breeding value of the genotypecan be precisely estimated by separating genetic variancefrom environmental variance. In this direction, the componentsof variance such as PCV and GCV, heritability and predictedgenetic advance as per cent mean were computed for sixquantitative characters studied in F2 population of crosses C-152 x V-16 (Table 1) and C-152 x HC-03-02 (Table 2).

Evaluation of F2 segregating populations for sixbiometrical traits exhibited wide range of variation for all thetraits studied in both the crosses. This variation indicatedthat there is substantial scope for selection of genotypes forthese traits. Rangaiah and Nehru (1998) also reported highrange of variation for above mentioned characters in F2segregating populations of two crosses of cowpea, which isin confirmity with the results of present investigation.

In the F2 segregating population of the cross C-152 xV-16 (Table 1) high phenotypic coefficient of variation (PCV)and genotypic coefficient of variation (GCV) estimates were

recorded for number of pods per plant and seed yield perplant. This result is in conformity with findings of Gowda etal. (1991) and Hadpad (2001). This indicates greater scope forselection to improve upon these characters in the crossesstudied. Whereas, high PCV and moderate GCV estimates wererecorded for traits viz., plant height, number of seeds per podand in case of number of branches per plant, high PCV andlow GCV were recorded. While, for the parameter test weightmoderate PCV and GCV were recorded. Similar results wereobtained by Rangaiah and Nehru (1998) and Hadpad (2001).In the F2 segregating population of the cross C-152 x HC-03-02, (Table 2) high PCV and GCV were estimated for the traitplant height. Similar results were obtained by Suma Biradar etal. (2001), Mehta and Zavari (1999). Whereas high PCV andmoderate GCV were observed for the traits viz., number ofbranches per plant, number of pods per plant, number of seedsper pod. These results are in conformity with earlier findingsof Gowda et al. (1991). While, moderate PCV and GCV wereestimated in test weight and high PCV and low GCV wasobtained in the parameter seed yield per plant.

Genotypic coefficient of variation (GCV) would be moreuseful for the assessment of variability than the phenotypiccoefficient of variation (PCV) since, it depends upon theheritable portion of the total variability (Allard, 1970). Higherthe proportion of GCV more will be the chance for exploitationof that particular character. Many practical decisions inbreeding programs are based on the magnitude of heritablevariation. In comparing PCV and GCV estimates it was evidentthat the influence of environment on the expression of mostof the characters was low indicating the greater role of geneticfactors causing variability in these characters. Theseobservations indicated ample scope for improvement of theabove traits by selection from their phenotypic values.

Table 2: Estimates of mean and genetic variability parameters for six characters in F2 generation of the cross C-152 x HC-03-02 ofcowpea

Table 1: Estimates of mean and genetic variability parameters for six characters in F2 generation of the cross C-152 x V-16 of cowpea

S.No Characters Mean Range PCV (%) GCV (%) h2 (%) GAM 1 Plant height (cm) 57.27 26.5-88 23.67 11.01 46.51 22.62 2 Number of pods per plant 17.99 4-55 52.49 28.36 54.02 58.41 3 Number of seeds per pod 11.12 4-16 22.82 19.92 80.25 41.04 4 Number of branches per plant 5.40 6-11 33.12 8.8 26.57 18.13 5 Test weight (g) 16.81 7.5-21 19.20 18.99 98.90 39.10 6 Seed yield per plant (g) 34.16 7.28-138.6 48.83 37.87 77.55 78.01

S.No Characters Mean Range PCV (%) GCV (%) h2 (%) GAM

1 Plant height (cm) 69.28 46-100.5 21.89 20.19 92.233 41.6

2 Number of pods per plant 18.28 12-28 27.82 13.81 49.64 28.45

3 Number of seeds per pod 13.28 10-17 21.72 11.37 52.34 23.41

4 Number of branches per plant 4.14 3-7 34.75 18.71 53.84 38.54

5 Test weight (g) 16.42 15-18 11.4 11.14 97.71 22.96

6 Seed yield per plant (g) 44.72 19.2-194.94 31.22 5.78 18.51 20.53


Table 3: Simple correlations among seed yield and its attributing characters in F2 generation of the cross C-152 x V-16 (C1) andC-152 x HC-03-02 (C2) of cowpea

* & ** indicates significant at 5 %and 1 % level respectivelyX1 - Plant height (cm) X4 - Number of branches per plantX2 - Number of pods per plant X5 - Test weight (g)X3 - Number of seeds per pod X6 - Seed yield per plant (g)

In the F2 segregating population of the cross C-152 x V-16 (Table 1), heritability (broad sense) was high for the traitsviz., test weight, number of seeds per pod and seed yield perplant. While, moderate heritability observed in the traits likeplant height, number of pods per plant and number of branchesper plant. Similarly in the F2 segregating population of thecross C-152 x HC-03-02 (Table 2), high heritability wasestimated in test weight and plant height. While, the traitsviz., number of pods per plant, number of seeds per pod andnumber of branches per plant recorded moderate heritability.The trait seed yield per plant recorded low heritability.

High heritability coupled with high GAM for the traitslike number of seeds per pod, test weight and seed yield perplant was observed in the F2 population of cross C-152 x V-16.Similar results were earlier obtained by Rangaiah and Nehru(1998), Gowda et al. (1991). Moderate heritability and highGAM were recorded for plant height and number of pods perplant. These results were in accordance with work of Hadpad(2001) and Mehta and Zaveri (1999). Moderate heritabilityand GAM recorded for the trait number of branches per plant.High heritability with high GAM was observed for plant heightand test weight in the F2 population of the cross C-152 x HC-03-02, whereas moderate heritability and high GAM wasobserved for number of pods per plant, number of seeds perpod and number of branches per plant. Low heritability andhigh GAM were observed for seeds yield per plant. Similarresults were reported earlier by Hadpad (2001).

High heritability coupled with high genetic advance asper cent mean for the above said traits indicated that thesetraits are under the control of additive gene action anddirectional phenotypic selection for these traits in geneticallydiverse genotypes could be effective for desired geneticimprovement. These traits could further be improved byapplying pedigree selection. Moderate heritability coupledwith moderate genetic advance which is being observed in

the present study indicated that considerable influence ofenvironment apart from non-additive gene action. Therefore,simple selection may not be effective in improvement of thesetraits. The straight selection on the basis of phenotypicperformance alone would not, therefore be rewarding in theimprovement of these traits indicating non-additive geneaction.

The quantitative traits viz., number of pods per plant,number of seeds per pod and test weight showed strongrelationship with seed yield per plant in the cross C 152 x HC03 02 (Table 3). In the cross C 152 x V 16 (Table 3), number ofpods per plant and number of seed per pod showed strongrelationship with seed yield. Therefore, it can be suggestedthat individual plant selections may be practiced for plantswith above mentioned characters which ultimately lead toimprovement in seed yield in the later generations. Similar,kind of results were earlier reported by Reddy and Singh (1994),Gill et al., (1995) and Anbumalarmathi et al., (2005). However,plant height and number of branches per plant in the cross C152 x V 16 recorded negative non significant relationship withseed yield per plant, indicating selection for these traits wouldnot improve seed yield in the segregating generations.

ACKNOWLEDGEMENTS

AICRP on Arid Legumes, ZARS, GKVK, Bangaloreprovided the cowpea planting materials.

REFERENCES

Al-jibouri HA, Miller PA, Robinson HF.1958. Genotypic andenvironmental variances in an upland cotton crop of interspecificorigin. Agronomy Journal 50: 633-634

Allard RW. 1970. Principles of Plant Breeding. John Wiley and SonsInc., Newyork and London, p.485.

Anbumalarmathi J, Sheeba A and Deepasankar P. 2005. Genetic variabilityand interrelationship studies in cowpea (Vigna unguiculata L.).Research on Crops 6(3): 517-519.

X1 X2 X3 X4 X5 X6 X1 C1 1.000 -0.003 -0.040 -0.214 0.001 -0.033 C2 1.000 0.116 -0.042 -0.082 -0.088 0.049 X2 C1 1.000 0.029 0.028 -0.124 0.863* C2 1.000 0.105 -1.017 0.051 0.701* X3 C1 1.000 -0.086 0.071 0.395* C2 1.000 0.050 -0.017 0.674* X4 C1 1.000 -0.098 -0.035 C2 1.000 0.113 0.050 X5 C1 1.000 0.156 C2 1.000 0.350* X6 C1 1.000 C2 1.000

Khan et al., : Genetic variabilty and association studies in cowpea (Vigna unguiculata L. walp.) 4 5

Burton GW and De Vane E. H. 1953. Estimating heritability in tallFescue (Festuca arundinaceae) from replicated clonal material.Agronomy Journal 45: 478-481.

Cochran WG and Cox GM. 1957. Experimental Designs. John Wileyand Sons, Inc. 611p.New York.

Gill JS, Verma MM, Gumber RK and Singh B. 1995. Character associationin ungbean lines derived from three intervarietal crosses in mungbean.Crop Improvement 22: 255-260.

Gowda TH, Hiremath SR and Salimath PM. 1991. Estimation of geneticparameters in intervarietal crosses of cowpea (Vigna unguiculataL.) and their implication in selection. Legume Research 14: 15-19.

Hadpad SB. 2001. Strategies for increasing variability for yield and itsattributes in cowpea. M.Sc. (Agri.) Thesis, Univ. Agric. Sci.,Dharwad.

Hanson CH, Robinson HF and Comstock RE. 1956. Biometrical studiesof yield in segregating population of Korean Lespedeza. AgronomyJournal 48: 268-272.

Johanson HW, Robinson HF and Comstock RE. 1955. Estimates ofgenetic and environmental variability in soybeans. AgronomyJournal 47: 314-308.

Mehta DR and Zaveri PP. 1999. Genetic variability and associationanalysis in F5 generation resulted from 3 selection scheme in cowpea.Journal of Maharashtra Agriculture University 23: 238-240.

Mather and Jinks.1983. Biometrical Genetics. (3 rd ed.Chapman andHall) London. p.396.

Rangaiah S and Nehru SD. 1998. Genetic variability, correlation andpath analysis in cowpea. Karnataka Journal of Agriculture Sciences11: 927-932.

Reddy KR and Singh DP. 1994. Inheritance of resistance to mungbeanyellow mosaic virus. Madras Agriculture Journal 80: 199-200.

Suma Biradar. 2001. Inheritance of seed size in cowpea (Vignaunguiculata L.) M.Sc. (Agri.) Thesis, Univ. Agric. Sci., Dharwad.


Yield and yield attributes of hybrid pigeonpea (ICPH 2671) grown for seed purposeas influenced by plant density and irrigationM.G. MULA, K.B. SAXENA, A. RATHORE and R.V. KUMAR

International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru – 502 324, Andhra Pradesh,India; Email: [email protected](Received : September 18, 2012; Accepted: August 01, 2013)

ABSTRACT

The field experiment was conducted during 2009-10 and 2010-11 cropping seasons in Vertisols at Patancheru, AP, India toevaluate the agronomic viability for large-scale seedsproduction of hybrid pigeonpea (ICPH 2671) from a cytoplasmicmale-sterile (CMS) line ICPA 2043. The experimentaltreatments include two row ratio (4 male sterile:1 male fertileand 3 male-sterile:1 male fertile), two row spacings (150 cmand 75 cm), two intra row spacing’s (50 cm and 30 cm), and twoirrigation frequencies (14 and 21 days intervals). Resultsrevealed that no significant difference was noticed during bothyears of study on the interactive effects of row ratio + spacing,row ratio + irrigation, spacing + irrigation, and row ratio +spacing + irrigation. Individual plants at wider spacing showedsignificant positive effect on various agronomic traits but thisdid not translate into increased seed yield due to plant density.However, there was a significant difference on the effect of rowratio and spacing. Row ratio of 4:1 produced the highest seedyield (1306 kg/ha) due to more number of rows of male sterilelines than in 3:1. Aplant spacing of 75 cm x 30 cm provided thehighest seed yield (3255 kg/ha) as compared to the othertreatments.The study also revealed that the application of 2 to3 irrigations during flower initiation till pod development isrequired to develop a good seed yield.

Keywords: Cytoplasmic male-sterility, Pigeonpea , Row ratio,Spacing, Seed production

Pigeonpea [Cajanus cajan (L.) Mills.] is an importantgrain legume in the semi-arid tropics of Asia and Africa due toits high protein (20-22%) content. India is the largest producerand consumer of pigeonpea because it plays an importantrole in food security, balanced diet and alleviation of poverty(Rao et al. 2002). Globally pigeonpea occupies 4.6 m ha area in21 countries with annual production of 3.4 million tons and aproductivity of 893 kg/ha (Mula and Saxena 2010). In India,pigeonpea covers 3.5m ha area with 2.4 million tons productionhaving a low productivity of 685 kg/ha. The productivity ofpigeonpea has remained low and stagnant over the last fewdecades thus this prompted scientists to breed hybridpigeonpea.

The first hybrid pigeonpea developed by ICRISAT,ICPH 8, could not make any impact due to the genetic controlof male-sterility (GMS) whereby its hybrid seed productionbecame tedious and expensive and was not accepted bycommercial hybrid seed producers (Reddy et al. 1978; Saxena

et al 1992). However, hybrid pigeonpea has shown to increaseyield of more than 40% as compared to its check variety Asha(Saxena and Nadarajan 2010). In this regard, the cytoplasmicmale-sterility (CMS) developed by ICRISAT was utilized forthe extensive seed production of hybrids and their femaleparents (Saxena et al. 2005). Saxena et al. (2006) indicated thatthe successful hybrid seed production in pigeonpea dependson the efficacy of mass pollen transfer from restorer line (R-line) to male-sterile line (A-line) by pollinators, mainly bees.

Moreover, the variation between agro-climaticconditions and irrigation among different locations and withinlocation likewise affects the growth and development ofpigeonpea (Ahlawat et al. 2005). Agronomic activities areregarded as important factor in increasing crop productionsuch as soil moisture, light intensity, and inter- and intra-rowspacing influence pigeonpeas growth and development (Sinhaet al. 1988). Therefore, this study was initiated to identify theappropriate row ratio, plant spacing and irrigation frequencyfor optimizing seed yield of ICPH 2671.


The experimental material consisted of two parental linesthat included female-sterile (ICPA 2043) and its male-fertilerestorer line (ICPR 2671) sown in an isolated area of Vertisolsduring 2009-10 (Year 1) and 2010-11 (Year 2) cropping seasonat Patancheru, Andhra Pradesh, India.

Two row ratio proportion of 4 female-sterile to 1 male-fertile (4:1) and 3 female-sterile to 1 male-fertile (3:1) were used.Within this row ratio, the female-sterile lines have two rowspacings (75 cm and 150cm) and two plant to plant spacings(30 cm and 50cm). The restorer line was sown at plant-to-plantspacing of 30 cm. The row length of each treatment was eightmeters. In 2009 and 2010, a total 997.59 mm and 1206.29 mmannual rainfall was observed, respectively. For both croppingseasons, less rainfall in the month of November at 44.2 mmand 17.9 mm correspondingly was experienced duringpigeonpeas flower initiation and podding phase.Two irrigationtreatments, wherein, three irrigation (every 14 days interval)and two irrigation (every 21 days intervals) at field capacity of50 mm/irrigation during flower initiation to pod developmentwere applied. Irrigation was not required when the pods areat physiological maturity. The different treatmentscombinations were laid out in Randomized Complete Block

Mula et al., : Yield and yield attributes of hybrid pigeonpea (ICPH 2671) grown for seed purpose as influenced by plant 4 7

Design (RCBD) with two replications. The recommendedfertilizer dose of 100 kg/ha di-ammonium phosphate (18-46-00) was thoroughly applied and normal cultural practices werefollowed uniformly to raise a good crop for all the experimentalunits.

Five plants were selected randomly in each plot anddata were recorded on height at 50% flowering (cm), diameterof main stem (cm), weight of dry biomass (kg), number ofprimary branches, number of secondary branches, pods perplant, seeds per pod, 100 seed weight (g) and seed yield perplant (g/plant). The total seed yield (kg/ha) was computed onplot basis. Analysis of variance using the split plot designwas conducted to study the effect of row ratio, spacing,irrigation and their interaction to identify the best treatmentcombination for the optimum seed production of pigeonpeahybrid ICPH 2671.


Row ratio effect: No growth and yield contributing traitswere significantly influenced by the row ratio in the first yearof the study however, the major effect of row ratio (4:1 and3:1) was found significant (P<0.05) on the weight of biomass,yield/plant and seed yield/hectare of ICPA 2043 in the secondyear (Table 1).The biomass in 3:1 is significantly more (0.26kg/plant) than in 4:1 row ratio (Table 2) which confirms to thefindings of Mula et al. (2011) where 3:1 row ratio registeredthe highest biomass weight however, this has not influencedthe yield traits of ICPA 2043 due to population density whichwas more in 4:1. The maximum yield/plant (78.02 g) and yield/hectare (1306 kg) were recorded in the 4:1 row ratio than the3:1 (Table 4).These results supported the findings of Saxena(2006) and Mula et al. (2010a) where 4:1 was observed as thebest row ratio of male:female parent lines for producingoptimum seed yield of pigeonpea.

Irrigation effect: During the two years research, onlythe branches and yield/plant of ICPA 2043 in year 1 weresignificantly (P<0.05) affected by irrigation. Irrigationfrequency at 14 days intervals during flower initiation till poddevelopment recorded the highest mean number of branches(47) (Table 1) and yield/plant (129.72 g) (Table 4). However,these findings did not influenced the seed yield/hectare ofICPA 2043 for both irrigation frequencies which correspondsto the findings of Reddy et al. (1984) and Kumar Rao et al.(1992) where no major interactions were observed betweenthe two irrigation levels and plant densities on the total seedyield.

Spacing effect: The effect of spacing on the growthand development of ICPA 2043 varies from year to year asreflected in this two years study. Spacing significantly (P<0.05)influenced the stem diameter, biomass weight, branches, pods/plant, yield/plant, and total seed yield/hectare of ICPA 2043 inyear one (Table 1). In year two, height at 50% flowering, pods/

Graph 1. Seeds/pod as influenced by row ratio andirrigation inYear 1

Graph 2. Diameter of Stem as influenced by spacing andirrigation in Year 2.

Graph 3. Yield/plant as influenced by spacing andirrigation in Year 2


plant, seeds/pod, weight of 100 seeds, and yield/plant weresignificantly affected by plant spacing. In 2009-10 croppingseason, the research revealed that planting distance 150 cm x50 cm gave the highest mean diameter of stem at 2.49 cm,weight of biomass at 1 kg/plant (Table 2), pods/plant at 752(Table 2), yield/plant at 149.07 g and yield/ha of 1432.1 kg(Table 4) while planting distance 75 cm x 30 cm produced thehighest number of branches at 47/plant (Table 2).The yieldobtained in wider spacing was attributed to the yield traits(pods/plant and yield/plant) which is in conformity to thefindings of Venkataratnam et al. (1984).

In 2010-11 cropping season, planting distance 150 cm x50 cm generated the highest mean height of 228 cm at 50%flowering, weight of dry biomass of 0.25 kg/plant (Table 2),359 pods/plant, 3.32 seeds/pod, 14.55 g of 100 seed weight(Table 2), and yield/plant of 98.61 g (Table 2). However, widerspacing has not influenced the increased in seed yield ofICPA 2043 which confirms to the findings of Sinha et al. 1988and Kumar et al. 2001.

Interaction effect of row ratio and spacing: There wereno significant (P<0.05) interactive effect of row ratio andspacing in the two year study of ICPA 2043 except for yield/plant in 2010-11 cropping season (Table 1). Row ratio 4:1 withplant spacing of 150 cm x 50 cm produced the highest meanyield/plant at 118.9 g (Table 2), but this factor did not influencedthe total seed yield/ha of ICPA 2043 where widely spacedpigeonpea resulted in a gradual decline in yield of pigeonpea(Wilsie 1935 and Abrams and Julia 1973).

Interaction effect of row ratio with irrigation: The datain Table 1 revealed that there were no major significant (P<0.05)difference observed for the agronomic and yield and yieldtraits of ICPA 2043 in the two year study except for number ofbranches (Year 2) and number of seeds/pod (Year 1). Rowratio 3:1 with irrigation frequency of 21 days interval duringflower initiation till pod development provided the highestmean number of 34 branches/plant (Table 2) while in Year 1,the highest number of 4.25 seeds/pod (Table 2) were observedin the 4:1 row ratio with 21 days irrigation interval which wasclearly plotted in Graph 1. This result are in accordance withthe findings of Lawn and Troedson (1990) and Kumar Rao etal. (1992) where no major interactions were seen between theirrigations and spatial arrangements on the various agronomicand yield traits of pigeonpea.

Interaction effect of spacing with irrigation: Theagronomic yield and yield traits of ICPA 2043 were notsignificantly (P<0.05) influenced by the interactive effects ofspacing and irrigation during 2009-10 cropping season (Table1). However, in 2010-11 cropping season, the interactive effectof spacing and irrigation were found significantly differentfor diameter of main stem (cm) and yield/plant (g) (Table 1).Results showed that in 2010-11 trial, spacing of 150 cm x 50cmwith irrigation frequency at 21 days interval provided thehighest diameter of stem (2.66 cm) (Graph 2 and Table 2) andyield/plant of 111.60 g (Graph 3 and Table 2) however, thevegetative and yield characters did not gain any advantageto the total seed yield as compared with closer spacing, theresults are in conformity with Sekhon et al. (1996).

Table 1. Effect and interactive effect of row ratio, spacing and irrigation on the agronomic and yield traits of ICPH 2671 at 5% levelof significance

Agronomic traits Yield traits Yield Height at 50%

flowering (cm) Stem diameter

(cm) Biomass

(kg) Branches

(no.) Pods/plant

(no.) Seed/pod

(no.) Weight of 100

seeds (g) Plant (g) Hectare (kg)

Treatment effect

Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Y1 Y2 Effect of Row ratio 0.63 0.31 0.11 0.06 0.63 0.02 0.21 0.41 0.54 0.20 0.45 0.07 0.06 0.26 0.57 0.03 0.63 0.05 Effect of irrigation 0.61 0.44 0.51 0.71 0.64 0.37 0.03 0.06 0.74 0.90 0.07 0.79 0.25 0.29 0.03 0.61 0.29 0.97 Effect of spacing 0.28 0.01 0.0002 0.19 0.0006 0.08 0.01 0.11 0.005 0.01 0.33 0.0006 0.87 0.02 0.002 <.0001 <.0001 0.10 Interactive effect of row ratio with spacing

0.47 0.52 0.24 0.48 0.29 0.51 0.32 0.40 0.96 0.17 0.50 0.60 0.60 0.75 0.58 0.005 0.75 0.63

Interactive effect of row ratio with irrigation

0.67 0.95 0.91 0.61 0.74 0.84 0.23 0.03 0.51 0.22 0.03 0.38 0.90 0.35 0.13 0.72 0.96 0.66

Interactive effect of spacing with irrigation

0.45 0.13 0.052 0.01 0.19 0.83 0.12 0.56 0.60 0.68 0.53 0.70 0.92 0.52 0.30 0.005 0.32 0.39

Interactive effect of row ratio, spacing and irrigation

0.80 0.95 0.78 0.54 0.18 0.98 0.48 0.41 0.51 0.97 0.86 0.26 0.92 0.29 0.37 0.51 0.42 0.61

Mula et al., : Yield and yield attributes of hybrid pigeonpea (ICPH 2671) grown for seed purpose as influenced by plant 4 9

Table 2. Mean attributes of ICPA 2043 as influenced by the direct and interactive effects of row ratio, spacing and irrigation.

Note: Mean data provided are only those with significant difference (P<0.05) revealed in Table 1.

Year 1 Year 2 Traits Factor Treatment Mean Factor Treatment Mean

150 x 50 228 150 x 30 226.13 75 x 50 223.10

Height at 50 % Flowering (cm)

Effect of spacing

75 X 30 216.26 150 x 50 2.49 150 x 50 + every 21 days 2.66 150 x 30 2.26 150 x 30 + every 21 days 2.49 75 x 50 2.19 75 x 50 + every 14 days 2.33

Effect of spacing

75 X 30 2.00 75 x 30 + every 14 days 2.33 150 x 30 + every 14 days 2.21 150 x 50 + every 14 days 2.18 75 x 30 + every 21 days 2.18

Stem Diameter (cm)

Interactive effect of spacing and

irrigation

75 x 50 + every 21 days 2.10 150 x 50 1.00 3:1 0.26 150 x 30 0.88

Effect of row ratio 4:1 0.20

75 x 50 0.66 150 x 50 0.25

Effect of spacing

75 X 30 0.60 150 x 30 0.24 75 x 50 0.23

Biomass (kg)

Effect of spacing

75 X 30 0.21 Every 21 days 42 3:1 + every 21 days 34 Effect of

irrigation Every 14 days 47 4:1 + every 14 days 30 150 x 50 42 4:1 + every 21 days 29 150 x 30 43

Interactive effect of row ratio &

irrigation 3:1 + every 14 days 27

75 x 50 46

Branches (no.)

Effect of spacing

75 X 30 47

150 x 50 752 150 x 50 359 150 x 30 650 150 x 30 291 75 x 50 492 75 x 50 251

Pods/plant (no.) Effect of spacing

75 X 30 457

Effect of spacing

75 X 30 190 4:1 + every 21 days 4.25 150 x 50 3.32 3:1 + every 14 days 4.22 150 x 30 3.25 3:1 + every 21 days 4.11 75 x 50 2.83

Seeds/pod (no.) Interactive effect of row ratio &

irrigation 4:1 + every 14 days 3.75

Effect of spacing

75 X 30 2.75 150 x 50 14.55 150 x 30 14.55 75 x 50 13.89

Weight of 100 seeds (g)

Effect of spacing

75 X 30 14.08 Every 21 days 117.91 4:1 78.02 Irrigation effect Every 14 days 129.72


150 x 50 149.07 150 x 50 98.61 150 x 30 140.67 150 x 30 68.72 75 x 50 101.43 75 x 50 59.23

Effect of spacing

75 X 30 104.09

Effect of spacing

75 X 30 42.09 4:1 + 150 x 50 118.9 4:1 + 150 x 30 84.20 3:1 + 150 x 50 78.40 4:1 + 75 x 50 64.90 3:1 + 75 x 50 53.50 3:1 + 150 x 50 53.20 4:1 + 75 x 30 44.00

Interactive effect of row ratio &

spacing

3:1 + 75 x 30 40.10 150 x 50 + every 21 days 111.60 150 x 50 + every 14 days 85.70 150 x 30 + every 14 days 69.00 150 x 30 + every 21 days 68.50 75 x 50 + every 14 days 66.50 75 x 50 + every 21 days 51.90 75 x 30 + every 21 days 43.20

Yield/plant (g)

Interactive effect of spacing &

irrigation

75 x 30 + every 14 days 40.90 150 x 50 1432.10 4:1 1306.29 150 x 30 2278.90


75 x 50 1903.30

Yield/ha (kg) Effect of spacing

75 X 30 3254.90


Interaction effect of row ratio, plant spacing andirrigation: The interactive effect of row ratio, spacing andirrigation was non-significant (P<0.05) for all the growth andyield characters of ICPA 2043 in both years (Table 1) whichagree with the findings of Mula et al. (2010b and 2011a) andReddy et al. (1984) that for any growth and agronomiccharacters studied there was no interaction between irrigationlevels and plant density.

CONCLUSION

The research revealed that agronomic and yield traitsof ICPA 2043 were more likely influenced only by the directeffect of row ratio, and spacing rather than the other effectsand interactive effect of the three factors (row ratio + spacing+ irrigation). Row ratio 4:1 produced the highest seed yield(1306.29 kg/ha) due to more number of rows of female linesthan in 3:1. Moreover, spacing of 75 cm x 30 cm accorded thehighest seed yield (3254.9 kg/ha) as compared to the othertreatments. Because of wider spacing, individual plantattributes showed significant advantage on the growth andyield traits over closer spacing, although, this advantage havenot influenced the increase in total seed yield of ICPA 2043due to lesser plant population. Furthermore, the applicationof irrigation whether at 21 days interval (2 times) or at 14 daysinterval (3 times) during flower initiation till pod developmentis crucial for seed growth. It is further concluded that any ofthe row ratios, spacing’s and irr igation frequencycombinations can be adopted to produce ample amount ofhybrid seeds.

REFERENCES

Abrams R and Julia FJ. 1973. Effect of planting time, plant population,and row spacing on yield and other characteristics of pigeonpeas,Cajanus cajan (L.) Millsp. University of Puerto Rico. Journal forAgriculture 57(4):275-285.

Ahlawat IPS and Rana DS. 2005. Concept of efficient water use inpulses. In: Pulses. Singh G, Sekhon HS and Kolar JS (eds.). AgrotechPublishing Academy, Udaipur, India. p. 320.

Kumar Rao JVDK, Johansen C, Chauhan YS, Jain KC and Talwar HS.2001. An analysis of yield variation among long-duration pigeonpeagenotypes in relation to season, irrigation and plant population.Journal of Agricultural Science 136:291-299.

Kumar Rao JVDK, Johansen C, Chauhan YS, Jain KC and Talwar HS.1992. Response of long-duration pigeonpea genotype to irrigationand spacing in central India. International Pigeonpea Newsletter16:14-16.

Lawn RJ and Troedson RJ. 1990. Pigeonpea: Physiology of yieldformation. Pages 181-197. In: The Pigeonpea. Nene YL, Hall SD

and Sheila VK (eds). CAB International. International CropsResearch Institute for the Semi-Arid Tropics, Patancheru 502 324,AP, India.

Mula MG and Saxena KB. 2010. Lifting the level of awareness onpigeonpea – a global perspective. Patancheru 502 324, AndhraPradesh, India: International Crops Research Institute for the Semi-Arid Tropics. 540 pp.

Mula MG, Saxena KB, Kumar RV, Mula RP and Rathore A. 2010a.Effect of spacing and irrigation on seed production of a CMS-basedpigeonpea hybrid. Green Farming 1:331-335.

Mula MG, Saxena KB, Rathore A and Kumar RV.2010b. Response tospacing and irrigation in a medium-duration CMS-line of pigeonpea.Journal of Food Legumes 23(3&4):186-190.

Mula MG, Saxena KB, Rathore A and Kumar RV. 2011. Influence ofspacing and irrigation on seed production of medium-durationpigeonpea hybrid. Green Farming 2(1):24-26.

Mula MG, Saxena KB, Kumar RV and Rathore A. 2011a. Influence ofspacing and irrigation on the seed yield of a CMS line ‘ICPA 2043’of hybrid pigeonpea. Journal of Food Legumes 24(3):202-206.

Rao SC, Coleman SW and Mayeux HS, 2002. Forage production andnutritive value of selected pigeonpea ecotypes in the SouthernGreat Plains. Crop Science 42:1259-1263.

Reddy BVS, Green JM and Bisen SS. 1978. Genetic male-sterility inpigeonpea. Crop Science 18:362-364.

Reddy GRS, Ramaseshaiah K, Jain TC and Rao YY. 1984. Irrigation andplant density requirements for optimum yields of red gram. MadrasAgricultural Journal 71:281-284.

Saxena KB and Nadarajan N. 2010. Prospects of pigeonpea hybrids inIndian Agriculture. Electronic Journal of Plant Breeding 1(4):1107-1117.

Saxena KB. 2006. Hybrid Pigeonpea Seed Production Manual. Info.Bull. No.74. ICRISAT, Patancheru 502 324, A.P., India.

Saxena KB, Kumar RV, Srivastava N and Bao S. 2005. A cytoplasmic-nuclear male-sterility system derived from a cross between Cajanuscajanifolius and Cajanus cajan. Euphytica 145(3):289-294.

Saxena KB, Chauhan YS, Johansen C, and Singh L. 1992. Recentdevelopments in hybrid pigeonpea research. Proc. Workshop onNew Frontiers in Pulses Research and Development. November10-12, 1989. Kanpur, India. 58-59.

Sekhon HS, Singh G, Sidhu PS and Sarlach RS. 1996. Effect of varyingplant densities on the growth and yield of new pigeonpea hybridand other genotypes. Crop Improvement 23:93-98.

Sinha AC, Mandal BB and Jana PK. 1988. Physiology analysis of yieldvariation in irrigated pigeonpea in relation to time of sowing, rowspacing and weed control measures. Indian Agriculturist 32:177-185.

Venkataratnam N, Rao IM and Sheldrake AR. 1984. Effects of plantpopulation on post-rainy season pigeonpea yields. InternationalPigeonpea Newsletter 3:20-22.

Wilsie CP. 1935. Seed production studies with legumes in Hawaii. Journalof American Society on Agronomy 27:784-790.


Influence of organic nutrient sources on growth, seed yield and economics of cowpeaunder mid hills of Arunachal PradeshV.K. CHOUDHARY, P. SURESH KUMAR and R. BHAGAWATI

ICAR Research Complex for NEH Region, Arunachal Pradesh Centre, Basar- 791101 (India);E-mail: [email protected](Received: January 20, 2012; Accepted: December 6, 2013)

ABSTRACT

Raising a good crop of cowpea with manures and suitableagricultural practices plays crucial in the hill agroecosystemof Arunachal Pradesh. Although the availability of diversemanures there is plenty yet these are not being properlyutilized in management for realization of higher yield.Therefore, the present study was conducted during 2009 and2010 at ICAR Research Complex for NEH Region, ArunachalPradesh Centre, Basar to fine tune the effective organic sourcefor cowpea. The experiment involving diverse organic manorialtreatments viz., vermicompost @ 2.5 tonnes/ha, poultry manure@ 1.25 t/ha, swine manure @ 3.0 t/ha, cow dung manure @ 10.0t/ha, farm yard manure @ 10.0 t/ha were tried for their efficacyunder field condition. Higher growth, yield attributes and seedyield were recorded under vermicompost @ 2.5 t/ha followed bypoultry manure @ 1.25 t/ha over those in control. SPAD valueand solar radiation interception at middle and bottom of thecrop canopy during 30 and 60 days after sowing were also higherin the treatments where vermicompost or poultry manure wereapplied. Seed quality parameters viz., protein, fibre content,self life and palatability, and economics were also favouredfollowing vermicompost application.

Key words: Cowpea, Economics, Organic manure, Seed quality, Seedyield, Yield attributes

Cowpea (Vigna unguiculata L, Walp.) is an importantlegume cum vegetable crop known to for its role insupplementation of farm income and conservation of naturalresources especially in hill agroecosystem. It is an importantfood legume grown under rainfed conditions in the tropics,consumed as both seed and vegetable (Sangakkara 1998).Although it occupies a smaller proportion of the crop areathan cereals, cowpea contributes significantly to householdfood security (Langyintuo et al. 2004). The seed is a goodsource of human protein, while the stover is a valuable sourceof livestock protein. The food experts and nutritionists haverealized and appreciated the food value of cowpea because ofits low calorific value, high content of proteins, vitamins, andminerals (Abebe et al. 2005). In hilly terrain, due to steepness,farmers usually opt for multipurpose crop species like cowpeawhich not only give income but also protect the soil fromerosion (Ramkrishnan 1984). Cowpea fixes atmospheric N upto 240 kg/ha and leaves about 60-70 kg residual N forsucceeding crops. Thus, cowpea is one of the most essentialvegetable crops in organic farming systems as it contributes

to the sustainability of cropping systems and soil fertilityimprovement even in a marginal lands through provision ofground cover, plant residue, nitrogen fixation and suppressingweed (Abayomi et al. 2008, Mishra et al. 2012).

Addition of organic materials is a common practice in ahill agroecosystem. Besides plant nutrients, the presence ofenzymes and hormones in manure make them essential forimprovement of soil fertility and productivity. Cowpea requiresgood quantity of nutrients throughout the growth periodsespecially P for better development of roots, better nodulationand N-fixation (Kutama et al. 2008). Moreover, in early stages,plant requires N for better germination, production of morebranches and peduncles resulting in greater number of pods,seeds and significantly higher yields (Rajasree and Pillai 2001,Abayomi et al. 2008). In addition, N and P have a stimulatingeffect on root activity and rooting pattern of the crop.Available nitrogenous compound (also through a starter dose)enables seedlings to make a good start even before nitrogenfixation. Plants fed with organic nitrogen during vegetativeperiods are much larger by the onset of flowering than thosedependent on symbiotic N-fixation (Abayomi et al. 2008).Therefore, considering the importance of organic manure andits impact on crop and its production economics, the studywas designed to evaluate the growth and yield responses ofcowpea to diverse organic sources of nutrients so as to finetune it for their suitability in pulses nutrition.


A field experiment was conducted in clay-loam soil atthe Research Farm of ICAR Research Complex for NEH Region,Arunachal Pradesh Centre, Basar during 2009 and 2010. Thearea falls under the humid subtropical climate. The dailytemperature during the study period varies between minimumof 240C and maximum of 350C and received average rainfall of1300 mm (April- August). The soils are clay loam in texture,acidic in reaction (pH 5.3), high in organic carbon (1.50% byWalkaley and Black), low in available N (205.6 kg/ha by alkalinepermanganate), low in available phosphorus (8.3 kg/ha byBray P) and medium in available potassium (260 kg/haestimated by Neutral normal ammonium acetate). Moistureretention at 0.03 and 1.5 MPa, bulk density and saturatedhydraulic conductivity were 29.6% and 17.2%, 1.45 t/m3 and532.1 mm/hr respectively, in 0-20 cm surface soil.


All the organic materials (with nutrient contents givenin Table 1) were applied 20 days before planting and mixedthoroughly in the soil. The experiment involving six treatmentsviz. 1) vermicompost @ 2.5 t/ha, 2) poultry manure @ 1.25 t/ha, 3) swine manure @ 3.0 t/ha, 4) cow dung manure @ 10 t/ha, 5) farm yard manure @ 10 t/ha and 6) a control was laid outin a randomized completely block design with three replications.Each treatment was superimposed with 25 kg of P/ha throughsingle super phosphate at the time of sowing except control.Cowpea variety ‘Kashi Kanchan’ was sown with recommendedplanting geometry (45x15 cm). Five plants of each plot weretagged and all the plant parameters such as plant height,number of leaves, leaf area and leaf area index (LAI at 60DAS), total dry matter (TDM) of leaf, stem and pods (at thirdpicking) and number of nodules (at 60 DAS) were recorded.Seed yield attributes such as number of pods, length of pods,and number of seeds and green pod yield were recorded from1x1 m2 of net plot whereas, seed and stover yields wererecorded from rest of the net plot.

Chlorophyll (SPAD value) and solar radiationinterception (%) was measured at 30 and 60 DAS byChlorophyll Meter (SPAD-502) and Digital Lux Meter (TES1332) respectively during clear sunny days at 1.00 pm. Proteinand fibre content were recorded during the experimentation.Shelf life and palatability of green pod were also assessed bytesting samples by a semi-trained sensory panellist. Tomeasure and assess the quality parameters, 3rd picking wasused in the study. Economics of cultivation such as cost ofcultivation, gross returns, net returns and B: C ratio additionalreturn, marginal return (MR), marginal cost (MC) and MR:

MC was calculated on the basis of prevailing market price ofinputs and outputs. Statistical analysis was carried out toknow the variance for different parameters and effect oftreatments using standard statistical package (AGRES); andsignificance was ascertained at both 1 and 5% level ofsignificance.

RESULTS AND DISCUSSIONS

Crop Growth: Plant biometrics such as plant height,leaves & branches/plant, leaf area, LAI and total dry matterwere observed to be significantly higher with application ofvermicompost @ 2.5 t/ha followed by poultry manure @ 1.25t/ha over those in control (Table 2). Although application ofcow dung and farm yard manure @ 10.0 t/ha improved theseparameters, yet their effects were less pertinent in comparisonto vermicompost and poultry manure. From the observationon early crop establishment and production of more numbersof leaves and branches, the effect of both these manures wereapparent. Increase in leaf area and LAI made the plants tocapture more solar radiation by its canopy with enhancedphotosynthesis that further helped in better translocation ofphotosynthates to different plant parts resulting in higherdry matter (Abebe et al. 2005). Higher root nodules were alsocounted with vermicompost application (Table 2). This was inconformity with earlier finding of enhanced symbioticrelationship in Rhizobium vis-a-vis root nodules followingorganic supply (Madukwe et al. 2008).

Seed yield and its attributes: Plants grown under control(no manure) reached at 50% flowering a week earlier than thatin vermicompost treated plots. Yield attributes viz., pods/plant,pod length and seeds/pod were also higher undervermicompost @ 2.5 t/ha followed by poultry manure @ 1.25t/ha over the control (Table 2). As a result, yield of both greenpod and stover under vermicompost were increased by 120and 49% respectively (followed by poultry manure) over thesein control. Application of cow dung and farm yard manure

Table 2. Growth and yield parameters of cowpea as influenced by organic sources of nutrient

Organic manure Plant height (cm)

Branches /plant

Leaves/ plant

Leaf area (dm2/plant)

LAI TDM (g/plant)

Nodules/ plant

50% flower (days)

Pods/ plant

Length of pod (cm)

Seeds/ pod

Green pod yield

(t/ha)

Seed yield (t/ha)

Stover yield (t/ha)

Vermicompost @ 2.5 t/ha 78.6 6.8 51.3 62.1 9.3 57.6 23.7 52.2 38.1 30.3 13.1 4.92 1.50 7.24

Poultry Manure @ 1.25 t/ha 76.5 6.3 46.0 58.1 8.0 52.2 20.0 50.2 33.6 27.2 12.2 4.38 1.35 7.00

Swine manure @ 3.0 t/ha 72.2 5.6 39.0 53.6 7.9 48.1 21.0 53.2 25.9 22.2 11.6 3.87 1.27 6.14

Cow dung manure @ 10.0 t/ha 69.5 4.7 32.7 43.2 6.4 43.6 15.0 48.0 23.3 25.4 10.5 3.53 1.20 5.35

Farm yard manure @ 10.0 t/ha 66.6 4.2 40.0 47.9 7.1 41.9 14.0 47.3 22.0 22.9 10.8 3.45 1.17 5.58

Control 62.6 3.2 26.3 31.7 4.7 33.7 10.2 45.2 17.1 20.7 9.6 2.24 0.80 4.86 CD(P=0.05) 6.46** 1.61* 5.81** 6.01** 1.23** 5.29** 3.27** 4.46* 6.21** 4.02** 1.83* 0.40** 0.273** 0.45*

Table 1. Nutrient content in different organic sourcesOrganic manure N (%) P (%) K(%) Vermicompost 2.00 1.00 1.50 Poultry Manure 4.00 1.60 1.80 Swine manure 1.67 1.17 1.49 Cow dung manure 0.50 0.30 0.60 Farm yard manure 0.50 0.25 0.40

NS, Non-significant of P<0.05; *, significant level of P <0.05, **, significant level of P <0.01LAI: leaf area index; TDM: total dry matter

Choudhary et al., : Influence of organic nutrient sources on growth, seed yield and economics of cowpea under 5 3

NS, Non-significant of P<0.05; *, significant level of P <0.05, **, significant level of P <0.01*** For palatability score 1- Very poor, Score 2- Poor, Score 3- Medium, Score 4- Good, Score 5- Very good

Chlorophyll content (SPAD) Solar radiation interception (%)

Organic manure

30 DAS 60DAS Middle Bottom

Protein (%)

Fiber content (%)

Self life (Days)

Palatability***

Vermicompost @ 2.5 t/ha 25.7 33.5 45.1 83.0 23.5 9.1 10.5 5.0 Poultry Manure @ 1.25 t/ha 25.8 30.8 43.3 80.8 22.8 9.8 9.5 4.1 Swine manure @ 3.0 t/ha 23.3 29.3 39.6 78.9 21.7 9.9 8.3 3.6 Cow dung manure @ 10.0 t/ha 24.5 28.7 37.7 77.4 21.3 10.8 8.1 3.2 Farm yard manure @ 10.0 t/ha 24.5 27.9 37.6 76.6 20.8 10.7 7.7 3.1 Control 20.4 25.5 33.7 74.1 18.1 13.3 7.2 2.4 CD (P=0.05) 3.13* 2.31** 3.81** 4.26* 2.78* 1.25** 1.01** -

Table 3. Chlorophyll content, solar radiation and quality parameters of cowpea as influenced by organic sources of nutrient

also improved yield attributes resulting in 73 and 58% highergreen pod yield respectively over control. Seed yield followedthe same trend as that of green pod yield. Higher yieldattributes and seed yield of cowpea following vermicompostapplication was due to higher crop growth resulting information of higher numbers of reproductive organs (Sharmaet al. 2002, Abayomi et al. 2008).

Chlorophyll content and solar radiation interception:Solar radiation interception and SPAD value were significantlyinfluenced by different sources of manures (Table 3). AlthoughSPAD value at early stage (30 DAS) was similar under bothpoultry manure and vermicompost yet at later stage (60 DAS),maximum SPAD value was measured in vermicompost appliedplot followed by poultry manure. Solar radiation interceptionat middle and bottom of the canopy was the highest undervermicompost followed by poultry manure, and the minimuminterception was recorded in control. The higher value of SPAD

with poultry manure was mainly due to higher value of N(Table 1). In addition, once plants got established,vermicompost stimulated enhanced uptake of micronutrientslike, Mg2+ and Fe2+ providing ease in availability of enzymesand plant hormones which were the integral part ofchlorophyll. Similarly, as a result of higher leaf area and LAI,solar radiation interception was highest under vermicompostand poultry manure. Consequently, higher photosynthatesand dry matter were accumulated on plant parts (Anburaniand Manivannan 2002).

Quality parameters: Certain quality parameters likeprotein, fibre content, shelf life and palatability of the seedwere significantly varied with different sources of organicmanure (Table 3). Seed protein content analysed was 30%higher under vermicompost supplied plots and was followedby poultry manure (26%) than the control (registering leastprotein). Fibre content was also 46% lower under

Table 4. Economic analysis of cowpea (green pod and seed) under diverse organic sources

*Price of input and output in ` : Cowpea green pod at ` 10/kg, Stover ` 500/t, seed ` 45/kg, vermicompost at ` 3.2/kg, poultry manure ` 4/kg, swinemanure ` 3/kg, cow dung manure ` 1/kg, farm yard manure ` 1/kg

Particular Vermicompost Poultry manure

Swine manure Cow dung manure

Farm yard manure

Control

Pod & stover Cost of cultivation (`/ha) 12200 12200 12200 12200 12200 12200 Cost of treatment (`/ha) 8000 5000 6000 4000 5000 - Total cost of cultivation (`/ha)* 20200 17200 18200 16200 17200 12200 Gross return from cowpea (`/ha) 55400 49800 44400 40550 39400 26700 Net return (`/ha) 35200 32600 26200 24350 22200 14500 B:C ratio 1.74 1.90 1.43 1.50 1.29 1.19 Green pod yield difference over control (`/ha) 2.68 2.14 1.63 1.29 1.21 - Marginal cost (`/ha) 8000 5000 6000 4000 5000 - Marginal return (`/ha) 26800 21400 16300 12900 12100 - MR: MC 3.35 4.28 2.72 3.23 2.42 -

Seed Cost of cultivation including treatment* (`/ha) 20750 17750 18750 16750 17750 12750 Gross return from cowpea (`/ha) 67500 60750 57150 54000 52650 36000 Net return (`/ha) 46750 43000 38400 37250 34900 23250 B:C ratio 2.25 2.42 2.05 2.22 1.97 1.82 Seed yield difference over control (t/ha) 0.70 0.55 0.47 0.40 0.37 - Marginal cost (`/ha) 8000 5000 6000 4000 5000 - Marginal return (`/ha) 31500 24750 21150 18000 16650 - MR:MC 3.94 4.95 3.53 4.50 3.33 -


vermicompost applied plots over that in control. The shelf lifeof green pods was also observed to be higher withvermicompost followed by poultry manure with the least shelflife under control. Green pod harvested from plots suppliedwith 2.5 t/ha of vermicompost has also higher score forpalatability followed by poultry manure with low palatabilityscore under control. The release of essential nutrients due todecomposition of air dried manure by soil microbes was mainlycontributed to nutrients availability in soil-plant system andimprovement in protein content of cowpea (Abebe et al. 2005).

Economics: Both gross and net returns were higherwith vermicompost with lower values under control (Table 4).This resulted in higher BCR with poultry manure (1.9:1)followed by vermicompost (1.74:1) in comparison to control.Additional harvest of green pods and cowpea seeds was alsorecorded under vermicompost supplied plots followed bypoultry manure, whereas the ratio of marginal return to itscost (MR:MC) was highest under poultry manure (4.28)followed by vermicompost (3.35).

Thus, it was inferred from above that vermicompost @2.5 t/ha or poultry manure @ 1.25 t/ha could be effective inenhancing productivity of cowpea with improved quality ofthe produce.

REFERENCES

Abayomi YA, Ajibade TV, Sammuel oF and Saadudeen BF. 2008. Growthand yield responses of cowpea (Vigna unguiculata (L.) Walp)genotypes to nitrogen fertilizer (NPK) application in the SouthernGuinea Savanna Zone of Nigeria. Asian Journal of Plant Sciences 7:170-176.

Abebe G, Hattar B and Al-Tawaha ARM. 2005. Nutrient availability asaffected by manure application to cowpea (Vigna unguiculata L.

Walp.) on calacarious soils. Journal of Agriculture and Social Sciences1: 1-6.

Anburani A and Manivannan K. 2002. Effect of integrated nutrientmanagement on growth in brinjal. South Indian Horticulture 50:377-386.

Kutama AS, Aliyu BS and Saratu AO. 2008. Influence of phosphorusfertilizer on the development of root nodules in cowpea (Vignaunguiculata L. Walp) and soybean (Glycine max L. Merril).International Journal of Pure and Applied Sciences 2: 27-31.

Langyintuo AS, Ntoukam G, Murdock L, Lowenberg-DeBoer J andMillera DJ. 2004. Consumer preferences for cowpea in Cameroonand Ghana. Agricultural Economics 30: 203-213.

Madukwe DK, Christo IEC and Onuh MO. 2008 Effects of organicmanure and cowpea (Vigna unguiculata (l.) Walp) varieties on thechemical properties of the soil and root nodulation. Science WorldJournal 3: 43-46.

Mishra JP, Praharaj CS, Singh KK and Narendra Kumar 2012. Impactof conservation practices on crop water use and productivity inchickpea under middle Indo-gangatic plains. Journal of FoodLegumes 25: 41-44.

Mishra J.P., Praharaj C.S. and Singh K.K. 2012. Enhancing water useefficiency and production potential of chickpea and fieldpea throughseed bed configurations and irrigation regimes in North Indian Plains.Journal of Food Legumes 25: 310-313.

Rajasree G and Pillai GR. 2001. Performance of fodder legumes underlime and phosphorus nutrition in summer rice fallow. Journal ofTropical Agriculture 39: 67-70.

Ramakrishanan PS. 1984. The science behind rotational bush fallowagricultural system (Jhum). Proc. Indian Aca. Sci. (Plant Science)93: 379-400.

Sangakkara UR. 1998. Growth and yields of cowpea (Vigna ungukulata(L.) Walp) as influenced by seed characters, soil moisture and seasonof planting. Journal of Agronomy and Crop Science 180: 137-142.

Sharma SR, Bhandari SC and Purohit HS. 2002. Effect of organic manureand mineral nutrients on nutrient uptake and yield of cowpea.Indian Journal of Agronomy 50: 1-6.


Pathogenic variation and compatibility groups in Sclerotium rolfsii isolates causingcollar rot on chickpea (Cicer arietinum L.)OM GUPTA, SACHIN PADOLE and MADHURI MISHRA

Department of Plant Pathology, Jawaharlal krishi vishwa vidyalaya, Jabalpur, M.P. 482004, India; Email:[email protected](Received: October 05, 2012 ; Accepted : October 14, 2013)

ABSTRACT

Pathogenic variability of fifty one isolates of Sclerotium rolfsiicollected from collar rot infected plants of chickpea were broadlygrouped into three pathotypes on the basis of number of daystaken to initiate plant mortality and causing 100 per centmortality. The isolates belonging into three groups were studiedfor mycelial compatibility and the pathotypes showed threereactions i.e. compatible reaction, antagonistic reaction andmycelial incompatibility. In their mycelial compatibility 1273pairing combinations were observed, out of which 203combinations (15.9%) were found compatible and 175 (28.0%)incompatible and 84 per cent combinations (1070) showedantagonistic effect. Microscopic observations on mycelialinteraction revealed hyphal thinning followed by protoplastlysis, vacuole formation and hyphal thickness at the interactionzone.

Key words: Sclerotium rolfsii, Pathotypes, Mycelial compatibility

Sclerotium rolfsii Sacc. is a devastating soil borne plantpathogenic fungus with a wide host range (Punja 1988). InIndia, the plant mortality due to collar rot of chickpea causedby S. rolfsii range from 54.7 to 90 per cent (Kotasthane et al.1976). It causes significant reduction in plant population atseedling stage especially in soybean–chickpea or paddy–chickpea based cropping system. Geographical variabilityamong S. rolfsii populations was demonstrated by earlierworkers (Nalim et al. 1995 and Okabe et al. 1998). Studies ofvariability within the population in a geographical region areimportant because these also document the changes occurringin a population. Not much work has been done on pathogenicdiversity and mycelial compatibility within the isolates.Keeping in view, the present study was undertaken to knowthe pathogenic diversity, mycelial compatibility/incompatibility of S. rolfsii isolates from Madhya Pradesh.


Fifty one isolates of S. rolfsii causing collar rot ofchickpea, used in this study were collected from diseasedplants adjacent to Jabalpur, Madhya Pradesh. The isolateswere purified for further studies by growing single sclerotiafrom each colony on potato dextrose agar slants.

Pathogenic variability: Virulence analysis of the 51isolates of Sclerotium rolfsii was carried out on chickpeavariety JG 322 in net house with complete randomized block

design in three replications. Test plants (10 /pot) were grownin sterilized soil and soil infested with the culture of S. rolfsii@ 10 % (w/w) was used to inoculate 10 days old seedling atcollar regions. The pots were watered as and when required.Observations were recorded on time period for diseaseinitiation and maximum disease development (Gupta, 2000).

Mycelial compatibility: Mycelial disc of 5 mm diametercut from the edge of an actively growing colony (3 to 4 daysold) from each isolate was placed approximately 25 - 35 mmapart on opposite sides of 90 x 15 mm petri plates and incubatedat 25 ± 20C. Three isolates were paired on each petridish andthe test was repeated. The pairings were examinedmacroscopically and microscopically after 5 - 15 days asdescribed by Punja and Grogan (1983).

RESULTS AND DISCUSSIONS

Pathological variability has been established on thebasis of variation in their virulence i.e. the days taken fordisease initiation after inoculation and days taken fordevelopment of 100 per cent mortality which indicated thatisolates may be grouped into three pathotypes i.e. highlyvirulent, virulent and least virulent. Isolates 6, 11, 25, 44, 46,48, and 49 caused 50 % mortality within 5-9 days of inoculationand required 14 days in causing 100 per cent mortality,representing highly virulent group, whereas rest of the isolatestook 15-24 days and hence categorized as virulent and leastvirulent (Table 1). No correlation was noticed between isolatesin causing disease initiation and 100 per cent mortality. Agrawalet al. (1976) also reported the highest seedling mortality dueto S. rolfsii in lentil plants, when inoculated just after sowing.Variation in infection was observed in all the isolates. IsolatesDL-1, DL-2, CH-2, AT-1 and AT-2 were more aggressive andmost of the cultivars were susceptible to these isolates(Hussain et al. 2009). Similar results were reported by Ansariand Agnihotri 2000 and Remesal et al. 2012.

Mycelial compatibility: Mycelial compatibility in S.rolfsii isolates was observed to possess three combinationsi.e. compatible reaction, antagonistic reaction and theincompatible reaction. 1273 pairings of the 51 isolates (Table2) were made and 203 combinations showed compatiblereaction (15.9%) i.e. intermingling of two isolates at the zoneof interaction. Other 1070 combinations showed antagonisticreactions (84.1%) with each other i.e. forming thin band of


No. of days and mortality (%)

Groups 50 100

No. of Isolates

Isolates

Highly virulent 5-9 12-14 07 6, 11, 25, 44, 46, 48, 49 Virulent 5-16 15-20 21 2, 3, 4, 8, 10, 13, 14, 16, 19, 20, 23, 30, 31, 32, 37, 38, 41, 42, 45, 47, 51 Least virulent 4 -17 21-24 23 1, 5, 7, 9, 12, 15, 17, 18, 21, 22, 24, 26, 27, 28, 29, 33, 34, 35, 36, 39, 40, 43, 50

Table 1 : Pathological variability in isolates of Sclerotium rolfsii

Table 2. Mycelial compatibility and incompatibility groups in isolates of Sclerotium rolfsii

A - Antagonistic reaction NI - normal intermingling

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 1 A A A A A A A A A A A A A A NI A A A NI NI A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A 2 A A A A A A A A A A A A A A A NI A A A A NI A A A A A A A A A A A A A A A A A A A A A A A A A A A A 3 A A A NI A A A A A A A A A A NI NI A A A A A A A A A A A A NI NI A A A A A A A A A A A A A A A A A A 4 A A A A A A A A NI A A A A A A A A A A A A A A A A A A A A NI A A A A A A A A A A A A A NI A A A 5 A A A A A A A NI A A A A A A A A A A A A A A A NI NI NI A A NI A A A A A NI NI A NI A A A A A A A A 6 A A A A A A A NI A A A A A A A A A NI A A A A A A A A A A A A A A A A A NI A A A A A A A A A 7 A A A A A A A A A A A NI A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A 8 A A A A A A A A A A A A A A A A A A A NI A A A A A A A A A A A A A A A A A A A A A A A 9 A A A A A A A A A A A A A A A A NI A A A A A A A A NI A A A A A A NI A A A A A A A A A 10 NI A A A A A A A A A A A A A A A A A A A NI A A A A NI A A A A A NI NI A A A NI A A A A 11 A A A A A A A A A A A A A A A NI NI A A A A A A A A A A A NI NI A A A A A NI A A A A 12 NI A A A A A A A A A A A A A A A A A A A NI A A A A A A A A NI A A A A A A NI A A 13 A A A A A A A A A A A A NI A A A A A A A A A A A A A A NI A A A A NI A A A A A 14 A A NI A A A A A A A A NI NI A A A A A A A A A A A A NI A A NI A A A A A A A A 15 A A A A A A A A A A A A A A A A A A A A A A A A A A NI A A A A NI A A A A 16 A A A NI NI A A A A NI NI NI NI NI A A A A A A A A A A A A A A NI NI NI A A A A 17 A A A A A A A A A A A A A A A A NI A A A A A A A A A A A A A A A A A 18 NI A A A A A A NI A A A A A A A A A A A A A A A A A A A A A A A A A 19 A A A A A A A A A A A A A A A A A NI A A A A A A A A A NI A A NI A 20 A NI NI A A A A A A A A A A A A A A NI NI NI NI NI NI A A NI A A A A A 21 A A A NI A A A A A A NI NI A A A A A A A NI NI A A A A A A A A A 22 NI A A NI NI A A A A A A A A A A A A A A A NI A A NI NI NI NI A A 23 A A A A A A A A A A A NI A A A A A A A A A A A A A A A A 24 A A A NI A A A A A A A A NI A A A A A A A A A A A A A A 25 A NI A A A A A NI A A A A A A A A A A A A NI A A A A A 26 NI NI A A A A A A A A A A NI NI NI NI A NI NI A A A NI A A 27 A NI NI A A A A A A A A NI A A A NI A NI A A NI A A A 28 A A A A A A A A A NI NI A A A A NI NI NI NI A A NI NI 29 NI NI NI NI NI A A NI A A NI NI A NI NI NI A A A A A A 30 NI NI A A NI NI A NI NI NI NI A NI NI A A A A A NI A 31 NI A A A NI NI NI NI A A A NI A A A NI A A A A 32 A A A A A NI A A A A A NI A A NI A A NI A 33 A A A A NI A A A A A A A A NI NI A A A 34 A A A A A A A A A A A A A A NI A A 35 NI NI NI A NI NI NI NI A A A A A A A NI 36 NI NI A NI NI A NI A A A A A A A A 37 NI NI NI NI A A A A A A A A A A 38 A NI A A NI NI A A A A A A A 39 A A A A A A NI A NI NI A A 40 NI A NI NI A A A A A A A 41 A NI NI A A A A NI A A 42 A A A NI NI NI A A A 43 NI NI NI NI NI NI A NI 44 A A A NI A NI A 45 A A A A NI NI 46 A A A A A 47 NI A A NI 48 A NI A 49 NI A 50 A 51 A

Gupta et al., : Pathogenic variation and compatibility groups in Sclerotium rolfsii isolates causing collar rot on chickpea 5 7

Fig 1. Mycelial compatibility reaction between isolates ofSclerotium rolfsii

(a) Normal intermingling (NI) and barrage (Br.) formationbetween compatible and incompatible isolates

(b) Broadening of interacting zone showing unlysed (35, 39,40, 41, 42, 43, 44, 45, 46, 47, 50 and 51) and

gradual lysis of mycelia

living or dead mycelial. In all the antagonistic reactionssclerotia were not formed at the interaction zone. 735combinations (Fig 1 a) showed formation of sclerotia (59%) inthe borders of lytic zone of the two isolates while 5 isolatesi.e. 39, 40, 41, 43 and 47 showed sclerotial formation at boardersand isolates 35, 47 and 51 formed sclerotia evenly. The numberof sclerotia was drastically reduced in isolates 42, 44, and 50.In some combinations on prolong incubation, antagonisticside, the isolates no. 35, 39, 40, 41, 42, 43, 44, 45, 47, 50 and 51were broadened at interaction zone or in some cases lysisoccurred completely in one isolate only (Fig 1, b). However, insome combinations, the interacting zone did not widen evenafter prolong incubation.

Based on mycelial compatibility, 175 (28.0%)incompatible reaction were observed among the isolates. Themycelial interaction zone of two isolates observed undermicroscope revealed that (Fig 2) in some isolates there wasprotoplast lysis, vacuole formation, variation in hyphalthickness and hyphal lysis. The region of mycelialintermingling of isolates 29 and 39 showed the protoplastlysis whereas six isolates i.e. 29, 34, 35, 42, 46 and 47 showedvacuole formation while hyphal thickness and hyphal lysiswere observed in 21, 38 and 50, 51 isolates respectively inantagonistic effect.

The high rate of antagonistic reactions (84%) in themycelial compatibility test in the present experiments furthershows the degree of diversity among the isolates of S. rolfsii

collected from different chickpea field of Jabalpur. The isolatespossess three combinations viz., compatible reactions,antagonistic reaction and the incompatible reaction. Formationof vacuole, hyphal thinning followed by protoplast andmycelial lysis at the interaction zone is attributed to theheterokaryotic condition of the nuclei but involvement of toxinscannot be ruled out (Cillers et al. 2000, Sharma et al. 2002,Chand et al. 2003 and Akram et al. 2008). A detailed study inthis regard may reveal some information about the cause ofmycelial death in the incompatible groups.

REFERENCES

Abida Akram, Muhammad Iqbal1, Rizwana Aleem Qureshi and ChaudharyAbdul Rauf. 2008. Variability among isolates of sclerotium rolfsiiassociated with collar rot disease of Chickpea in Pakistan. PakistanJournal of Botany 40: 453-460.

Agrawal SC, Agrawal PS and Khare MN. 1976. Susceptibility of lentilplants to Sclerotium rolfsii Scc. at different stage of growth. JNKVVResearch Journal 10: 73.

Ansari MM and Agnihotri SK. 2000. Morphological, physiological andpathological variations Among Sclerotium rolfsii isolates of soybean.Indian Phytopathology 53: 65-67.

Chand R, Verma R, Singh SK, Chaurasia S and Lal M. 2003. Biology ofaquatic isolates of Sclerotium rolfsii. Indian Phytopathology 56:293-294.

Cillers AJ, Herselman L and Pretorius ZA. 2000. Genetic variabilitywithin and among mycelial compatibility groups of Sclerotiumrolfsii in South Africa. Phytopathology 90: 1026-1031.

Gupta Om 2000. A rapid technique for screening chickpea genotypes toseed and collar rot caused by Sclerotium rolfsii. Extended summary,In National Seminar on “Agriculture scenario challenges andopportunities” held at College of Agri. Gawalior. 197-198

b Fig 2. Showing mechanism of antagonism(a) Lysis of mycelial protoplast (b) Formation of vacuole

(c) Thickening of hyphae (d) Lysis of hyphae

c d


Hussain A, Ghafoor A and Ayub N. 2009. Biodiversity among the isolatesof Sclerotium of chickpea in Pakistan. Pakistan Journal ofPhytopathology 21: 98-103

Kotasthane SR, Agrawal PS, Joshi LK and Singh Laxman 1976. Studieson wilt complex in bengalgram. JNKVV Research Journal 10: 257-258.

Nalim FA, Starr JL, Woodard KE, Segner S and Keller NP. 1995. Mycelialcompatibility groups in texas peanut field population of Sclerotiumrolfsii. Phytopathathology 85: 1507- 1512.

Okabe I, Morikawa C, Matsumoto N and Yokoyama K. 1998. Variationin Sclerotium rolfsii isolates in Japan. Myco. Science 34: 399-407.

Punja ZK and Grogan RG. 1983. Basidiocarp induction, nuclearcondition, variability and heterokaryon incompatibility in Athelia(Sclerotium) rolfsii. Phytopathathology 73: 1273-1278.

Remesal E, Jordán-Ramírez R, Jiménez-Díaz RM and Navas-Cortés JA.2012. Mycelial compatibility groups and pathogenic diversity inSclerotium rolfsii populations from sugar beet crops inMediterranean-type climate regions. Plant Pathology 61: 739–753.

Sharma BK, Singh UP and Singh KP. 2002. Variability in Indian isolatesof Sclerotium rolfsii. Mycologia 94: 1051-1058.


Efficacy of Bioinoculants in combination with insecticides against insect pests ofblackgram Vigna mungo (L.) HepperP.S. SINGH and V. CHOURASIYA

Department of Entomology and Agricultural Zoology, Institute of Agricultural Sciences, Banaras Hindu University,Varanasi-221005, Uttar Pradesh, India; Email: [email protected](Received : August 28, 2012 ; Accepted : November 16, 2013)

ABSTRACT

A study was conducted to evaluate efficacy of the bioinoculantsand chemical insecticides against insect pests of blackgramVigna mungo (L.) Hepper. Seed treatment with Beauveriabassiana + profenophos (spray) was found most effective againstwhiteflies (5.42white fly/cage) and was followed by seedtreatment with Beauveria bassiana + spray with Beauveriabassiana (6.27 whiteflies /cage). Similarly, in case of jassids,the seed treatment with Beauveria bassiana + profenophos(spray) registered minimal population count (1.92 jassids/cage)and was followed by combination of seed treatment withP. florescens + profenophos (spray) (2.10 jassids/cage) amongthe all spray. In case of thrips, combination of seed treatmentwith imidacloprid + profenophos (spray) gave best performancewith lowest thrips infestation (2.58 thrips/10 flower) and highestreduction over control, followed by the Beauveria bassiana+profenophos (spray) 2.92 thrips/10 flower. The per cent poddamage 2.7 per cent with treatment combination Beauveriabassiana (seed treatment) + Beauveria bassiana (spray) whilehighest damage recorded in control plot i.e. 7.3 per cent. TheBeauveria bassiana + profenophos registered highest yield i.e.11.59 q/ha while lowest in control plot i.e. 7.98 q/ha.

Key words: Bioinoculants, Blackgram, Insecticides, Jassid, Poddamage, Thrips, Whitefly

Black gram, Vigna mungo (L.) Hepper commonly knownas urdbean, provide 25 per cent protein and is the richest inphosphoric acid content among the pulses. It established itselfas a highly valuable pulse crop with ability to improve the soilfertility by fixing atmospheric nitrogen. The area underblackgram cultivation in India is about 2.67 million ha withproduction of 1.17 million tonnes, and productivity of 463 kg/ha (Anonymous, 2009). Among the major problems known tolimit the yields of these pulses, incidence of insect pests aremain constrains. Chhabra and Kooner (1985) recorded 54.3per cent losses caused by insect pests in urdbean. Thripsincidence was recorded from flowering to pod-filling stage(Chandra and Rajak 2004). Insecticide application has beenone of the effective and quick method of reducing insect pestpopulation in the field. More often it forms the only solutionto out breaks of pests. However, the performance ofbioinoculants in combination with insecticides changingplant-environment interaction, with specific knowledge of hostplant resistance mechanism must be emphasized to develop

an economic strategy against insect pests.Investigation wascarried out in order to minimize the losses caused by the insectpests in black gram.


The present study was carried out on urdbean varietyPant U -31 during Kharif season of 2010-11 at the AgriculturalResearch Farm of university. Each plot having 10 rows of 4 mlength., (Plot size 4x3 m). The plant spacing between rows andplants were maintained at 30 cm and 10 cm, respectively. Theincidence of insect pests was recorded before and afterspraying with rectangular split cage, on randomly 5 selectedplants from each treatment. The immature as well as the maturestage of major sucking pests present on them were counted at3 and 7 days after spraying. The insect pests recorded werewhitefly, Bemisia tabaci; jassid, Empoasca kerri; thrips,Caliothrips indicus; The number of insect count recordedreplication wise for all the treatments were averaged separatelyfor each treatment on interval basis. The seed treatment wasdone by mixing the required quantity of the insecticides orbioinoculants formulation in desired quantity of seed. Thetreated seeds were dried in shade. The spray mixture of eachtreatment was prepared by mixing the required quantity of theinsecticides and bioinoculants formulation in water to make itequivalent to 600 liters/ha. The foliar applications of thetreatment started at flowering stage (40 DAS) and repeatedonce at the interval of 15 days. In control plot, the plain waterwas sprayed. The pod and grain damage assessment by podborer complex was done after harvesting. 100 pods were pickedup randomly from each treatment plot for pod damage andgrain damage assessment. The plots yield were recorded afterharvesting and converted to yield on hector basis.


Effect on the population of whitefly

The data presented in Table 1 revealed that all themicrobial and chemical insecticidal treatments were foundsignificantly superior over control as observed at intervals of3 and 7 days after spraying. When the microbial and chemicalinsecticides were compared amongst themselves, 3 days afterspraying, seed treatment with Beauveria bassiana + spraywith profenophos and seed treatment with imidacloprid + spray


Table 1. Efficacy of microbial and chemical insecticides against whitefly infesting urdbean during Kharif 2010

NOTE:Figures in parentheses are transformed as X+1; DAS= Days after spraying, ST = Seed Treatment, Sp = SprayingDifference between Treatments CD = (P=0.05) = 0.09Difference between Period CD = (P=0.05) = 0.04Interaction between Treatments X Periods CD = (P=0.05) = 0.13

Population/Cage After 1st spray

Population/Cage After 2nd spray

S.No. Treatments formulation

3 DAS 7DAS

Average

3 DAS 7DAS

Average Average of both spray

T1 Beauveria bassiana (ST.) 10g/kg 8.73 (3.12)

9.33 (3.21)

9.03 (3.17)

8.20 (3.03)

8.07 (3.01)

8.13 (3.02)

8.58 (3.09)

T2 Pseudomonas florescens (ST.) 10g/kg 9.60 (3.26)

9.00 (3.16)

9.30 (3.21)

8.53 (3.09)

8.73 (3.12)

8.63 (3.10)

8.97 (3.16)

T3 B. bassiana + P. florescens (ST.) 5g/kg+3g/kg 9.27 (3.20)

9.80 (3.29)

9.53 (3.25)

8.40 (3.07)

8.93 (3.15)

8.67 (3.11)

9.10 (3.18)

T4 Imidacloprid (ST.) 5g/kg 9.40 (3.22)

10.07 (3.33)

9.73 (3.28)

8.60 (3.10)

9.00 (3.16)

8.80 (3.13)

9.27 (3.20)

T5 B. bassiana (ST.) & B. bassiana (SP.) 10g/kg+2 ml/lit

6.67 (2.77)

6.40 (2.72)

6.53 (2.74)

5.47 (2.54)

6.53 (2.74)

6.00 (2.64)

6.27 (2.69)

T6 P. florescens (ST.) & B. bassiana (SP.) 10g/kg+2 ml/lit

7.20 (2.86)

7.40 (2.90)

7.30 (2.88)

6.00 (2.65)

5.87 (2.62)

5.93 (2.63)

6.62 (2.76)

T7 B. bassiana (ST.) & Profenophos (SP.) 10g/kg+2 ml/lit

5.73 (2.59)

6.07 (2.66)

5.90 (2.63)

5.07 (2.46)

4.80 (2.41)

4.93 (2.44)

5.42 (2.53)

T8 P. florescens (ST.) & Profenophos (SP.) 10g/kg+2 ml/lit

6.47 (2.73)

6.73 (2.78)

6.60 (2.76)

5.93 (2.63)

6.67 (2.77)

6.30 (2.70)

6.45 (2.73)

T9 Imidacloprid (ST.) & Profenophos (SP.) 5g/kg+2 ml/lit 5.80 (2.61)

6.53 (2.74)

6.17 (2.68)

6.33 (2.71)

7.07 (2.84)

6.70 (2.77)

6.43 (2.73)

T10 Control - 11.0 (3.46)

10.73 (3.43)

10.87 (3.44)

10.00 (3.32)

9.93 (3.31)

9.97 (3.31)

10.42 (3.38)

Table 2. Efficacy of microbial and chemical insecticides against Jassids infesting urdbean during Kharif 2010

NOTE: Figures in parentheses are transformed as X+1; DAS = Days after spraying, ST = Seed Treatment, Sp = SprayingDifference between Treatments CD = (P=0.05) = 0.06Difference between Period CD = (P=0.05) = 0.03

Population/Cage After 1st spray

Population/Cage After 2nd spray

S.No. Treatments Formulation

3 DAS 7DAS

Average

3 DAS 7DAS



3.00 (2.00)

2.97 (1.99)

3.07 (2.02)

3.00 (2.00)

3.03 (2.01)

3.00 (2.00)


3.27 (2.07)

3.23 (2.06)

3.20 (2.05)

3.13 (2.03)

3.17 (2.04)

3.20 (2.05)


3.00 (2.00)

3.03 (2.01)

3.13 (2.03)

2.87 (1.97)

3.00 (2.00)

3.02 (2.00)


3.40 (2.10)

3.33 (2.08)

3.13 (2.03)

3.00 (2.00)

3.07 (2.02)

3.20 (2.05)

T5 B. bassiana (ST.) & B. bassiana (SP.) 10g/kg+2 ml/lit 2.27 (1.81)

2.20 (1.79)

2.23 (1.80)

2.07 (1.75)

2.07 (1.75)

2.07 (1.75)

2.15 (1.77)

T6 P. florescens (ST.) & B. bassiana (SP.) 10g/kg+2 ml/lit 2.33 (1.83)

2.33 (1.83)

2.33 (1.83)

2.13 (1.77)

2.20 (1.79)

2.17 (1.78)

2.25 (1.80)

T7 B. bassiana (ST.) & Profenophos (SP.) 10g/kg+2 ml/lit 2.00 (1.73)

2.00 (1.73)

2.00 (1.73)

1.87 (1.69)

1.80 (1.67)

1.83 (1.68)

1.92 (1.71)

T8 P. florescens (ST.) & Profenophos (SP.) 10g/kg+2 ml/lit 2.20 (1.79)

2.27 (1.81)

2.23 (1.80)

2.00 (1.73)

1.93 (1.71)

1.97 (1.72)

2.10 (1.76)


2.33 (1.83)

2.30 (1.82)

2.07 (1.75)

2.00 (1.73)

2.03 (1.74)

2.17 (1.78)

T10 Control T10 - 4.40 (2.32)

4.20 (2.28)

4.30 (2.30)

3.93 (2.22)

4.33 (2.31)

4.13 (2.27)

4.22 (2.28)

with profenophos were most effective in restricting thewhitefly population i.e. 5.73 and 5.80 whiteflies / cage afterfirst spraying while 5.07 and 6.33 whiteflies / cage after secondspraying. When the average population of first and secondapplication of microbial and chemical insecticides werecompared the average population of whitefly was minimum in

combination of seed treatment with Beauveria bassiana andspray with profenophos (5.42 whiteflies / cage) than all othertreatments. The results of the present study are similar to thefinding of Alves et al. (2001), which proved that use ofBeauveria bassiana and imidacloprid reduced the white flypopulation and gave the highest average yield.

Singh & Chourasia : Efficacy of Bioinoculants in combination with insecticides against insect pests of blackgram 6 1

Effect on the population of jassid

Three days after application of treatment, seed treatmentwith B. bassiana + Spray with profenophos, P. florescens (seedtreatment) + profenophos (spray) and seed treatment withimidacloprid + profenophos (spray) were most effective interms of reducing the jassid population i.e. 2.0, 2.20 and 2.27jassids / cage after first spraying, respectively while, seedtreatment with Beauveria bassiana + spraying profenophos,P. florescens (seed treatment) + profenophos (spray) and seedtreatment with imidacloprid + profenophos (spray) were mosteffective in terms of reducing the jassid population i.e. 1.87,2.0 and 2.07 jassids / cage after second spraying, respectively.

The result showed that combination of seed treatmentwith Beauveria bassiana + Beauveria bassiana (spray) and

Table 3. Efficacy of microbial and chemical insecticides against Thrips infesting urdbean during Kharif 2010

Table 4. Effect of microbial and chemical insecticides the urdbean pod and grain damage by pod fly, pod borer, pod bug and yield

NOTE: Figures in parentheses are transformed as X+1; DAS= Days after spraying, ST = Seed Treatment, Sp = SprayingDifference between Treatments CD = (P=0.05) = 0.17Difference between Period CD = (P=0.05) = 0.07Interaction between Treatments X Periods CD = (P=0.05) = 0.24

Population/10 flower After 1st spray

Population/10 flower After 2nd spray

S. No. Treatments Formulation

3 DAS 7DAS

Average

3 DAS 7DAS



8.00 (3.00)

7.67 (2.94)

7.33 (2.89)

6.67 (2.77)

7.00 (2.83)

7.33 (2.89)


7.33 (2.89)

7.17 (2.86)

6.67 (2.77)

6.33 (2.71)

6.50 (2.74)

6.83 (2.80)


6.33 (2.71)

6.50 (2.74)

6.67 (2.77)

6.67 (2.77)

6.67 (2.77)

6.58 (2.75)


6.67 (2.77)

6.50 (2.74)

6.00 (2.65)

6.33 (2.71)

6.17 (2.68)

6.33 (2.71)

T5 B. bassiana (ST.) & B. bassiana (SP.) 10g/kg+2 ml/lit 4.00 (2.24)

3.67 (2.16)

3.83 (2.20)

3.00 (2.00)

3.33 (2.08)

3.17 (2.04)

3.50 (2.12)

T6 P. florescens (ST.) & B. bassiana (SP.) 10g/kg+2 ml/lit 4.33 (2.31)

4.33 (2.31)

4.33 (2.31)

3.33 (2.08)

3.67 (2.16)

3.50 (2.12)

3.92 (2.22)

T7 B. bassiana (ST.) & Profenophos (SP.) 10g/kg+2 ml/lit 3.33 (2.08)

3.00 (2.00)

3.17 (2.04)

2.67 (1.91)

2.67 (1.91)

2.67 (1.91)

2.92 (1.98)

T8 P. florescens (ST.) & Profenophos (SP.) 10g/kg+2 ml/lit 3.33 (2.08)

3.67 (2.16)

3.50 (2.12)

3.33 (2.08)

3.33 (2.08)

3.33 (2.08)

3.42 (2.10)


2.67 (1.91)

2.67 (1.91)

2.67 (1.91)

2.33 (1.83)

2.50 (1.87)

2.58 (1.89)

T10 Control - 10.67 (3.42)

10.00 (3.32)

10.33 (3.37)

9.33 (3.21)

10.00 (3.32)

9.67 (3.27)

10.0 (3.32)

seed treatment with Beauveria bassiana + spray withprofenophos were most effective in terms of reducing thejassid population up to 2.15 and 1.92 per cage, respectively,as compared to control treatment i.e. 4.30 and 4.13 jassids /cage, after 1st and 2nd spraying respectively. The averagepopulation in both 1st and 2nd spray treatments plot the minimumpopulation was recorded in treatment combination ofBeauveria bassiana (seed treatment) + profenophos (spray)i.e. 1.92. The control plot had recorded higher as compared toall the treatments. Our results are similar to the findings ofSatpute et al. (2001) who have reported the efficacy of theseed dresser insecticides, imidacloprid which reduced thejassid (Empoaska kerri) population significantly. Lal et al.(1985) have also used the several chemical insecticides forcontrolling the jassid population.

Pod damage (%) S.No. Treatments Formulation Pod fly Pod borer Pod bug

Grain Damage (%) Yield (q/ha.)

T1 Beauveria bassiana (ST.) 10g/kg 3.7 4.0 2.0 10.0 9.72 T2 Pseudomonas florescens (ST.) 10g/kg 3.0 3.7 2.3 10.3 8.68 T3 B. bassiana + P. florescens (ST.) 5g/kg+3g/kg 2.7 4.3 3.0 10.0 9.44 T4 Imidacloprid (ST.) 5g/kg 2.3 3.7 2.0 9.3 9.37 T5 B. bassiana (ST.) & B. bassiana (SP.) 10g/kg+2 ml/lit 4.3 2.7 2.7 9.0 9.93 T6 P. florescens (ST.) & B. bassiana (SP.) 10g/kg+2 ml/lit 4.0 4.0 2.3 9.7 9.79 T7 B. bassiana (ST.) & Profenophos (SP.) 10g/kg+2 ml/lit 3.3 4.3 1.7 9.7 11.59 T8 P. florescens (ST.) & Profenophos (SP.) 10g/kg+2 ml/lit 4.7 3.7 2.3 10.3 10.41 T9 Imidacloprid (ST.) & Profenophos (SP.) 5g/kg+2 ml/lit 2.3 4.3 2.3 9.3 10.83 T10 Control - 6.7 7.3 5.7 16.0 7.98

C.D.at 5% 1.6 1.5 1.4 2.3 0.091


Effect on the population of thrips

When different treatments were compared for theirefficacy against thrips, 3 days after spraying, seed treatmentwith imidacloprid + spray with profenophos was most effectivein reducing the thrips population upto 2.67 per 10 flower after1st spraying whereas seed treatment with imidacloprid wasmost effective in reducing the thrips population upto 6.33,seed treatment with Beauveria bassiana + spray withprofenophos reduced thrips population /10 flowers upto3.33 and 2.67 after 1st & 2nd spraying . Control plot recorded10.67 and 9.33 thrips/10 flowers after 1st and 2nd spraying,respectively. The average population in both 1st and 2nd spraytreatment plots the maximum population recorded in treatmentplot of Beauveria bassiana (seed treatment) i.e.7.33 andminimum population in imidacloprid (seed treatment) +profenophos (spray) i.e. 2.58. The control plot had recordedhigher as compared to all the treatments. When the microbialand chemical insecticides were compared, the averagepopulation of thrips was found lesser in combination of seedtreatment with imidacloprid and spray with profenophos with2.58 thrips/10 flowers was most effective than all othertreatments. Sreekanth et al. (2003) reported the imidaclopridschedules significantly reduced the Thrips palmi populationin the urd bean crop field. Nayak et al. (2004) also evaluatedthe efficacy of different combinations of insecticides amongstwhich imidacloprid as seed treatment against thrips was mosteffective.

Effect on per cent pod damage by pod borer

The per cent pod damage caused by pod borer indifferent treatment plots ranged from 2.7 per cent with treatmentcombination Beauveria bassiana (seed treatment)+ Beauveria bassiana (spray) to 4.3 per cent with treatmentcombination of Beauveria bassiana (seed treatment)+ P. florescens (seed treatment), which differed significantlyfrom damage recorded in control plot i.e. 7.3 per cent. Here allthe treatments showed comparatively lower pod damage incomparison to control treatment, but use of B. bassiana (seedtreatment) + Beauveria bassiana (spray), P. florescens (seedtreatment) + profenophos (spray), P. florescens (seedtreatment) + Beauveria bassiana (spray) and Beauveriabassiana (seed treatment), imidacloprid (seed treatment) andP. florescens (seed treatment) were most effective with lowper cent of pod damage i.e. 2.7, 3.7, 4.0,4.0, 3.7 and 3.7,

respectively (Table 4).All the microbial and chemical insecticides were effective

in increasing the yield over control. The combination ofmicrobial and chemical insecticides found better in efficacy tocheck the attack of insect pests and as a result of Beauveriabassiana + profenophos registered highest yield i.e. 11.59 q/ha followed by combination of seed treatment withimidacloprid + profenophos (spray), P. florescens (seedtreatment) + spray with profenophos which registered 10.83q/ha and 10.41 q/ha yield, respectively. In agreement withthese results Ganapathy and Karuppih (2004) reported theefficacy of new insecticide imidacloprid used as seed treatmentwhich gave the better yield.

REFERENCES

Alves SB, Silveira CA, Lopes RB, Tamai MA, Ramos EQ and Salvo SDe. 2001. Efficacy of Beauveria bassiana , imidacloprid andthiacloprid for the control of Bemisia tabaci and the incidence ofBGMV, Manejo Integradode Plagas 61: 31-36.

Anonymous 2009. Directorate of Economics and Statistics. Departmentof Agriculture and Cooperation.

Chandra U and Rajak DC . 2004. Studies on insect-pests on urdbean(Vigna mungo). Annals of Plant Protection Sciences 12 (1):213-214.

Chhabra KS and Kooner BS . 1985. Losses in summer mungbean due toinsect pest in Punjab, Indian Journal of Entomology 47 (1): 103 -105.

Ganapathy T and Karuppiah R. 2004. Evaluation of new insecticidesfor the management of whitefly (Bemisia tabaci Genn.), mungbeanyellow mosaic virus (MYMV) and urdbean leaf crinkle virus (ULCV)diseases in mungbean (Vigna radiata (L.) Wilczek). Indian Journalof Plant Protection 32: 35-38.

Lal SS, Yadav CP and Dias CAR. 1985. Insect pests of pulse crops andtheir management. Pesticides Annual Report. pp. 66-67.

Nayak SK, Ujagir R and Chhibber RC. 2004. Control of thrips andwhite fly infesting blackgram (Vigna mungo L.) by newer groups ofinsecticides. Environment and Ecology 22 (3): 538-542.

Satpute NS, Katole SR, Nimbalkar SA, Sarnaik DN and Satpute US.2001. Efficacy of imidacloprid and thiamethoxam seed treatmentagainst cotton jassid, Amarasca devastans Distant. Journal ofApplied Zoological Researches 12 (1): 88-90.

Sreekanth M, Sriramulu M, Rao RDVJP, Babu BS and Babu TR. 2003.Relative efficacy and economics of different imidacloprid schedulesagainst Thrips palmi (Karny), the vector of peanut bud necrosisvirus on mungbean (Vigna radiata L. Wilczek). Indian Journal ofPlant Protection31(1):43-47.


Studies on insecticide efficacy and application schedule for management of blisterbeetles on greengramK.S. PAWAR1, SARIKA P. SHENDE1, R.M. WADASKAR2 and A.Y. THAKARE1

1Department of Entomology, 2Pulses Research Unit, Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola, Maharashtra,India; E-mail: [email protected](Received : June 29, 2013 ; Accepted : November 18, 2013)

ABSTRACT

On account of its association with flowering phase, adult blisterbeetles inflict huge losses in short duration crops likegreengram. Management of blister beetles is difficult becauseof their wider host range and high mobility. The experimentswere conducted at Pulses Research Unit, Dr PDKV, Akola, duringKharif season 2012-2013. Evaluation of insecticides for themanagement of blister beetles revealed application ofcypermethrin 10 EC @ 0.01%, chlorpyriphos 50 EC +cypermethrin 5 EC @ 0.1375% and lambda cyhalothrin 2.5 EC@ 0.00375% as most effective insecticides in minimizing theadult blister beetles abundance; translating in higher grainyield of 9.8, 9.6 and 9.4 q/ha, respectively. The incremental costbenefit analysis revealed superiority of cypermethrin (1 : 12.2),alphamethrin 20 EC @ 0.05% (1 : 10.4) and lambda cyhalothrin(1 : 9.48). The experiment on standardisation of the applicationschedule for management of blister beetles revealed superiorityof insecticide, cypermethrin 10 EC @ 1ml/lit (I1) in terms oflowest beetles abundance per meter row length (mrl), highestyield per hectare and highest ICBR. It was followed by acephate75 SP @ 2 g/lit (I2). Efficacy of fenvalerate dust 0.4 % (I3) wasnot comparable with these superior treatments. Most effectivespraying schedule, (S3) three sprays - at 7 days interval withfirst application at bud initiation resulted in minimum countof blister beetles/mrl, followed by (S2) two sprays - at 10 daysinterval with first application at bud initiation (S2). Costeffectiveness of treatments revealed superiority of twoapplications of cypermethrin 10 EC 1ml/lit (I1XS2) and acephate75 SP 2 g/lit (I2XS2) at 10 days interval commencing firstapplication at bud initiation.

Key words: Application schedule, Blister beetle, Greengram andInsecticide efficacy.

Greengram, referred as the “Queen of Pulses”, is apopular short duration grain legume inIndia. It occupies thirdplace after chickpea and pigeonpea (Ved Ram et al. 2008).Greengram is extensively grown in all types of soil undervarying climatic conditions and play an important role inrainfed and irrigated agriculture (Ananthi and Vanangamudi,2013). The productivity of greengram is grossly affected byseveral insect pests, of which blister beetles in flowering phaseis the most destructive pest.(Shende et al. 2013). A lossinflicted by blister beetles in short duration crops with flowercluster tends to be manifold. Blister beetle is one of the mostserious pest of agricultural crops due to peculiar habit of

devouring flowers. The damage caused to flower is soextensive that there is no pod setting resulting into the lowyields (Dhingra and Sarup, 1992).

Mylabris phalerata has a wide host range whichincludes major pulses viz., greengram, cowpea and blackgram.Immense damage potential of 16.8 – 19.4 flowers per adult perday signifies its economic importance (Dhavan et al. 2013).Average per cent damage of flowers by blister beetles was 80per cent in greengram (Maheshwari, 1986), whereas, it wasupto 95 per cent in pigeonpea (Sharma et al. 2010). The yieldloss up to 25-30 per cent in greengram is reported by Boopathiet al. 2009.

Due to wider host range, high mobility and therobustness the management of blister beetles is difficult.Reports of severe damage of blister beetles and the failure ofrecommended insecticides in providing satisfactory controlare frequent (Singh et al. 1992). Also, review of literature doesnot throw sufficient light on aspects like insecticides and theirapplication frequency for the cost effective management ofadult blister beetles. Thus, present study was framed toevaluate newer insecticides along with the standardisation ofapplication schedule for effective management of blisterbeetles on greengram.


Two field experiments on evaluation of differentinsecticides efficacy and application schedule for managementof blister beetles on greengram were conducted during Kharifseason 2012-2013 at Pulses Research Unit, Dr. PDKV, Akola.‘PKV Green gold’ was used as test variety, sown at 30 X 10 cmspacing. Gross plot size of 2.1 X 4.2 m (7 rows of 4.2 m) and netplot size of 1.5 X 4.0 m (5 rows of 4.0 m) were used inassessment. The crop was raised under recommended packageof practices, except the plant protection measures.

The mean blister beetle abundance per mrl was basedon five mrl per treatment plot. Avoidable yield loss due toapplication of different treatments was derived by deductingthe yield of untreated control from respective treatments. Theincrease in grain yield was multiplied by wholesale marketprice of greengram. Cost of plant protection measures,including labour and sprayer charges were deducted fromthis amount to derive net profit per ha. Incremental Cost Benefit


Ratio (ICBR) was worked out as the ratio of net profit to thecost of plant protection.l Evaluation of insecticides for management of blister

beetles

A trial comprising of ten treatments including untreatedcontrol was replicated thrice in randomized block design toevaluate the efficacy of different insecticides against adultblister beetles on greengram. Application of differentinsecticidal treatments was made at 50 per cent floweringphase. The mean blister beetle abundance differential createdas effect of treatment per mrl was recorded daily upto 10 daysafter application of treatments.l Evaluation of insecticide application schedule for

management of blister beetles

A trial comprising of twelve treatments {Factor A(Spraying schedules) – 3 and Factor B (Insecticides) – 4},replicated thrice in factorial randomized block design wasconducted to evaluate the application schedule of insecticidesagainst blister beetles on greengram. Application ofinsecticides was taken at bud initiation stage as per scheduledapplication interval. The observations on blister beetlespopulation per meter row length of plant was recorded at 1, 3,5, 7, 10 and 14 days after first application of the insecticide.


Evaluation of insecticide efficacy (management trial)for management of blister beetles:

The data presented in table 1, regarding mean adultblister beetle population per mrl revealed statistical superiorityof chlorpyriphos 50 EC + cypermethrin 5 EC @ 0.1375% andcypermethrin 10 EC @ 0.01% with 0.0 beetles/mrl, one dayafter application of treatment. Methyl parathion 2% dust @20kg/ha (0.33 beetles/mrl) was superior treatment amongstthe dust formulations, whereas, maximum beetles populationwas recorded in untreated control (0.93 beetles/mrl). Two daysafter application of treatment, cypermethrin 0.01% (0.13 beetles/mrl), chlorpyriphos + cypermethrin 0.1375% (0.2 beetles/mrl),lambda cyhalothrin 0.00375% (0.33 beetles/mrl) andalphamethrin 0.05% (0.4 beetles/mrl) formed superior set oftreatments, on the contrary, untreated control plot hadabundance of 1.2 adult blister beetles/mrl.

Three days after application of fenvalerate 0.02% (0.4beetles/mrl) and cypermethrin 0.01% (0.6 beetles/mrl)abundance of beetles was restricted to minimal, whereas,maximum abundance of beetles was recorded in untreatedcontrol plot with 1.4 beetles/mrl. Superiority of lambdacyhalothrin 2.5 EC @ 0.00375% (0.6 beetles /mrl),chlorpyriphos + cypermethrin 0.1375% (0.73 beetles/mrl) andcypermethrin 0.01% (0.8 beetles/mrl) was evident in minimizingpopulation of beetles. Untreated control plot hadcontemporary abundance of 1.67 beetles/mrl, four days afterapplication of treatment.

Five days after application of treatment higher efficacyof synthetic pyrethroids viz., lambda cyhalothrin 0.00375%(0.6 beetles/mrl), alphamethrin 0.05% (0.73 beetles/mrl),cypermethrin 0.01% (0.8 beetle/mrl) and deltamethrin 0.0042%(0.93 beetles/mrl) was evident in terms of lower blister beetlespopulation as against 1.6 beetles/mrl in untreated control. Dataon population abundance of blister beetles, six days afterapplication of treatment, revealed superiority of cypermethrin0.01% (0.67 beetle/mrl), deltamethrin 0.0042% (0.8 beetles/mrl),chlorpyriphos + cypermethrin 0.1375% (0.93 beetles/mrl) andfenvalerate 0.02% (1.0 betles/mrl) in reducing beetlespopulation. Maximum beetles population of 1.87 beetles/mrlwas recorded in untreated control.

Application of deltamethrin 0.0042% (0.6 beetles/mrl)and chlorpyriphos + cypermethrin 0.1375% (0.8 beetles/mrl)were superior to manage the abundance whereas, applicationof deltamethrin 0.0042% (0.33 beetles/mrl) and fenvalerate0.02% (0.4 beetles/mrl) showed higher suppression ability,seven and eight days after application of treatment,respectively. Higher abundance of blister beetles populationwas recorded in untreated control, seven and eight days afterapplication with 1.8 and 1.6 beetles/mrl, respectively.

Alphamethrin 0.05% (0.13 beetles/mrl), deltamethrin0.0042% (0.2 beetles/mrl) and chlorpyriphos + cypermethrin0.1375% (0.2 beetles/mrl) expressed higher ability to restrictthe population of blister beetles, nine days after applicationof treatment, whereas, application of cypermethrin 0.01% (0.0beetles/mrl), chlorpyriphos + cypermethrin 0.1375%(0.07beetles/mrl) and lambda cyhalothrin 0.00375% (0.13beetles/mrl) formed the superior treatments, ten days afterapplication. Higher population of blister beetles was recordedin untreated control with 1.2 and 0.8 beetles/mrl, nine and tendays after application, respectively.

In nut shell it can be inferred that the treatment withcypermethrin 10 EC 0.01% and chlorpyriphos 50 EC +cypermethrin 5 EC 0.1375% were promising with consistentlylower blister beetle population counts per mrl. Application oflambda cyhalothrin 0.00375% and deltamethrin 0.0042%, beingthe next superior set, can also be used as an effectivealternative for the management of blister beetles on greengram.It was also evident that the dust formulations lagged to otherinsecticides in population suppression ability.

The present findings are supported by the observationsof Dhavan, 2012, who reported efficacy of cypermethrin (1ml/lit) at flowering phase for effective management of blisterbeetles on greengram. Chandel and Sood (1996) reportedpyrethroids viz., cypermethrin (0.002%), and deltamethrin(0.002%) as superior option to other insecticides. On rajmashthey also observed that, the application of cypermethrinrestricted blister beetle activity till 20 days after spraying.Similar observations were reported by Kakar et al. 1990 aboutcypermethrin @ 30 g ai/ha at flowering stage on french bean.Kumar et al., (2010) reported that lambda cyhalothrin (0.0025%)

Pawar et al. : Studies on insecticide efficacy and application schedule for management of blister beetles on greengram 6 5

Table 1. Effect of different treatments application on population abundance of adult blister beetlesMean Blister beetle count per mrl

Treatment details Rate of

application 1 DAS (*)

2 DAS (*)

3 DAS (**)

4 DAS (**)

5 DAS (**)

6 DAS (**)

7 DAS (**)

8 DAS (**)

9 DAS (*)

10 DAS (*)

T1 Chlorpyriphos 1.5% Dust 20 Kg/ha 0.73 (1.07)

0.93 (1.17)

1.33 (1.15)

1.4 (1.18)

1.33 (1.15)

1.6 (1.26)

1.4 (1.18)

1.2 (1.09)

1.13 (1.27)

0.4 (0.9)

T2 Fenvalerate 0.4% Dust 20 Kg/ha 0.6 (1.0)

0.8 (1.1)

1.2 (1.09)

1.33 (1.15)

1.4 (1.18)

1.8 (1.34)

1.6 (1.26)

1.4 (1.18)

1.0 (1.2)

0.4 (0.9)

T3 Methyl Parathion 2% Dust 20 Kg/ha 0.33 (0.87)

0.6 (1.0)

1.13 (1.05)

1.2 (1.09)

1.2 (1.09)

1.4 (1.18)

1.33 (1.15)

1.13 (1.05)

0.67 (1.03)

0.33 (0.87)

T4 Chlorpyriphos 50 EC+ Cypermethrin 5 EC

0.1375% 0.0 (0.71)

0.2 (0.8)

0.8 (0.89)

0.73 (0.85)

1.13 (1.05)

0.93 (0.95)

0.8 (0.89)

0.87 (0.92)

0.2 (0.8)

0.07 (0.73)

T5 Lambda Cyhalothrin 2.5 EC 0.00375% 0.13 (0.77)

0.33 (0.87)

0.73 (0.85)

0.6 (0.76)

0.6 (0.76)

1.2 (1.08)

1.13 (1.05)

0.8 (0.89)

0.4 (0.9)

0.13 (0.77)

T6 Alphamethrin 10EC 0.005% 0.2 (0.8)

0.4 (0.9)

0.67 (0.8)

1.0 (0.99)

0.73 (0.85)

1.13 (1.05)

0.93 (0.95)

0.67 (0.81)

0.13 (0.77)

0.2 (0.8)

T7 Cypermethrin 10 EC 0.01% 0.0 (0.71)

0.13 (0.77)

0.6 (0.77)

0.8 (0.87)

0.8 (0.87)

0.67 (0.8)

1.0 (0.99)

0.6 (0.77)

0.4 (0.9)

0.0 (0.71)

T8 Fenvalerate 20 EC 0.02% 0.4

(0.9) 0.6

(1.0) 0.4

(0.62) 0.93

(0.96) 1.0

(0.99) 1.0

(0.99) 1.2

(1.08) 0.4

(0.63) 0.33

(0.87) 0.33

(0.87)

T9 Deltamethrin 2.8 EC 0.0042% 0.73 (1.07)

0.73 (1.07)

0.87 (0.92)

1.13 (1.05)

0.93 (0.96)

0.8 (0.87)

0.6 (0.76)

0.33 (0.56)

0.2 (0.8)

0.2 (0.8)

T10 Control 0.93 (1.17)

1.2 (1.3)

1.4 (1.2)

1.67 (1.27)

1.6 (1.26)

1.87 (1.36)

1.8 (1.34)

1.6 (1.26)

1.2 (1.3)

0.8 (1.1)

F test Sig Sig Sig Sig Sig Sig Sig Sig Sig Sig SEm(+) 0.05 0.05 0.06 0.06 0.07 0.07 0.07 0.06 0.06 0.05 CD at 5% 0.16 0.15 0.17 0.19 0.21 0.21 0.21 0.17 0.18 0.15 CV % 10.33 9.00 11.07 11.00 11.57 11.91 11.31 11.02 10.67 10.82

Figure in parentheses indicate (**) square root value and (*) indicate (x + 0.5) square root transformed value, DAS - Day after spraying

as most effective treatment with maximum reduction in pestpopulation on pigeonpea. Boopathi et al. (2009) reported thatdeltamethrin 2.8 EC was more effective with cent per centreduction in adult population up to 7 days after spraying ongreengram. Similar findings are reported by Dikshit et al. (2001)on sponge gourd and Prasad and Dimri (1998) on okra. Sharmaet al. (2010) stated that most of the insecticides are not veryeffective against these beetles, but synthetic pyrethroids suchas cypermethrin 10 EC @ 1.0 ml/l or lambda cyhalothrin 5 EC@ 1.0 ml/l work reasonably well, which strengthens findingsof the present study.

These findings of the field study were strengthened bythe laboratory bioassay data of Shende et al. 2013 whoreported that chlorpyriphos 50 EC + cypermethrin 5 EC(0.1375%), lambda cyhalothrin 2.5 EC (0.00375%), alphamethrin20 EC (0.05%), cypermethrin 10 EC (0.01%), fenvalerate 20 EC(0.02%) and deltamethrin 2.8 EC (0.0042%) at field dose inflicted100 per cent mortality, within 24 hours. The data on relativetoxicity revealed that lambda cyhalothrin 2.5 EC, deltamethrin2.8 EC and cypermethrin 10 EC were 188.3, 113.0 and 56.5times more toxic with reference to chlorpyriphos dust,respectively.

Effect of various treatments (management trial) on yield,net profit and ICBR :

Data in table 2 revealed highest seed yield of greengramdue to application of cypermethrin 0.01% (9.8 q/ha). It was

followed by chlorpyriphos + cypermethrin 0.1375% (9.6 q/ha)and lambda cyhalothrin 0.00375% (9.4 q/ha). Lowest yield of6.6 q/ha was recorded in untreated control plot, indicatingimmense damage potential of blister beetles on greengram.Chandel and Sood (1996) reported that crop yield was greaterin plots treated with pyrethroids (cypermethrin 0.002%,fenvalerate 0.002%, deltamethrin 0.002%). Their findings weresupported by Dhavan, 2012 and Shende et al. 2013 whoconcluded that for the management of adult blister beetlespyrethroides proved most efficacious.

Net profit realised due to application of cypermethrin0.01% was highest (` 9760/ha), and was followed bychlorpyriphos + cypermethrin 0.1375% (` 8595/ha), lambdacyhalothrin 0.00375% (` 8358/ha). Application of fenvalerate0.4% dust secured lowest net profit of (` 2575/ha). Data onincremental cost benefit ratio revealed cost effectiveness ofcypermethrin 10EC @ 0.01% with highest ICBR of 1:12.2.It was followed by alphamethrin 0.05% (1 : 10.4) and lambdacyhalothrin 0.00375% (1 : 9.5). Lowest ICBR was estimated inapplication of fenvalerate 0.4% dust (1: 3.55). Other promisingtreatments can be arranged in descending order of costeffectiveness as fenvalerate 0.02% (1: 8.72) methyl parathion2% dust (1: 8.09), deltamethrin 0.0042% (1: 6.6), chlorpyriphos+ cypermethrin 0.1375% (1: 6.59), chlorpyriphos 1.5% dust(1: 3.8) and fenvalerate 0.4% dust (1: 3.55).

These finding are strengthened by Dhavan (2012) whoreported higher ICBR of 1 : 15.4 for cypermethrin (1ml/lit) and


1 : 6.6 for methyl parathion 2 % dust, whereas, Kumar et al.(2010) recorded higher ICBR for lambda cyhalothrin 0.025%(1:23.3) and fenvalerate 0.02% (1:16.18), in pigeonpea. Thesefindings are in corroboration with findings of present study.Similar observation for higher efficacy, yield, net monetaryreturns and ICBR was recorded for application of cypermethrinand chlorpyriphos + cypermethrin against blister beetles ongreengram (Anonymous, 2013).Standardisation of insecticide application schedule formanagement of blister beetles on greengram.

Effect of various treatments on blister beetle abundanceafter application of treatment is summarised in Table 3.l Blister beetle abundance one day after first spraying

Data on insecticide efficacy revealed superiority ofcypermethrin 10 EC @ 1ml/lit (I1) and acephate 75 SP @ 2g/lit(I2) with lowest abundance of 0.3 blister beetles/mrl and wassignificantly superior over control (0.7 blister beetles/mrl) (I0).The most effective insecticide application schedule was threesprays - at 7 days interval with first application at bud initiation(S3) with population of 0.4 blister beetles/mrl, and wasstatistically superior over rest of schedules. The insecticidesand application frequency interaction did not showed anystatistical differences among the blister beetles count/mrl.l Blister beetle abundance three days after first spraying

Lowest blister beetles abundance (0.1 adult blisterbeetles/mrl) was observed due to application of cypermethrin10 EC @ 1 ml/lit (I1), statistically superior over rest of thetreatments. Treatment of fenvalerate 0.4% dust @ 20 kg/ha(I3) was the least effective treatment with 0.5 blister beetles/mrl, still significantly superior over untreated control (0.7 blisterbeetles/mrl). Most effective insecticidal spraying schedule in

terms of higher efficacy against blister beetle abundance wasthree sprays commencing first application at bud initiationfollowed by (fb) 7 days after first application (DAFA) (fb) 7days after second application (DASA) (S3) with counts of 0.3blister beetles/mrl, significantly superior over control (I0) with0.5 blister beetles/mrl. Three sprays of cypermethrin 10 EC @1 ml/lit (I1 X S3) was the superior combination which recordedlowest population of 0.1 blister beetles/mrl and was statisticallysignificant over control with blister beetle abundance of 0.8beetles/mrl.l Blister beetle abundance five days after first spraying

Effect of insecticide treatments on blister beetleabundance five days after spraying revealed cypermethrin 10EC @ 1 ml/lit (I1) as most effective treatment with lowest countof 0.1 adult blister beetles/mrl. Insecticide treatment with lowestefficacy was application of fenvalerate 0.4% dust @20 kg/ha(I3) with count of 0.3 adult blister beetles/mrl and it was inturn statistically superior over control (0.7 adult blister beetles/mrl). Spraying schedule comprising of three sprayscommencing first application at bud initiation (fb) 7 DAFA(fb) 7 DASA (S3) was most effective with abundance of 0.2blister beetles/mrl, The most effective insecticide scheduletreatment with higher ability to restrict blister beetlespopulation was application of cypermethrin 10 EC @ 1 ml/litat bud initiation (fb) 7 DAFA (fb) 7 DASA (I1 x S3) with 0.1adult blister beetles/mrl and was statistically significant overrest of the treatments.l Blister beetle abundance seven days after first spraying

Data on effect of insecticidal treatment on blister beetlespopulation revealed significant superiority of treatmentcypermethrin 10 EC @ 1 ml/lit (I1) with 0.2 adult blister beetles/mrl, which was statistically superior over rest of the treatments.

*Price of insecticide:1.Chlorpyriphos 1.5% D @ ` 475/25 kg, 2.Fenvalerate 0 .4% D @ ` 363/25kg, 3. Methyl Parathion 2%D @ ` 500/25kg,4.Chlorpyriphos 50 EC+Cypermethrin 5 EC @ ` 504/lit,5.Lambda Cyhalothrin 2.5 EC @ ` 276/lit. 6.Alphamethrin 10 EC @ ` 326/lit,7.Cypermethrin 10 EC @ ` 250 /lit, 8.Fenvslerate 20 EC @ ` 320/lit, 9. Deltamethrin 2.8 EC @ ` 546/lit *No. of Labour required: For spraying :5 males, For dusting :-3 males*No. of spray pump equipment : 3, * Charges for hired spray pump,duster @ ` 25/day * Labour charges : ` 120/day,*Market price of greengram @ ` 3300/-

Table 2 Incremental cost benefit ratio in different insecticidal treatments in greengram.Sr. No.

Treatments Rate of application

Yield of greengram

(q/ha)

Increase in yield over

control (Rs/ha)

Cost of increased yield over

control (Rs/ha)

Cost of insecticide

(Rs/ha) (a)

Cost of labour charges (Rs/ha)

(b)

Cost of Plant protection

(Rs/ ha) (a+b=c)

Net profit

(Rs/ha) (d)

ICBR (d/c)

Rank

T1 Chlorpyriphos 1.5% Dust 20 Kg/ha 7.8 1.2 3960 380 435 815 3145 1 : 3.86 8 T2 Fenvalerate 0 .4% Dust 20 Kg/ha 7.6 1.0 3300 290 435 725 2575 1 : 3.55 9 T3 Methyl parathion 2% Dust 20 Kg/ha 8.9 2.3 7590 400 435 835 6755 1 : 8.09 5 T4 Chlorpyriphos 50 EC

+Cypermethrin 5 EC 2.5ml/lit 9.6 3.0 9900 630 675 1305 8595 1 : 6.59 7

T5 Lambda Cyhalothrin 2.5 EC 1.5ml/lit 9.4 2.8 9240 207 675 882 8358 1 : 9.48 3 T6 Alphamethrin 10 EC 0.5ml/lit 9.2 2.6 8580 82 675 752 7828 1 : 10.4 2 T7 Cypermethrin 10 EC 1ml/lit 9.8 3.2 10560 125 675 800 9760 1 : 12.2 1 T8 Fenvalerate 20 EC 1ml/lit 9.06 2.46 8118 160 675 835 7283 1 : 8.72 4 T9 Deltamethrin 2.8 EC 1.5ml/lit 9.1 2.5 8250 410 675 1085 7165 1 : 6.6 6 T10 Control - 6.6 -


The insecticide application frequency did not showedstatistically significant differences in blister beetles count/mrl. Trend of superior combination of insecticide andapplication schedule revealed superiority of three sprays ofcypermethrin 10 EC @ 1 ml/lit with first spray at bud initiation(fb) 7 DAFA (fb) 7 DASA (I1 x S3), which recorded 0.1 blisterbeetles/mrl. It was statistically significant over rest of thetreatments and untreated control with blister beetle abundanceof 0.8 adult blister beetles/mrl (I0).l Blister beetle abundance ten days after first spraying

Amongst the insecticides under evaluation, superiorityof cypermethrin 10 EC @ 1 ml/lit (I1) with count of 0.1 adult

l Blister beetle abundance fourteen days after firstspraying

Even after fourteen days of application cypermethrin10 EC @ 1ml/lit (I1) maintained statistical superiority with nopopulation of adult blister beetles. Next effective treatmentwas application of acephate 75 SP @ 2 g/lit (I2) with 0.1 adultblister beetles/mrl. The highest count of adult blister beetles/mrl was recorded in control (I0) where 0.5 adult blister beetles/mrl were recorded. The insecticide application frequency didnot revealed any statistical differences on blister beetlesabundance/mrl, whereas, the statistically superiorcombinations viz., cypermethrin 10EC @ 1ml/lit at bud

1 DAFA 3 DAFA 5 DAFA 7 DAFA 10 DAFA 14 DAFA One

spray Two

sprays Three sprays

One spray

Two sprays

Three sprays

One spray

Two sprays

Three sprays

One spray

Two sprays

Three sprays

One spray

Two sprays

Three sprays

One spray

Two sprays

Three sprays

Interaction of insecticides and application schedule

(S1) (S2) (S3) (S1) (S2) (S3) (S1) (S2) (S3) (S1) (S2) (S3) (S1) (S2) (S3) (S1) (S2) (S3) Control (I 0) 0.7 0.8 0.7 0.8 0.9 0.5 0.8 0.8 0.5 0.7 0.9 0.5 0.8 0.8 0.5 0.6 0.7 0.3 Cypermethrin 10 EC @ 1 ml/lit (I 1) 0.3 0.3 0.3 0.2 0.2 0.1 0.2 0.2 0.1 0.3 0.2 0.1 0.2 0.1 0.1 0.0 0.0 0.0 Acephate 75 SP @ 2 g/lit (I 2) 0.5 0.3 0.3 0.4 0.3 0.3 0.3 0.2 0.2 0.4 0.3 0.2 0.2 0.3 0.1. 0.1 0.1 0.0 Fenvalerate 0.4% dust @ 20 kg/ha (I 3) 0.5 0.5 0.5 0.7 0.5 0.4 0.5 0.5 0.3 0.5 0.4 0.3 0.5 0.4 0.3 0.3 0.2 0.2 F test NS Sig Sig Sig Sig Sig SE (m) + 0.05 0.05 0.07 0.08 0.08 0.07 CD at 5 % - 0.09 0.10 0.12 0.12 0.10 CV % 4.86 5.11 7.22 7.22 4.67 5.85

Table : 3 Interaction effect of insecticides and application schedule on blister beetle abundance/mrl

DAFA – Days after first application, fb – followed by

Table : 4 effect of insecticide and application schedule on blister beetle abundance per mrl.

DAT : days after treatment

Treatment details Mean Blister beetle abundance per mrl 1DAT 3DAT 5DAT 7DAT 10DAT 14DAT

Untreated control (I0) 0.7 0.7 0.7 0.7 0.7 0.5 Cypermethrin 1ml/lit (I1) 0.3 0.1 0.1 0.2 0.1 0.0 Acephate 2.0g/lit (I2) 0.3 0.3 0.2 0.3 0.2 0.1 Fenvalerate 0.4 % @ 20 kg/ha (I3) 0.5 0.5 0.4 0.4 0.4 0.2 SE(m)+ 0.04 0.04 0.06 0.04 0.04 0.04 CD at 5 % 0.05 0.06 - 0.07 0.07 0.06 One spray (S1) 0.5 0.5 0.4 0.4 0.4 0.2 Two sprays at 10 days interval (S2) 0.4 0.4 0.2 0.4 0.4 0.2 Three sprays at 7 days interval (S3) 0.4 0.3 0.2 0.2 0.2 0.1 SE(m)+ 0.02 0.02 0.02 0.04 0.04 0.04 CD at 5 % 0.04 0.04 0.05

blister beetles/mrl was evident even ten days after firstspraying, whereas, blister beetle counts of 0.7 /mrl wasrecorded in untreated control. The insecticide applicationfrequency lacked any statistical differences in blister beetlescounts/mrl.

Combinations of insecticide and spraying schedulerevealed treatment of cypermethrin 10 EC @ 1 ml/lit at budinitiation (fb) 7 DAFA (fb) 7 DASA (I1 x S3) as most promisingwith lowest count of 0.1 adult blister beetles/mrl. Higher blisterbeetle abundance was recorded in untreated control (I0) with0.8 adult blister beetles/mrl.

initiation (I1 x S1), cypermethrin 10EC @ 1ml/lit at bud initiation(fb) 10 DAFA (I1 x S2) and cypermethrin 10 EC @ 1ml/lit at budinitiation (fb) 7 DAFA (fb) 7 DASA (I1 x S3) and acephate 75 SP2 g/lit at bud initiation (fb) 10 DAFA (I2 x S3) were mostpromising with no population of adult blister beetles/mrl.l Effect of various treatments on pod bearing in

greengram

Effect of treatment on pod bearing (Table 5) revealedthat application of cypermethrin @ 1ml/lit (I1) registeredhighest number of pods (175.0 pods/10plants). Next effectivetreatment was application of acephate @ 2 g/lit (I2) with 171.7


pods/10 plants, at par with the former treatment. fenvalerate0.4% dust @ 20 kg/ha (I3) was least effective treatment (158.6pods/10 plants), statistically superior over untreated controlwith 100.3 pods/10 plants. Effect of various spraying schedulesand insecticide treatments and spraying schedulecombinations on pod bearing in greengram was statisticallynon-significant.l Effect of various treatments on yield of greengram

The data on effect of treatment on realization of yield(Table 5) revealed that application of cypermethrin @ 1ml/lit(I1) registered highest yield 1259.7 kg/ha. Next effectivetreatment, acephate 75 SP @ 2 g/lit (I2) registered yield of

1256.0 kg/ha and it was at par with former treatment and thesetreatments were significantly superior over control. (950.4 kg/ha). The insecticide schedule of two sprays (S2) firstapplication at bud initiation (fb) 10 DAFA recorded yield levelof 1266.1 kg/ha. Next effective spraying schedule was threesprays (S3) First spray at bud initiation (fb) 7 DAFA (fb) 7DASA with yield 1172.0 kg/ha. Least effective sprayingschedule was one spray at bud initiation (S1) with yield 1002.5kg/ha. Trend of statistically superior treatment combinationwas, cypermethrin 10 EC @ 1ml/lit at bud initiation (fb) 10DAFA (I1 x S2) (1417.0 kg/ha), followed by acephate 75 SP @ 2g/lit at bud initiation (fb) 10 DAFA (I2 x S2) with yield level of1380.3 kg/ha and acephate 75 SP @ 2 g/lit at bud initiation (fb)

Table 5 : Effect of insecticides and application schedule pod bearing and yield of greengram.

No. of pods/10 plants Yield (Kg/ha) One

Spray Two

Sprays Three Sprays

Factor A One

Spray Two

Sprays Three Sprays

Factor A Insecticides and Application schedule

(S1) (S2) (S3) Mean (S1) (S2) (S3) Mean Control (I0) 106.3 102.3 92.3 100.3 868.7 1032.7 950.0 950.4 Cypermethrin 10 EC @ 1 ml/lit (I1) 137.0 199.3 188.7 175.0 1068.3 1417.0 1282.7 1259.7 Acephate 75 SP @ 2 g/lit (I2) 127.0 195.0 193.3 171.7 1090.3 1380.3 1308.3 1256.0 Fenvalerate 0.4% dust @ 20 kg/ha (I3) 122.0 181.7 172.3 158.7 982.7 1234.3 1148.0 1121.7

Factor B Mean 123.1 169.6 161.7 1002.5 1266.1 1172.0 Factor A Factor B Interaction Factor A Factor B Interaction

F test Sig NS NS Sig Sig Sig SE(m)+ 10.76 9.32 18.64 43.26 37.46 74.72 CD at 5 % 15.72 - - 63.10 54.56 109.13 CV % 7.3 5.8 Table 6: Incremental cost benefit ratio in various insecticidal treatments in greengram

DAFA – Days after first application, DASA – Days after second application,Greengram @ Rs. 32.50/kg,Labour charges @ Rs. 150/male per day, Rs. 120/ female per day (labour required 3 male, 1 female/day)

Tr. No.

Treatment details Mean Yield

(kg/ha)

Increase in yield over

control (kg/ha)

Cost of increased

yield (Rs./ha)

Insecticide cost

(Rs./ha)

Labour charges (Rs./ha)

Sprayer charges (Rs./ha)

Labour + sprayer charges (Rs./ha)

Cost of plant protection

(Rs./ha)

Net profit (Rs./ha)

ICBR

T1 Cypermethrin 10 EC (1.0ml/lit)at bud initiation.

1068.3 117.9 3831.4 125 570 75 645 770 3061 1: 4.0

T2 Acephate 75 SP (2g/lit) at bud initiation.

1090.3 139.9 4546.4 500 570 75 645 1145 3401 1: 3.0

T3 Fenvalerate 0.4% dust (20kg/ha.) at bud initiation.

982.7 32.2 1047.2 500 570 75 645 1145 -98 1: -0.1

T4 Cypermethrin 10 EC (1.0ml/lit) at bud initiation (fb) 10 DAFA.

1282.7 332.2 10797.2 250 1140 150 1290 1540 9257 1: 6.0

T5 Acephate 75 SP (2g/lit) at bud initiation (fb) 10 DAFA .

1308.3 357.9 11631.4 1000 1140 150 1290 2290 9341 1: 4.1

T6 Fenvalerate 0.4% dust (20kg/ha.) at bud initiation (fb) 10 DAFA .

1148.0 197.6 6420.6 1000 1140 150 1290 2290 4131 1: 1.8

T7 Cypermethrin 10 EC(1.0ml/lit) at bud initiation (fb) 7 DAFA (fb) 7 DASA.

1417.0 466.6 15163.1 375 1710 225 1935 2310 12853 1: 5.6

T8 Acephate 75 SP (2g/lit) at bud initiation (fb) 7 DAFA (fb) 7 DASA.

1380.3 429.9 13971.4 1500 1710 225 1935 3435 10536 1: 3.1

T9 Fenvalerate 0.4%dust (20kg/ha.) at bud initiation (fb) 7 DAFA (fb) 7 DASA.

1234.3 283.9 9226.4 1500 1710 225 1935 3435 5791 1: 1.7

T10 Untreated control. (C1) 868.7 T11 Untreated control. (C2) 1032.7 T12 Untreated control. (C3) 950.0


7 DAFA (fb) 7 DASA (I2 x S3) with yield of 1308.3 kg/ha. Thebest treatment was at par with later treatments. Least effectivetreatment, fenvalerate 0.4% dust @ 20 kg/ha at bud initiationhad yield of 982.7 kg/ha as against yield level of 868.7 kg/ha incontrol (I0).l Effect of various treatments on yield, net profit and

ICBR

Data in table 6 suggests application of cypermethrin 10EC @ 1.0ml/lit at bud initiation (fb) 10 DAFA as most effectivetreatment with highest yield level of 1282.0 kg/ha, net monetaryreturn of ¹ 9257/ha and an ICBR of 1:6.0. Next effectivetreatment with higher returns was cypermethrin 10 EC @ 1.0ml/lit at bud initiation (fb) 7 DAFA (fb) 7 DASA with grain yieldof 1417.0 kg/ha, net monetary return of 12853 ¹ /ha and ICBRof 1:5.6. It was followed by treatment of acephate 75 SP @ 2 g/lit at bud initiation (fb) 10 DAFA with yield level of 1308.3 kg/ha, net monetary return of 9341 ¹ /ha and ICBR 1:4.1. Treatmentof fenvalerate dust 0.4% @ 20kg/ha at bud initiation was theleast effective treatment with negative ICBR (1:-0.1), suggestingyield procured in application of treatment could not justifythe cost of plant protection incurred. It is also inferred that,fenvalerate dust with other spraying schedule doesn’t qualifyas cost effective alternative for management of blister beetles,when compared to other promising treatments. Trend similarto present findings about cypermethrin and acephate efficacyand cost effectiveness was reported by Dhavan, 2012 andstrengthened by Anonymous, 2013.

It can be inferred from the findings of the present studythat for effective management of adult blister beetles, selectionof insecticides as well as the application time and applicationinterval are very crucial. Synthetic pyrethroides, cypermethrinin this case was very effective and was well supported by thereview. Application of acephate, also gave promising resultsunder field conditions and can be used as an alternative tothe pyrethroides. Targeting the adult blister beetles in theirmost favoured crop phenology, the flowering phase ensurescost effectiveness of the treatments. It is also evident fromthe data that the synthetic pyrethroides confers excellentprotection for a period of ten days, but, the flowering phase ingreengram persists for around twenty days. Hence, twosprays with an application interval of ten days registeredhighest efficacy and cost effectiveness for the treatments.

REFERENCES

Ananthi, K. and Vanangamudi Mallika. 2013. Physiologicalmanipulation for enhancing productivity in mungbean (Vignaradiata(L.) Wilczek) with value added humic acid formulation. J.of food legumes. 26(1-2) : 75-78.

Anonymous, 2013. Annual report of Pulses Entomology, PulsesResearch Unit, Dr. PDKV, Akola.

Boopathi, T., Pathak, K.A., Das, N. and Bemkaireima. 2009. Fieldbioefficacy of botanicals and common insecticide against blisterbeetle Mylabris pustulata and Epicauta sp. in greengram. J. of Eco-friendly Agric. 4(2): 194-195.

Chandel, R.S. and Sood, A.K. 1996. Chemical control of blister beetleMylabris macilenta (Marsh.) infesting rajmash in the dry temperatezone of H.P. Himachal Journal of Agric. Res. 22(1-2): 44-50.

Dhavan, S.P., 2012. Determination of economic threshold level andmanagement of blister beetles on mungbean M.Sc. thesis (unpub.)Dr. PDKV, Akola.

Dhavan, S.P., Pawar, K.S. and Wadaskar, R.M. 2013. Studies ongreengram blister beetle, Mylabris phalerata Pall. InsectEnvironment, 19(1): 3-4.

Dhingra, S. and Sarup, P. 1992. Detection of resistance in the blisterbeetle, Mylabris pustulata Thunb. to various insecticides evaluatedduring the last quarter century. J. Ent. Res. 16(3): 231-235.

Dikshit, A.K., Lal, O.P. and Kumar. R. 2001. Persistence and bioefficacyof insecticides in okra and sponge gourd. J. of Ent. Res. 25(2): 131-136.

Kakar, K.L., Bhalla, O.P. and Singh, A.K. 1990. Studies on pest complexof french beans and their control under mid-hill regions in H.P. Ind.J. of Pl. Prot. 18:71-75.

Kumar, S., Sandal, R. and Varma, K.S. 2010. Evaluation of someinsecticides and plant products against blister beetle, Mylabrispustulata (Thunberg) on pigeonpea. J. of Pest Management andEco. Zoo. 18(1/2) 271-276.

Maheshwari, U. K. 1986. Biological control of major agricultural pulsespest Mylabris pustulata. A new approach. Ind. J. of Ent. 48(4):381-387.

Prasad, C.S. and Dimri, D.C. 1998. Field evaluation of some insecticidesfor the control of blister beetle, Mylabris spp. on okra. J. of InsectSci. 11(2)188-189.

Sharma, O.P., Gopali, J.B., Yelshetty, S., Bambawale, O.M., Garg, D.K.and Bhosle, B.B. 2010. Pests of pigeonpea and their management,NCIPM, LBS building, IARI campus, New Delhi-110012, India. pp.37.

Shende, Sarika, Thakare, A.Y. and Wadaskar, R.M. 2013. Dose mortalityresponses of blister beetles against some insecticides. The Bioscan.8(3):1061-1064 (Supplement on Toxicology)

Singh, A., Sood, B.C. and Garten, S.L. 1992. Role of phsphamidon(Dimecron) in controlling blister beetles. Int. Pigeonpea Newsl.16: 22-24.

Ved Ram, Ali Masood, Misra, S.K. and Upadhyay, R.M. 2013. Studieson sulphur, zink and biofertilizers on yield and yield attributes andnutrient content at different growth stages in mungbean. J. of foodlegumes. 21(4): 240-242.


Ovipositional preference of bruchid (Callosobruchus Maculatus Fabricius) on podcharacter and pod maturityS. NANDINI and G. ASOKAN

Department of Agricultural Entomology, Centre for Plant Protection Studies, Tamil Nadu Agricultural University,Coimbatore, Tamil Nadu 641003, India; E- mail :[email protected](Received : February 12, 2013; Accepted : October15, 2013)

ABSTRACT

The ovipositional preference of bruchid, Callosobruchuschinensis on different pulse crops with their varying maturitywas conducted through free-choice test to investigate itsoviposition behaviour and progeny development under ambientlaboratory condition. Pods at different maturity stages, basedon color and morphological characters were used to study theegg laying potential of pulse beetle. Yellow coloured registeredmaximum (32.7 eggs/5pods) followed by half shattered pod(18.7 eggs). In greengram, yellow pods recorded maximumoviposition (37.3). There was 53.6 per cent more oviposition inyellow pods than the half shattered greengram pods. In redgram,yellow colour pods were the most preferred pods by pulse beetleand the maximum number (36.3 eggs) was laid per 5 pods inyellow pods followed by green pods, striped pods and halfshattered pods for egg laying and do not differ significantly .The lowest 3.3 eggs was recorded in immature pods followedby matured pods (8.7 eggs). Blackgram, greengram and redgramrecorded as high as 32.7, 32.7 and 36.3 eggs/5 pods, respectively.Pod characters, however, revealed insignificance differenceson maximum egg hatching. Undoubtedly, maximum adultemergence was recorded in half shattered pods of green gram(77.9 %), red gram (75.6 %) and black gram (73.6 %).

Key words: Pulses, Callosobruchus maculates, Ovipositionalpreference, Pod maturity character

Pulses are excellent source of easily digestible proteinswith low flatulence which complements the staple rice diet inIndia. These pulses are drought resistant and suitable fordry land farming and predominantly used as an intercrop withother crops. Among the pulses, blackgram (Vigna mungo),green gram (Vigna radiata), and redgram (Cajanus cajan) arethe major pulses, contributing much for the total production.In India, pulses are cultivated to an extent of 22.37 millionhectares with an average production of 14.66 million tonnesand an average productivity 655 kg per hectare during theyear of 2008-09 (Anonymous, 2010). The average yield ofpulses is very low, not only in India but also in tropical andsubtropical Asia .The improvement in production andproductivity of pulses is becoming difficult mainly due to theoccurrence of insect pests .Totally, 25 species of insect pestsattack pulse crops. Amongst, Callosobruchus spp. belongingto the family Bruchidae, commonly called as Pulse “beetle” or“Weevil” is a serious pest of pulses worldwide. And this pestharbour both in the field (before harvest) and during storage

(Rathore and Sharma, 2002). Damage in the field is usuallyinsignificant, however when the infested seeds are stored,the adults emerge and lay eggs on the neighboring seeds.The Secondary infestation can cause total damage of the seedlot within 3–4 months. Durairaj (1999) reported maximum fieldinfestation ranged from 7-10% which leads to 100 per centdamage at storage level. Infestation of bruchids on pulsesseeds results in weight loss, low germination and change ofnutrition in seeds and eventually making them unfit for humanconsumption, or agricultural and commercial uses (Lale andKabeh, 2004).To study the biology, pod character preferencefor egg laying and per cent infestation of the pest species areessential to minimize the incidence in the field level so as topopulation build up in storage level could bereduced. Severalworkers have studied the oviposition behaviour and progenydevelopment of C.maculatus and related pest species in seedsof different pulse crops (Ofuya, 1987). Considering theseriousness of the pest detailed study was needed tounderstand the ovipositional preference for pulse beetle Withthe careful consideration of above references, the presentstudy was aimed to investigate how ovipositional preferencefor Pulse beetle, Callosobruchus maculatus with reference topod colour at maturity could reduce the carry over populationof Pulse beetle in black gram, green gram and red gram.


The present investigation was carried out at Departmentof Agricultural Entomology, Centre for Plant Protection Studies,Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu,India during the period of 2008-2010.

Plant materials

Black gram, green gram, red gram seeds were sownseparately in earthen pots and grown under insecticide freecondition. After 30 days pods at different maturity stages, vizimmature pod, green pod, yellow pod, hairy pod and maturedpod were collected from those plants and used for thesestudies.

Ovipositional preference of pulse beetle on podcharacter and pod maturity

Collected pods were kept separately inside a petridishcontaining agar agar based on the need to maintain moisture;in addition, petridishes with different pod maturity characters

Nandini & Asokan : Ovipositional preference of bruchid, (Callosobruchus Maculatus Fabricius) on pod character 7 1

were arranged in a clean, circular, transparent plastic trough.At the centre of the trough five pairs per petridish newlyemerged pulse beetles, obtained from mass rearing coloniesmaintained at Insectary, TNAU, and CBE were introduced.After releasing the beetles, the trough was secured with muslincloth at top. Later adults were allowed to lay eggs on podsand number of eggs laid on each type of pod was recorded3rd day after release of beetles; the setup was continued upto adult emergence (Fig: 1, 2 and 3). The observation on numberof eggs laid, hatching and adult emergence were recordedand data were computed by using AGRESS software to findthe square root and arc sine values for mean number and,respectively.


The black gram pod characters were significantlyinfluencing the egg laying behaviour. Among the blackgrampod characters, yellow colour pods were the most preferredpods by pulse beetles and maximum 32.7 eggs/5pods wererecorded followed by half shattered pods (18.7 eggs). Thematured non hairy (13.7 eggs) and hairy pods (8.3 eggs) werenext in order (Table: 1). The immature pods, green hairy podsand green non hairy pods do not differ significantly with pulsebeetle egg laying and registered very low egg numbers. Theadult emergence in blackgram pods displayed a trend ofmaximum percent adult emergence (73.6%) in half shatteredpods which was significantly different among the various podcharacters. The other pod characters were at par with adultemergence. Among the five different types of green gram podslowest number of eggs were laid in immature pods (3.7 eggs)followed by green pods. All the five different pod typessignificantly differed with egg laying preference. The maximumnumber of eggs (37.3 nos.) was recorded in yellow pods from5 pods. There was 53.6 per cent more eggs laid in yellow podsthan the half shattered green gram pods. Adult emergencemanifested very minimum percent in green gram immature pods(8.3%) and the highest per cent adult emergence (77.9%) in

half shattered pods (Table: 1). Similarly in red gram, yellowcolour pods were the most preferred by pulse beetle and themaximum oviposition (36.3 eggs) was laid per 5 pods recordedin yellow pods followed by green pods, striped pods and halfshattered pods in order for egg laying and do not differsignificantly with pulse beetle egg laying. The trend of adultemergence in red gram pods displayed maximum per cent adultemergence (75.6%) in half shattered pods, which wassignificantly different among the various pod characters.There was less than 50 per cent adult emergence in otherpods viz., immature pods, green pods, striped pods, yellowpods and matured pods which were at par statistically.

Raina (1971) demonstrated the preference with moreon yellow pods of red gram than any other pods whenartificially infested. Similar findings was encountered withyellow pods which received more eggs 32.7 in black gram,37.3 in green gram and 36.3 eggs in red gram per five pods.However, the next preferred pods varied with crops such ashalf shattered in black gram (18.7 eggs), green gram (17.3 eggs)and green and striped pods (15.7 eggs) in red gram. The egglaying preference was very clear that more eggs were seen inthe order of yellow pods, half shattered, green and stripedpods. Especially in black gram, the non hairy pods registeredmore eggs than hairy pods. Unhusked soybean, Bengal gramand pea seeds were more preferred for oviposition than the oiltreated and dehusked seeds by pulse beetles (Ghosh, 1937).Ghosal et al. (2004) reported that seed characters hadsignificant positive correlation with oviposition of C. analisbut development period showed negative correlation.However, present investigations showed no significantdifference in the egg hatching either among the pod charactersor crops. Irrespective of the number of eggs laid, the egghatching was considerably fair on all pods. Though the egglaying was more in yellow pods and maximum adult emergencewas noticed in half shattered pods, probably avoiding thestrain in making the exit holes for adults which is made easy

Table 1: Influence of pod characters and pod maturity on oviposition, hatching and adult emergence of pulse beetle, C. maculatusin black gram, green gram and red gram (Laboratory study)

Mean of four replication.*Figures in parentheses are 0.5)+(x Transformed values.**Figures in parentheses are arcsine transformed values. Means followed by common letter (s) in a column (lower case) do not differ significantly by LSD (P=0.05).

*Mean no. of eggs/ 5 pods **Mean egg hatch (%) **Mean adult emergence (%) Treatment Black gram Green gram Red gram Black gram Green gram Red gram Black gram Green gram Red gram

Immature pod 3.7 (1.91)a 3.7 (1.91)a 3.3 (1.83)a 82.2 (68.83) 91.6 (78.90) 91.7 (78.90) 19.4 (22.30)a 8.3 (11.10)a 44.4 (41.73)a Green pod- hairy 4.7 (2.16)a - - 78.3 (62.29) - - 44.4 (41.75)b - - Green pod- non hairy 5.7 (2.38)b 12.3 (3.51)b 15.7 (3.96)c 94.4 (80.86) 94.5 (78.36) 97.9 (84.05) 46.7 (43.08)b 33.2 (35.18)b 37.1 (37.47)a Striped pod - - 15.7 (3.96)c - - 93.9 (77.86) - - 35.8 (36.69)a Yellow pod 32.7 (5.72)e 37.3 (6.11)e 36.3 (6.03)d 99.0 (85.57) 96.3 (79.14) 97.1 (81.59) 44.3 (41.73)b 41.1 (39.91)b 41.5 (40.11)a Mature pod - hairy 8.3 (2.89)b - 93.6 (77.55) - - 33.1 (35.09)a - - Mature pod – non hairy 13.7 (3.70)c 15.7 (3.96)c 8.7 (2.94)b 97.8 (83.90) 97.7 (83.90) 95.8 (82.00) 42.4 (40.64)ab 38.9 (38.61)b 35.4 (36.43)a Half shattered pod 18.7 (4.32)d 17.3 (4.16)d 15.3 (3.92)c 98.1 (84.34) 96.1 (80.20) 97.8 (83.90) 73.6 (65.19)c 77.9 (62.02)c 75.6 (60.42)b CD(P=0.05) 0.30 0.18 0.19 NS NS NS 13.07 13.98 9.63


by half opened as the adult emergence had negativecorrelation with seed hardness, thickness (Ghosal et al., 2004).In spite of higher egg hatching percentage the adult emergencewas very low in immature pods due to the moisture content asalready denoted by the findings that temperature below 14o Cresulted in death, particularly of immature stages of almost allinsect pests (Ghosh, 1937).

Thus it may be concluded that under field condition,yellow coloured pods were most preferred for oviposition bypulse beetle in all three crops like viz, black gram, green gramand red gram. Maximum egg hatching was found to be similarin all pod characters. Adult emergence was maximum in halfshattered pods when compared to other pod charactersnamely, immature pod, green pod, yellow pod, hairy pod andmatured pod. Proper monitoring and control measures shouldbe taken at maximum oviposition coinciding with podcharacters to reduce the field carry over population of pulsebeetle.

REFERENCES

Anonymous. 2010. Selected statistical data storage: where the loss iscaused. Pesticides, 4: 125.

Durairaj C. 1999. Integrated management for pigeon pea pod borercomplex - A review. In: The second Asia-Pacific Crop ProtectionConference, Feb. 18-20, 1999. The Retreat Erangal Beach,Mumbai, India, Pp. 100 - 115.

Ghosal TK, Dutta S, Senapati SK and Deb DC. 2004. Role of phenolcontents in legume Pulse beetle, Callosobruchus chinensis (L.).Journal of Agricultural Entomology 11: 21-38.

Ghosh CC. 1937. The pulse beetles (Pulse beetleae) of Burma. IndianJournal Agriculture Science 7: 395-412.

Lale NES and Kabeh JD. 2004. Pre-harvest spray of neem (Azadirachtaindica, A. Juss.) seed products and pirimiphos-methyl as methodsof reducing field infestation of cowpeas by storage bruchids in theNigerian Sudan Savannah. International Journal of AgricultureBiology 6: 987-993.

Ofuya II. 1987. Callosobruchus maculatus (Fab.) (Coleoptera:Bruchidae) oviposition behaviour on cowpea seeds. Insect Scienceand Its Applications 8 (1): 77-79.

Raina AK. 1971. Comparative resistance to three species ofCallosobruchus in a strain of Chick pea (Cicer arietinum L.). Journalof Stored Product Research 7: 213-216.

Rathore GS and Sharma RC. 2002. Evaluation of moth bean germplasmfor resistance to Pulse beetle. Indian Journal of Entomology 2(1):81-86.

Fig: 1. Preferential study set up forC. maculatus in black gram

Fig: 3. Preferential study set up for C. maculatus in red gram

Fig: 2. Preferential study set up forC. maculatus in green gram


Beneficial traits of endophytic bacteria from field pea nodules and plant growthpromotion of field peaS. NARULA, R.C. ANAND and S.S. DUDEJA

Department of Microbiology, CCS Haryana Agricultural University, Hisar 125 004, India; E- mail: [email protected](Received : October 04, 2012; Accepted : November 07, 2013)

ABSTRACT

Endophytic bacteria from nodules of field pea (Pisum sativumL.) being grown in CCS Haryana Agricultural University farmwere isolated. A total of 60 endophytic bacteria from surfacesterilized nodules of field pea were isolated. Screening for thepresence of beneficial traits showed that 63.3% of field peanodule endophytes were promoting root growth of pea seedlingsin water agar root growth promotion assay. A total of 38.3% ofendophytic isolates were phosphate solubilizers, 83.3% wereammonia producers and only 32% of isolates were producingorganic acid. Root growth assay showed that nodule endophytesPNE17 and PNE26 are better root growth promoters; PNE15,PNE24 are best P solubilizers; PNE5, PNE15 are best ammoniaproducers and PNE17 and PNE27 are the best organic acidproducers. Based on the presence of multiple beneficial traits,selected 41 endophytic nodule isolates were inoculated togetherwith Rhizobium leguminosarum biovar viciae strain PS 43 infield pea under pot culture conditions and showed enhancedplant growth, nodulation and nitrogen fixing parameters infield pea. Highest shoot dry weight and shoot N contents wasobserved in plants inoculated with PNE17 followed by PNE26,PNE77 and PNE15 along with Rhizobium. Symbiotic ratio (SR)based on shoot N contents varied from 0.70 to 3.10 indicatingvide variation in effectivity. Endophytic isolate PNE 15, PNE22, PNE 26 and PNE 77 showed SR ratio more than 2.0, whileisolate PNE 17 was the most effective endophyte with SR morethan 3.0.

Keywords: Beneficial characters, Endophytes, field pea, growthpromotion, nitrogen fixation, nodules, Rhizobium, symbiosis

Field pea (Pisum sativum L.) is a leguminous plant,belongs to family Fabaceae. Pea has a potential as highyielding, short duration crop with high crude protein contents.It is used for vegetable (green pods), seed, pasture, silage,hay and green manure in different parts of the world and it isone of the best food for human beings as well as feed foranimals. It may produce substantial yield without anyrequirement of nitrogenous fertilizers due to symbioticrelationship with nitrogen-fixing bacteria, Rhizobiumleguminosarum biovar viciae in its nodules. Rhizobia are themain endophytic bacteria present inside the nodules oflegumes. In addition to rhizobia, bacterial endophytes likeAgrobacterium, Bacillus, Curtobacterium, Enterobacter,Erwinia, Mycobacterium, Paenibacillus, Pseudomonas,Phyllobacterium, Ochrobactrum, Sphingomonas, Ensifer,Mesorhizobium, Burkholderia, Phyllobacterium and

Devosia are also present in nodules of legumes (Dudeja et al.2012). Microbial endophytes, mainly bacteria and fungi, areassumed to originate from the seeds, the roots surroundingenvironment and the aerial portion of plants. The soilparticularly the rhizosphere is an important source of rootendophytes (Gao et al. 2004 and Castro-Sowinski et al. 2007).A number of experimental evidences demonstrate that bacterialendophytes support the plant growth and development.Endophytes could play an important role to promote the plantgrowth by increasing nitrogen uptake, synthesis ofphytohormones like auxins, cytokinins or gibberlins,solubilisation of minerals, and iron chelation. They may alsohave antimicrobial activities by producing siderophores,antimicrobial metabolites or by competing for nutrients andspace. Thus, these endophytic bacteria have many beneficialcharacters for plant growth promotion and in improving soilnutritive health.

Available reports indicate improved plant yield, planthealth and nodulation when co-inoculated with plant growthpromoting rhizobacteria (PGPR), compared to inoculation withrhizobia alone (Grimes et al. 1984; Poloneko et al. 1987; Bulliedet al. 2002; Bai et al. 2002; Bai et al. 2003 and Rajendran et al.2008). Recent studies have shown the potential role ofendophytic bacteria in plant growth promotion. Few studieshave shown that simultaneous infection with rhizobia andsome plant growth promoting endophytic (PGPE) bacteria,increases nodulation and growth in legumes (Sturz et al. 1997and Saini et al. 2013a).

Therefore, the aim of this study was to screen the rootnodule endophytic bacteria isolated from the field pea, for thepresence of beneficial characters and to evaluate the effect ofselected endophytic nodule bacteria on the growth andnitrogen fixation of field pea plants, so as develop better plantgrowth promoting endophytes (PGPE) for crop productivity.


Isolation of endophytes from field pea: Nodule samplesof field pea (Pisum sativum), being grown under CCS, HaryanaAgricultural University, Hisar farm were collected. To isolateendophytes the nodules were surface sterilized by using 0.2%mercuric chloride and 70% ethanol and then rinsed with sterilewater four to six times (Vincent, 1970). Sterilized nodules wereused to isolate the endophytic bacteria as detailed earlier(Narula et al. 2013). A total of 60 endophytic isolates were


obtained from nodules of field pea and were designated PNEwith different isolate number. To avoid surface contaminantsnodules after surface sterilization were kept on media platesand if in any nodule any growth appeared then isolate fromthat particular nodule were discarded so as to ensure theisolation of only endophytic bacteria.

Screening of field pea nodules endophytes for thepresence of beneficial traits: Plant growth promoters or auxinsare produced by different bacteria which can also be assessedby using root growth promotion assay. Therefore, field pearoot growth promotion by all the 60 nodule endophytes wasassessed. To study root growth promotion in water agarplates, healthy field pea seeds (cv HFP4) were selected forgrowth promotion assay and sterilized with 0.2% HgCl2 and70% ethanol and after 5-6 washing with sterilized distilledwater seeds were transferred to 1.5% water agar plates. After24-48 h, three germinated seeds were transferred to the freshlyprepared 1.2% water agar plates in triplicates and inoculatedwith freshly grown endophytes (24-36 hours) from nodulesusing 0.25 ml of the test culture per seedling. The plates wereincubated in an incubator in dark condition at 28±20C for7 days. Observations were taken for root growth and rootlength was measured in comparison to un-inoculated control.

In all the 60 endophytic isolates, presence of beneficialtraits like P solubilization, ammonia and organic acidproduction was also assessed. Bacterial endophytes weretested by plate assay using Pikovskaya medium (PVK)(Pikovskaya 1948). Isolates were spotted on Pikovskaya’smedium plates in triplicate using sterile inoculating needle.On the basis of solubilization zone formed after 5 days ofincubation at 28±2ºC, different endophytes were categorizedto have better comparison among all the nodule endophytes.

Similarly bacterial nodule isolates were tested for theproduction of ammonia in peptone water. Freshly grown logphase growing cultures were inoculated in 10 ml peptone waterin each tube and incubated for 4 to 5 days at 28±2ºC. Nessler’sreagent (1 ml) was added in each tube. The development ofcolour from yellow to brownish orange was a positive test forammonia production (Cappuccino and Sherman 1992) and onthe basis of intensity of colour developed; the endophyteswere categorized into different categories.

Just qualitative assessment of organic acid productionby the nodule endophytic isolates was done by methyl redtest (Sambrook and Russell 2001). Bacterial endophytes wereinoculated in MR-VP broth and incubated for 5 days at 28±2ºC.It was then, observed for drop in pH using methyl red as anindicator dye. Isolates having the ability to produce organicacid gave orange to bright red colour while yellow colourindicated a negative reaction and on the basis of intensity ofcolour developed, the endophytes were categorized intodifferent categories.

Promotion of plant growth and nitrogen fixation of fieldpea: Promotion of plant growth and nitrogen fixation in fieldpea by bacterial endophytes from nodules was assessed underpot culture conditions using field pea (Pisum sativum L.) var.HFP4 as test host. Sandy soil was collected from dry land areaof CCS Haryana Agricultural University research farm. Thesoil analysis showed that it was sandy soil of pH 8.6; organicC 0.15 Kg hectare-1; electrical conductivity 0.53 dSm-1;phosphorus 6 Kg hectare-1; potassium 293 Kg hectare-1 with126 Kg hectare-1 as total N. Six to seven kg of soil was taken inearthern pots of 8 inch diameter. Seeds of field pea cv HFP4were surface sterilized by using 0.2% mercuric chloride and70% ethanol. Three replicates of each treatment total 45treatments, control, rhizobium

+PSB, PSB and 41 PNE treatments were kept and ineach pot uniform inoculation of Rhizobium leguminosarumbiovar viciae strain PS-43 was done. All the three seeds ineach and every 45 treatment were inoculated with 3 ml inoculumof log phase growing cells of 41 selected nodule endophyticisolates based on the presence of beneficial traits; one controlwithout any treatment was also kept. Pots were irrigated withtap water on alternate days or as and when required. After 60days of growth (duration of the variety 3-4 months), plantswere uprooted and observation on nodule numbers, nodule,root and shoot dry weight and total shoot N contents weredetermined by Kjeldahl’s method (Bremner 1965) after dryingthe samples in oven at 80ÚC till constant weight.

Symbiotic Ratio (SR) analysis: Symbiotic Ratio (SR)was used as one of the measure to discriminate betweennitrogen fixing efficiencies of different field pea noduleendophytes (Nandwani and Dudeja, 2013). The symbiotic ratiofor different field pea nodule endophytes was calculated as:

A symbiosis was considered to be ineffective when

symbiotic ratio based on total N contents was < 1.0,intermediate effectiveness if ratio in the range of 1 to < 2 andeffective when ratio was 2 to < 3 and highly effective whenratio was 3.


All the 60 endophytic isolates from field pea noduleswere screened for the presence of beneficial characters. Inwater agar root growth assay, the root lengths of field peawere measured after seven days of incubation after inoculation(Fig 1). Depending upon the extent of root growth promotion

Symbiotic Ratio(for total N contents) =

Total shoot N contents ofuninoculated plants

Shoot biomass after inoculationwith different field pea nodule endophytesSymbiotic Ratio

(for shoot biomass) =Shoot biomass of uninoculated plants

Total N contents of shoots after inoculationwith different field pea nodule endophytes

Narula et. al., : Beneficial traits of endophytic bacteria from field pea nodules and plant growth promotion of field pea 7 5

all the nodule endophytes were categorized in three groupsi.e. 2.2 > 5, 5 > 10 and 10 > 15 cm root length as shown in Table1. Root length of control was 2.2 cm. Out of 60 field pea noduleendophytes, 63.3% of isolates were promoting root growth offield pea plant as the root length produced by them was morethan that of control. PNE17, PNE26, PNE73 and PNE77 werethe highest root growth promoters. The root growthpromotion is the consequence of phytohormone production,mainly auxins and gibberellins. IAA is the main auxin producedby bacteria. Many researchers have reported that a goodproducer of auxins or gibberellins is also a good growth

promoter (Khan and Doty 2009; Sgroy et al. 2009 and Panchaland Ingle, 2011) and enhanced plant growth. Similarly,elsewhere most of the endophytic isolates were reported toproduce auxin specially IAA (Hung and Annapurna, 2004; Liet al. and Selvakumar et al. 2008). Contrary to this, lessernumber of auxin producers was found in the nodules of peanutplant (Taurian et al. 2010).

Phosphate solubilization by bacteria increases theavailability of free phosphorus to the plant and therefore, isan important character of the endophytes for the plant growthpromotion. All pea nodule endophytes were screened forphosphate solubilization activity on Pikovskaya’s medium.Depending upon the extent of P solubilization, the isolateswere categoried as good, moderate, low and very low Psolubilizers so as to compare the different isolates amongthemselves and results showed that 38.3% bacterial isolateswere phosphate solubilizers (Table 2). PNE15, PNE24 andPNE80C were good phosphate solubilizers and all otherisolates were low P-solubilizers (Fig 2). Similarly, endophyticbacteria of alfalfa plant were also shown to solubilize insolubleP (Stajkovic et al. 2009) and all the isolates from the nodulesof soyabean and kudzu were also reported to solubilizephosphate (Li et al. 2008 and Selvakumar et al. 2008).

Ammonia is an important metabolite produced by theendophytes as it fulfills the requirement of nitrogen for theplants. All the pea nodule endophytes were screened forammonia production. The isolates were grown in peptonewater and their ammonia producing activity was determined

Table 1. Root growth promotion of field pea seeds (Pisum sativum L.) var. HFP4 on water agar plate assay by nodule endophytes

Root length of un-inoculated control = 2.2 cm

Table 2. Phosphate solubilizing activity of field pea noduleendophytes

Phosphate solubilization

activity

Pea nodule endophytes Percent phosphate solubilizers

Good PNE15 1.7% Moderate PNE24, PNE80C 3.3%

Low PNE44, PNE72, PNE72A, PNE75, PNE76, PNE80A, PNE81, PNE82, PNE84, PNE92

16.7%

Very low PNE5, PNE13, PNE23, PNE23A, PNE38, PNE48, PNE80, PNE88B, PNE89C, PNE91

16.7%

Overall phosphate solubilizing pea nodule endophytes 38.3%

Ammonia producing

activity

Pea nodule endophytes

Percent ammonia producers

Very good PNE5, PNE15, PNE23A, PNE91 6.7% Good PNE4, PNE41, PNE72, PNE76, PNE78 8.3%

Moderate PNE9, PNE13, PNE18, PNE21, PNE23, PNE24, PNE27, PNE42, PNE44A, PNE72A, PNE73, PNE75, PNE77, PNE80C, PNE81, PNE82, PNE85, PNE87, PNE89

31.7%

Low PNE17, PNE25, PNE30, PNE38, PNE44, PNE46, PNE48, PNE50, PNE80, PNE80B, PNE84, PNE88A, PNE88B, PNE89C, PNE93

25%

Very low PNE20A, PNE31, PNE43, PNE45, PNE74, PNE83, PNE90

11.7%

Overall ammonia producing pea nodule endophytes 83.3%

Table 3. Ammonia producing activity of field pea nodule endophytes

Table 4. Organic acid producing activity of field pea noduleendophytes

Organic acid producing

activity

Pea nodule endophytes

Percent organic acid producers

Very good PNE17, PNE27, PNE46, PNE47, PNE50, PNE73, PNE87

11.7%

Good PNE18, PNE85 3.3% Moderate PNE5, PNE41, PNE88B, PNE89 6.7%

Low PNE20 1.7% Very low PNE21, PNE38, PNE43, PNE88A,

PNE89C 8.3%

Overall organic acid producing pea nodule endophytes 31.7%

Extent of root growth promotion (cm ) Pea nodule endophytes Percent root growth promoters > 10 TO <15 PNE17 PNE26 PNE73 PNE77 - 6.6%

PNE14 PNE15 PNE19 PNE23 PNE24 PNE25 PNE27 PNE41 PNE47 PNE50 PNE72 PNE75 PNE76 PNE80 PNE80A

> 5 TO <10

PNE87 PNE88B PNE89 PNE91 PNE93

33.3%

PNE5 PNE13 PNE16 PNE20 PNE20A PNE21 PNE43 PNE44 PNE44A PNE82

< 5

PNE83 PNE88A PNE92 PNE89C -

23.3%

Overall root growth promoters pea nodule endophytes 63.3%


by adding Nesseler’s reagent. All the isolates were categorizedas very good, good, moderate, low and very low ammoniaproducers according to the intensity of the colour, just tocompare among themselves qualitatively. Overall, 83.3% oftotal pea nodule endophytes were ammonia producers (Table3). Best ammonia producers were PNE5, PNE15, PNE23A andPNE91. Similarly, five endophytic bacteria isolated from alfalfanodules were tested and three of them were found positive

for ammonia production (Stajkovic et al. 2009). Endophyticisolates from legumes and non legumes were also shown toproduce ammonia (Kumar et al. 2013)

A number of organic acids are produced by the bacterialendophytes such as indole acetic acid, gibberellic acid,jasmonic acid and abscisic acid etc. These organic acidssupport plant growth by solubilization of minerals and

Table 5. Promotion of plant growth and nitrogen fixation in field pea by field pea nodule endophytes

Rhizo = Rhizobium leguminosarum biovar viciae strain PS-43, PSB = standard P solubilizing strain

Symbiotic ratio based on PNE isolates used as inoculants

Nodule numbers

plant-1

Nodule dry biomass (mg plant-1)

Shoot dry biomass (g plant-1)

N contents in shoots (mg plant-1) Shoot biomass Shoot N contents

Control 54 32 1.60 4.12 - - R.l. bv viciae 80 54 1.87 4.92 1.17 1.19 PSB 73 24 1.77 4.97 1.11 1.21 Rhizo +PSB 89 43 2.20 8.43 1.38 2.10 Rhizo +PNE5 64 38 1.80 5.84 1.13 1.42 Rhizo +PNE9 56 26 1.63 5.41 1.02 1.31 Rhizo +PNE13 36 29 1.57 5.06 0.98 1.23 Rhizo +PNE14 64 33 1.30 4.52 0.8 1.10 Rhizo +PNE15 81 51 2.13 9.69 1.33 2.35 Rhizo +PNE16 65 33 1.47 5.77 0.92 1.40 Rhizo +PNE17 89 65 2.57 12.59 1.61 3.10 Rhizo +PNE19 51 107 1.27 3.85 0.79 0.94 Rhizo +PNE20 77 63 1.97 6.32 1.23 1.54 Rhizo +PNE20A 57 27 1.27 4.62 0.79 1.12 Rhizo +PNE21 63 26 0.83 3.05 0.52 0.74 Rhizo +PNE22 70 35 2.03 8.55 1.27 2.10 Rhizo +PNE23 85 48 0.83 3.18 0.52 0.77 Rhizo +PNE24 57 28 1.47 6.80 0.92 1.65 Rhizo +PNE25 76 32 0.77 2.87 0.48 0.70 Rhizo +PNE26 68 48 2.27 10.51 1.42 2.55 Rhizo +PNE27 68 37 1.97 7.67 1.23 1.86 Rhizo +PNE41 61 28 1.17 3.79 0.73 0.92 Rhizo +PNE43 44 30 1.20 4.68 0.75 1.34 Rhizo +PNE44 57 26 1.50 5.90 0.94 1.43 Rhizo +PNE47 66 32 1.57 5.05 0.98 1.23 Rhizo +PNE50 81 36 1.70 6.61 1.10 1.60 Rhizo +PNE72 85 60 1.57 5.40 0.98 1.31 Rhizo +PNE73 69 54 1.67 6.82 1.04 1.66 Rhizo +PNE75 88 57 1.87 6.92 1.17 1.68 Rhizo +PNE76 68 21 1.03 3.90 0.64 0.94 Rhizo +PNE77 68 41 2.30 8.67 1.44 2.11 Rhizo +PNE80 102 61 2.00 6.41 1.25 1.56 Rhizo +PNE80A 55 35 1.70 3.72 1.1 0.91 Rhizo +PNE82 103 46 1.40 4.95 0.88 1.20 Rhizo +PNE83 123 52 1.83 7.19 1.13 1.75 Rhizo +PNE86 125 50 1.83 5.02 1.14 1.22 Rhizo +PNE87 111 71 1.90 7.25 1.19 1.76 Rhizo +PNE88A 43 56 1.17 4.74 0.73 1.15 Rhizo +PNE88B 47 41 1.23 4.78 0.77 1.16 Rhizo +PNE89 38 45 1.20 3.58 0.75 0.87 Rhizo +PNE89C 22 44 1.07 3.00 0.67 0.73 Rhizo +PNE90 23 46 1.07 4.12 0.67 1.0 Rhizo +PNE91 30 46 0.97 3.29 0.61 0.80 Rhizo +PNE92 23 70 1.37 4.67 0.86 1.13 Rhizo +PNE93 68 60 1.27 5.61 0.79 1.36 SE(m) 4.465 11.31 0.20 0.764 - - C.D. at 5% 12.563 31.83 0.57 2.149 - -


chelation of metals and by root growth promotion. Thereforeall the bacterial endophytes were screened for organic acidproduction by methyl red test. All the isolates were categorizedas very good, good, moderate, low and very low organic acidproducers according to color difference just to compare amongthemselves. The results of organic acid producing bacterialpea nodule endophytes indicated that 31.7% of bacterial peanodule endophytes showed organic acids production (Table4). Best organic acid producers were PNE17, PNE27, PNE46,PNE47, PNE50, PNE73 and PNE87 as they were giving darkred color on addition of methyl red.

Overall promotion of plant growth and enhancingnitrogen fixing parameters is the ultimate aim of any inoculantsdevelopment programme. Endophytic bacteria are known toenhance plant growth and nitrogen fixation. To study thisaspect plant growth promotion and enhancement in differentN2 fixing parameters was studied under pot house condition.Under pot culture conditions the results of plant growthpromotion and nitrogen fixation by using selected 41 field peanodule isolates as inoculants showed enhanced nodulation,root growth, plant growth and nitrogen content in shoot ofpea. There was a considerable visible difference in the shootlength of pea plants inoculated with nodule endophytic

isolates than that of un inoculated control (Fig 3). There wasa significant increase in nodule number, nodule dry weight,shoot dry weight and total shoot N when field pea seeds wereco-inoculated with nodule endophytes and Rhizobium thanRhizobium applied alone (Table 5). Nodule number in absolutecontrol was 54, whereas in other positive controls it variedfrom 73 to 89 nodule plant-1. But when co-inoculated with peanodule endophytes, nodulation ranged from 22 to 125 noduleplant-1. There was a significant increase in nodule dry weightthat ranged from 21 to 107 mg plant-1 and that of controlsvaried from 24 to 54 mg plant-1. Shoot dry weight of absolutecontrol was 1.6 g plant-1, whereas in other controls it was 1.77to 2.20 g plant-1, but when inoculated with endophytes frompea nodules, shoot dry weight ranged from 0.83 to 2.57 gplant-1. Highest shoot dry weight was observed in plantsinoculated with PNE17 followed by PNE26, PNE77 and PNE15.Total shoot N of un inoculated control was 4.12 mg plant-1,whereas in other positive controls was 4.92 to 8.43 mg plant-1.After inoculation with endophytes from pea nodules, totalshoot N contents ranged from 2.87 to 12.59 mg plant-1 andshowed a significant increase in total shoot nitrogen contents.A highest total shoot N content was in plant inoculated withPNE17 followed by PNE26 and PNE15.

Symbiotic ratio (SR) based on shoot dry biomass andshoot an N content was also determined. Though visibledifferences in growth were there, SR based on shoot drybiomass was less than 2.0 (Table 5). However SR based on

Control

Fig. 1: Water Agar assay showing root growth promotion byinoculation of pea nodule endophyte (PNE-19)

PNE 19

PNE 15 PNE 24

Fig 2: Phosphate solubilization zone formed by pea noduleendophytic bacteria

Fig 3. Promotion of plant growth in field pea under potculture conditions by field pea nodule endophytes


shoot N contents varied from 0.70 to 3.10 indicating thatinoculation with field pea nodule endophytes along withrhizobial inoculation resulted in ineffective association in caseof isolates PNE 19, PNE 21, PNE 23, PNE 25, PNE 41, PNE 76,PNE 80A, PNE 89 and PNE 89C as the SR ratio was even lessthan 1.0. Isolates were most effective with SR more than 2.0,this included isolate PNE 15, PNE 22, PNE 26 and PNE 77. PNE17 was the most effective endophyte with SR more than 3.0.Field pea nodule endophytes showed considerableenhancement in growth of plants when co-inoculated withrhizobia. Very few studies using bacterial endophytes (PGPE)as inoculants has been reported and in case of red cloverbacterial endophytes promoted growth more often whenapplied in combination with R. leguminosarum biovar trifoliithan applied singly (Sturz et al. 1997). Using PGPR asinoculants number of studies have shown that co-inoculationof all non-rhizobial strains with Ensifer meliloti was found topositively influence growth in alfalfa (Stajkovic et al. 2009);similarly in soybean (Bai et al. 2003) pigeon pea (Rajendran etal. 2008); bean (Phaseolus vulgaris L) (Lee et al. 2005) andSophora (Zhao et al. 2011). The chickpea root and noduleendophytes recently isolated in our laboratory showed veryencouraging results under field conditions (Saini et al. 2013a,b)

Legume nodules were thought to be the site of onlyrhizobia and bacteroids are the site of nitrogen fixation. Butnow large number of rhizobial as well as non rhizobial generahas been reported to be present in the nodules. These noduleendophytes perform different functions and could prove tobe good inoculants for enhancing crop productivity. Presenceof endophytic bacteria in the nodules of field pea plant isinfluencing the plant growth through many ways. Differentbeneficial traits were present in the field pea noduleendophytes. Root growth assay showed PNE17 and PNE26are better root growth promoters; PNE15, PNE24 are best Psolubilizers; PNE5, PNE15 are best ammonia producers andPNE17 and PNE27 are the best organic acid producers. Out ofall these isolates, PNE 17 was found to be the most efficient inplant growth promotion and nitrogen fixation under pot cultureconditions. Therefore, the efficacy of such isolate needs tobe further confirmed under field conditions, so that these canbe promoted as new bio inoculants for legumes to enhancetheir productivity.

REFERENCES

Bai Y, Aoust FD, Smith D and Driscoll B. 2002. Isolation of plantgrowth-promoting Bacillus strains from soybean root nodules.Canadian Journal of Microbiology 48: 230-238.

Bai Y, Zhou X and Smith DL. 2003. Enhanced soybean plant growthresulting from co-inoculation of Bacillus strains withBradyrhizobium japonicum. Crop Science 43: 1774-1781.

Bremner JM. 1965. Total nitrogen. In: Methods of soil Analysis. (ed.C.A. black). American Society of Agronomy, Madison. 2: 1149–1178.

Bullied J, Buss TJ and Vessey JK. 2002. Bacillus cereus UW85inoculation effects on growth, nodulation, and N accumulation ingrain legumes: field studies. Canadian Journal of Plant Science 82:291–298.

Cappuccino JC and Sherman N. 1992. Microbiology: a laboratory manual,Benjamin/Cummings Publishing Company, New York, pp. 125-179.

Castro-Sowinski S, Herschkovitz Y, Okon Y and Jurkevitch E. 2007.Effects of inoculation with plant growth-promoting rhizobacteriaon resident rhizosphere microorganisms. FEMS Microbiology276(1): 1–11.

Dudeja SS, Giri R, Saini R, Suneja-Madan P and Kothe E. 2012. Interactionof endophytic microbes with legumes, Journal of Basic Microbiology52: 248–260

Gao Z, Zhuang J, Chen J, Liu X and Tang S. 2004. Population ofendophytic bacteria in maize roots and its dynamic analysis. YingYong Sheng Tai Xue Bao 15(8): 1344–1348.

Grimes HD and Mount, MS. 1984. Influence of Pseudomonas putidaon nodulation of Phaseolus vulgaris. Soil Biology and Biochemistry16: 27-30.

Hung PQ and Annapurna K. 2004. Isolation and characterization ofendophytic bacteria in soybean (Glycine sp.). Omonrice. 12: 92-101.

Khan Z and Doty SL. 2009. Characterization of bacterial endophytesof sweet potato plants. Plant and Soil 322(1-2): 197–207.

Kumar V, Pathak DV, Dudeja SS, Saini R, Giri R, Narula S and Anand RC,2013. Legume nodule endophytes more diverse than endophytesfrom roots of legumes or non legumes in soils of Haryana, India.Journal of Microbiology and Biotechnology Research 3 (3):83-92

Lee KD, Bai Y, Smith D, Han HS and Supanjani. 2005. Isolation ofplant-growth-promoting endophytic bacteria from bean nodules.Research Journal of Agricultural and Biological Sciences 1(3): 232-236.

Li JH, Wang ET, Chen WF and Chen WX. 2008. Genetic diversity andpotential for promotion of plant growth detected in noduleendophytic bacteria of soybean grown in Heilongjiang province ofChina. Soil Biology and Biochemistry 40: 238-246.

Nandwani R and Dudeja SS. 2013. Functional diversity of nativemesorhizobial genotypes available in Indian soils of Haryana statewhich nodulates chickpea. Acta Agronomica Hungarica 61(3): 207-217.

Narula S, Anand RC, Dudeja SS, Kumar V and Pathak DV. 2013.Molecular diversity of root and nodule endophytic bacteria fromfield pea (Pisum sativum L.). Legume Research 36(4): 344-350

Panchal H and Ingle S. 2011. Isolation and characterization ofendophytes from the root of medicinal plant Chlorophytumborivilianum (Safed musli). Journal of Advances in DevelopmentResearch 2 (2): 205–209.

Pikovskaya RE. 1948. Mobilization of phosphorus in soil in connectionwith vital activity of some microbial species. Microbiologiya. 17:362-370.

Polonenko DR, Scher FM, Kloepper JW, Singleton CA, Laliberte Mand Zaleska I. 1987. Effects of root colonizing bacteria onnodulation of soybean roots by Bradyrhizobium japonicum .Canadian Journal of Microbiology 33: 498-503.

Rajendran G, Sing F, Desai AJ and Archana G. 2008. Enhanced growthand nodulation of pigeon pea by co-inoculation of Bacillus strainswith Rhizobium spp. Bioresource Technology 99: 4544-4550.


Saini R, Kumar V, Dudeja SS and Pathak DV 2013a. Beneficial effectsof inoculation of endophytic bacterial isolates from roots and nodulesin chickpea. Acta Agronomica Hungarica (in press)

Saini R, Dudeja SS, Giri R and Kumar V, 2013b. Isolation, characterizationand evaluation of bacterial root and nodule endophytes fromchickpea cultivated in Northern India. Journal of Basic Microbiology53: 1-8

Sambrook J and Russell DW. 2001. Molecular Cloning: A LaboratoryManual, Vol. 1, Cold Spring Harbor, New York.

Selvakumar G, Kundu S, Gupta AD, Shouche YS and Gupta, HS. 2008.Isolation and characterization of non rhizobial plant growthpromoting bacteria from nodules of kudzu (Pueraria thunbergiana)and their effect on wheat seedling growth. Current Microbiology56: 134-139.

Sgroy V, Cassán F, Masciarelli O, Papa MF, Lagares A and Luna V. 2009.Isolation and characterization of endophytic plant growth-promoting (PGPB) or stress homeostasis-regulating (PSHB)bacteria associated to the halophyte Prosopis strombulifera. AppliedMicrobiology and Biotechnology. 85(2): 371–381.

Stajkovic O, De Meyer S, Milicic B, Willems A and Delic, D. 2009.Isolation and characterization of endophytic non-rhizobial bacteriafrom root nodules of alfalfa (Medicago sativa L.). BotanicaSERBICA. 33(1): 107-114.

Sturz AV, Christie BR, Matheson BG and Nowak J. 1997. Biodiversityof endophytic bacteria which colonize red clover nodules, roots,stems and foliage and their influence on host growth. Biology andFertility of Soils 25: 13-19.

Taurian T, Anzuay MS, Angelini JG, Tonelli ML, Ludueña L, Pena D,Ibáñez F and Fabra A. 2010. Phosphate-solubilizing peanut associatedbacteria: screening for plant growth promoting activities. Plantand Soil 329: 421-431.

Vincent JM. 1970. A manual for the practical study of root nodulebacteria . IBM Handbook No. 15. Oxford: Blackwell ScientificPublications.

Zhao L, Xu Y, Sun R, Deng Z, Yang W and Wei G. 2011. Identificationand characterization of the endophytic plant growth promoterBacillus cereus strain MQ23 isolated from Sophora alopecuroidesroot nodules. Brazilian Journal of Microbiology 42: 567-57.


Effect of temperature-tolerant rhizobial isolates as PGPR on nodulation, growthand yield of Pigeonpea [Cajanus cajan(L) Milsp.]SIMRANJIT KAUR and VEENA KHANNA1

Department of Microbiology and 1Department of Plant Breeding and Genetics Punjab Agricultural,Ludhiana-141004, India; Email: [email protected](Received : June 29, 2013 ; Accepted : November 18, 2013)

ABSTRACT

Plant-growth promoting rhizobacteria in conjuction withefficient Rhizobium, can affect the growth and nitrogen fixationin pigeonpea (Cajanus cajan (L) Milsp.) by inducing efficientsymbiosis and plant growth. In this study out of 15 rhizobialisolates, isolated from different pigeonpea growing fields, fourisolates i.e LAR-2, LAR-3. LAR-4 and LAR-8 were found togrow upto 45°C. Similarly, PGP traits such as IAA and P-solubilizing ability were evaluated at 35°C and 40°C and basedon these results LAR-2, LAR-3, LAR-4, LAR-8 were selected asco-inoculant with recommended Rhizobium LAR-6 for studyingtheir efficacy under field condition for symbiotic parametersand growth of pigeonpea. The seeds were treated with Rhizobiumalone or in combination with selected temperature tolerantrhizobial isolates (as PGPR). The rhizobial isolates showedpositive synergistic effect with recommended Rhizobium (LAR-6) in dual-inoculation, which resulted in a significant increasein number and dry weight of nodules over Rhizobium aloneand un-inoculated control. Maximum number and dry weightof nodules was recorded with treatment LAR-6+LAR-2 (37.4 noand 50mg/plant) followed by LAR-6+LAR-8 (30 no, & 48.7 mg/plant) as compared to Rhizobium LAR-6 alone (20.4 no, 31.4/plant) and control (8 no, 10.8 mg/plant). The same trend wasevident with yield attributing traits and N–content in seeds,The positive interaction between co-inoculants wassubsequently reflected in grain yield, LAR-6+LAR-2 inoculationexhibited 12.1% increase over control whereas with Rhizobiumalone it was 8.3%. Thus dual inoculation regime significantlyenhanced all symbiotic and growth parameters and also affectedyield.

Key words: Auxins, Dual-inoculants Nodulation, Synergism,Symbiosis, Temperature

India is the largest producer, consumer and importer ofpulses. Pulses occupy an area of 67.8 million hectares andcontribute 22% to world’s food basket (Reddy et al. 2012).India has the distinction of being world’s largest producer ofpigeonpea (93%), chickpea (68%) and of lentil (32%)(FAOSTAT 2011). Pigeonpea is an important nitrogen fixingpulse crop. One of the major factors adversely affectingpigeonpea productivity is poor nodulation in fields due toprevalence of inefficient and poor nodulating native rhizobia(Marsh et al. 2006). High soil temperature during summer, lownutrients availability in soil and moisture stress during plantgrowth have been identified as major constraints for improvingnodulation and nitrogen fixation in pigeonpea crop under semi-

arid rain fed agro-ecosystem. Therefore inoculation withefficient strains of Rhizobium possessing high temperaturetolerance and effective plant growth promoting traits athigher temperature would be required for increasingnodulation and their functioning for enhancing N-fixation andimproving plant growth and productivity (Singh et al. 2013,Gray and Smith. 2005). Thus the present study was undertakenfirstly to isolate and screen free living rhizobia from pigeonpearhizosphere for temperature tolerance and then to assess theirPGP traits at higher temperature and to evaluate theirperformance in terms of nodulation, growth and yield ofpigeonpea under field condition.


Collection and isolation of isolates: A total of 11pigeonpea rhizospheric soil samples were collected fromdifferent locations of Punjab and UP and rhizobial isolateswere selected on CRYEMA media. All isolates were furthertested for growth characteristic on YEMA-BTB media andcharacterized based on morpho-physiological and biochemicaltraits.

Selection of high temperature and salinity tolerantisolates: Rhizobial isolates were inoculated in YEMA brothand incubated at three different temperatures 35°C, 40°C, 45°Cand their growth measured in terms of optical density at 540nm at two hourly intervals. Salinity tolerance was evaluatedby following growth in the media amended with differentconcentrations of NaCl (1-5%) and growth checked after 48hours.

Evaluation of PGP traits at different temperature:Rhizobial isolates were tested for their potential for IAAproduction (Gordon and Weber 1951), P-solubilization ability(Jackson’s 1973) at two temperatures (35°C and 40°C).Siderophore production was estimated by Schwyn andNeilands’ method (1987).

Field experimental: The field experiment wasconducted in kharif of 2012 using pigeonpea variety PAU881 at research farms of Punjab Agricultural UniversityLudhiana (30° 56’N, 72° 52’E and altitude 247 m) having sandy-loam soil (pH 8.2). Soil had organic carbon (0.03%), availableN (105 kg/ha) available P (16.8 kg/ha) and K, (291kg/ha). Sixtreatments comprising un-inoculated control, recommendedRhizobium for pigeonpea LAR-6 alone and in combination

Kaur & Khanna : Effect of temperature-tolerant rhizobial isolates as PGPR on nodulation, growth and yield of Pigeonpea 8 1

with 4 selected rhizobial isolates. Seeds were treated as pertreatment before sowing. Treatments were laid down inrandomized blocks in triplicate, plot size 9m2 row to row 50 cm,crop was sown on 31 May 2012 and raised as perrecommended package of practices. Sampling for number ofnodules, nodule dry weight, root and shoot biomass for alltreatments was done at 45 DAS. Five plants were randomlyuprooted from each experimental plot by digging 15cm aroundthe plant washed with clean water to remove attached soilfrom roots and nodules. The nodules were counted and ovendried at 60°C for 48 hours and weighed. The roots and shootsof plants were also separated, oven dried at 60°C till constantweight. Leghaemoglobin and chlorophyll content was alsodetermined. At maturity plant height, number of pods, primaryand secondary branches were counted by taking 5 plantsfrom each plot, grain yield from each replication recorded, N-content of grains and straw (McKenzie and Wallace 1954)also determined. For statistical analysis software CPCS1 wasused.


Isolation and selection of rhizobial isolates: A total of15 rhizobial strains were isolated from pigeonpea rhizosphericsoil collected from different locations. All 15 isolates wereselected on CRYEMA media and purified isolates of pigeonpearhizobia were maintained on YEMA slants at 4°C. All isolateswere morphologically and biochemically tested (Table 1) andidentified as Rhizobium spp. Ten rhizobial isolates were foundto grow fast and other 5 strains were slow grower (Table 1).LAR-6 recommended Rhizobium (GenBank accession no.JX120574) also evaluated as fast growing.

Temperature and salinity tolerance: All 15 rhizobialisolates were screened for growth at 35°C, 40°C, 45°C. Four ofthe Rhizobial isolates LAR-2, LAR-3. LAR-4, LAR-8 and LAR-6 showed maximum growth (at 45°C 0.71, 0.70, 0.81, 0.72, 0.81measured in terms of optical density λ 540) although highvariability in growth was observed (Fig.1). Isolates RXI andRX2 showed relatively less growth even at 40°C. Nehra et al.(2007) reported four pigeonpea rhizobial strains (HR-3, HR-6,HR-10 and HR-12) to be temperature tolerant, highly efficientfor all the symbiotic parameters, and thus having the potentialto be used as bio-inoculants in the North-Western regions ofIndia. Marsh et al. (2006) also reported that out of 12 rhizobialstrains isolated from pigeonpea rhizosphere, three could growup to 44°C, He also reported that temperature has profoundeffect on growth and tolerance among Rhizobium strains.

The salinity assay revealed that all the isolates couldgrow at 3% salinity, 73.3% could grow at 4% and only 34% ofthe isolate could tolerate 5% of NaCl concentration. Rhizobialisolates LAR-2, LAR-4, LAR-8, RX1, RG2, could grow upto5% salinity and recommended culture LAR-6 was also fastgrowing and showed profuse growth up to 40°C, and could

tolerate 5% NaCl. Numerous studies have shown that salinitystress decreases nitrogenase activity and N2-fixation. Hencethe use of temperature and salt tolerant rhizobia would help

Fig. 1. Relative temperature-tolerance of rhizobial isolates

establish effective symbiosis (Belal et al. 2013).Evaluation of PGP traits: Four rhizobial isolates

showing temperature and salinity tolerance along with LAR-6 were evaluated for PGP traits at 35°C and 40°C. InterestinglyIAA production was found to be higher at 40°C as comparedto 35°C (Table 2), However, P-solubilization did not show anysignificant differences at both the temperatures. MaximumIAA was produced by LAR-6 (28 µg/ml) followed by LAR-8(25.8µg/ml) and LAR-2 (25.2 µg/ml) at 35°C and at 40°C (Table3) maximum IAA was again recorded with LAR-6 (32.3µg/ml)followed by LAR-2 (31.1µg/ml), LAR-8 (29 µg/ml). Alikhaniand Yakhchali (2009) reported 74% of the rhizobial strainscapable of producing IAA belonged to the fast growing,rhizobia group these results are in confirmation with the presentfindings. Several microorganisms including rhizobia have beenreported to synthesize auxins ( Zahir et al. 2005) and contributein growth and yield parameters (Khanna et al 2011). Deshwalet al (2013) also reported 96% symbiotic nitrogen fixing rhizobiaproduced IAA. LAR-2 exhibited higher P-solubilizing abilityat 35°C and 40°C (10.0, 8.1mg/100ml) followed by LAR-6 (8.9,8.0 mg/100ml) and LAR-8 (8.7, 7.9 mg/100ml). Effectivemicrobial inoculants play an important role in increasing theavailability of soil P to plant roots, and increasing Pmobilization in soil (Alikhani and Yakhchali 2009). Siderophoresare ferric specific ligands that are iron transporter which helpenhance competitive survival of rhizobia. Rhizobial isolatesLAR-6, LAR-8, LAR-2 (2.2, 2.0,1.9 cm.) showed highestproduction of siderophores as compared to other isolates.Khan et al. (2012) reported that some rhizobia not only produceand import their own siderophores but are also benefited byutilization of heterologous siderophores (produced by othermicroorganisms) present in soil. Out of 15 rhizosphericrhizobial isolates 4 isolates ( LAR-2, LAR-3, LAR-4, and LAR-8) selected on the basis of temperature-tolerance and PGPtraits (Table 3) were used as inoculants along withrecommended Rhizobium (LAR-6) in field study.

Effect of dual-inoculation of rhizobia on symbioticparameters

Nodulation: Nodulation plays an important role inpromoting plant growth and soil health. Data on nodule


numbers as shown in Table 4 reveals that all the treatmentssignificantly enhanced number of nodules as compared tocontrol, However, dual Rhizobium inoculation that is LAR -06+ LAR-02 showed highest number of nodules (37 nn/plant)followed by LAR-6+LAR-8 (30 nn/plant) after 45 DAS whichwere significantly higher as compare to control (8 nn/plant).Siddiqui (2009) reported that increase in growth and yield andthe number of nodules per root system is significantly higherin plants inoculated with Rhizobium spp. as compared toplants without Rhizobium inoculation under field condition.

Significantly higher nodule dry weight was recordedwith LAR-6 + LAR-2 (50.0 mg) followed by LAR-6 + LAR-8(48.7 mg) and LAR-6 + LAR-3 (31.0 mg) as compared to control(10.8 mg), it is well documented that fresh and dry weight ofnodules indicates the development of nodules (Singh et al2010). Tilak et al. (2006) reported nodules occupied by theintroduced efficient rhizobial strain results in positive effect

(4.4gm). Data on root dry weight shows that LAR-6 +LAR-8and LAR-6 + LAR-2 showed highest (0.61gm, 0.60gm/plant)root dry weight than other treatments and control (0.46gm).This may be attributed to their high efficiency to produceIAA by inoculant which is an important plant growthpromoting hormone.

Effect on yield attributing traits: Plant growthparameters such as plant height, number of primary branches,secondary branches, total number of pods/plant Table 6 showsthat LAR-6 + LAR-2 and LAR-6 +LAR-8 showed greaternumber of primary branches (25 and 24/plant) as compared toother treatments and un-inoculated control. Secondarybranches were also showed significantly higher as comparedto control highest number of secondary branches beingrecorded in treatment LAR-6+LAR-8 (45/plant) followed byLAR-6+LAR-2 (43.7/plant). A significant effect ofco-inoculations was also observed in number of pods/plantLAR-6 + LAR-2 showed more number of pods/plant (69/plant),followed by LAR-6+LAR-8 (57.6/plant). Plant height parameteralso showed significant results as the dual- inoculatedtreatment showed higher plant height than control, LAR-6+LAR-2 showed highest plant height (156.0 cm/plant)followed by LAR-06+LAR-08 (154.7 cm/plant) as compared tocontrol (132 cm/plant).

N-content in seed and straw: Nitrogen content is animportant growth parameter, which has a direct bearing onBNF. Data on N- content of seed in pigeonpea (Table 7),showed that LAR-6 + LAR-2 treatment exhibited maximum N-content (5.64%) compared to control (3.9%), Similar trend wasobserved in straw samples too LAR-6+LAR-2 showed highestN-content (1.94%) as compare to control (1.60) and othertreatments.

Grain yield: Grain yield is the most important economictrait. The data in Fig. 2 reveals that all 5 treatments recordedsignificantly increased grain yield over control. Inoculationwith Rhizobium LAR-6 alone enhanced grain yield over controlby 8.3%. Combined inoculation of LAR-6+LAR-2 furtherenhanced grain yield by 12.1% (1166 kg/ha) over control and3.4% (1127 kg/ha) over Rhizobium LAR-6 alone. The resultsare of agronomical significant and is in confirmation with earlierstudies which report increase recorded in grain yield usingsuitable combination of specific Rhizobium sp. and PGPR forenhancing pigeonpea productivity (Tilak et al. 2006).

The results of this study revealed that biofertilizationof pigeonpea crop with multiple Rhizobium inoculationsignificantly improved plant symbiotic parameters, plantgrowth and yield. Two treatments LAR-6+LAR-2 and LAR-6+LAR-8 showed maximum leghaemoglobin content,chlorophyll content, N-content, symbiotic parameters andyield attributing traits and grain yield as compared to othertreatments. Thus synergistic interaction on dual inoculationof PGPR (rhizobial isolates) and Rhizobium can help toenhance the productivity of pigeonpea and also contribute tosustainability of agricultural system.

[image (a) nodulation in LAR-6+LAR-2 (b) nodulation inLAR-6+LAR-8]

on symbiosis and legume yield.Leghaemoglobin and chlorophyll content: The efficacy

of nitrogen fixation is directly related to leghaemoglobincontent. All the treatments significantly enhancedleghaemoglobin content of nodules over control, maximumbeing recorded with in LAR-6 + LAR-2 Table 4 (4.8 mg/gm),followed by LAR-6+LAR-8 (4.6 mg/gm fresh weight of nodule)as control to control(3.1mg/gm) fresh weight of nodule. Inconfirmation with our study Wani et al. (2007) also reportedthat Rhizobium sp.RP5 increased leghaemoglobin content infield pea. Estimation of chlorophyll content of leaves isimportant because positive and significant correlation existsbetween photosynthesis and N2 fixation. Maximum chlorophyllcontent was observed in LAR-6+LAR-2 (1.36 mg/gm fresh wt.leaves) followed by LAR-6+LAR-8 (1.33 mg/gm). Rhizobiumalone and dually inoculated treatments showed positive effecton chlorophyll content as compared to control (1.03 mg/gmfresh wt. leaves). Zhau et al (2006) reported positive effectson plant photosynthesis and increase in chlorophyll contentafter rhizobia inoculation in soyabean.

Effect on shoot and root dry weight: Positive effect oninoculation was observed on plant biomass. As shown inTable 5, LAR-6+LAR-2 and LAR-6 + LAR-8 (6.5gm and 5.7gm)showed maximum shoot dry weight as compared to control

(a) (b)

Kaur & Khanna : Effect of temperature-tolerant rhizobial isolates as PGPR on nodulation, growth and yield of Pigeonpea 8 3

REFERENCES

Alikhania HA and Yakhchali B. 2009. Potential use of Iranian rhizobialstrains as plant growth promoting rhizobacteria (PGPR) and effectsof selected strains on growth characteristics of wheat, corn andalfalfa DESERT 14: 27-35

Belal Elsayed B, Hassan MM and El-Ramady HR. 2013. Phylogeneticand characterization of salt-tolerant rhizobial strain nodulatingfababean plants African Journal of Biotechnology (27): 4324-37

Deshwal VK, Singh SB, Kumar P and Chubey A. 2013. Rhizobia UniquePlant Growth Promoting Rhizobacteria: A Review InternationalJournal of Life Sciences 2: 74-86 FAOSTAT 2012.

FAOSTAT-Stastical Database 2012Gordon S A and Weber I P. 1951. Colorimetric estimation of indoleacetic

acid. Plant Physiology 25: 192-95.Jackson M L 1973 Phosphorusdetermination for soils In: Soil Chemical Analysis. pp. 134-82.PrenticaHall India Pvt. Ltd, New Delhi

Gray EJ, DL.Smith. 2005. Intracellular and extracellular PGPR:commonalities and distinctions in the plant-bacterium signalingprocesses. Soil Biology and Biochemistry. 37: 395–412

Khanna Veena, Sharma P and Sharma S. 2011. Studies on synergismbetween Rhizobium and plant growth promoting rhizobacteria inlentil (Lens culinaris Medikus). Journal of Food Legumes. 24: 158-59.

Table 1. Biochemical Characterization of Rhizobial IsolatesBiochemical test Rhizobium spp.

Gram reaction - Oxidase + Starch hydrolysis + Citrate utilization + Methy red (MR) - Voges Proskauer (VP) - 3-Ketolactose production - Fast grower 66.7% Slow grower 33.3%

Table 2. Evaluation of PGP traits of temperature tolerantisolatesIAA production (µg/ml) P-solubilization

(mg/100 ml) Rhizobial isolates

At 35°C 40°C 35°C 40°C

Siderophore production (Halo cm)

LAR-2 25.2 31.1 10.0 8.1 1.9 LAR-3 25.0 27 8.7 7.8 1.8 LAR-4 23.4 28.5 8.6 7.9 1.8 LAR-6 28.0 32.3 8.9 8.0 2.2 LAR-8 25.8 30 8.6 7.9 2.0 RXI 23.5 29.0 8.3 7.7 1.8 RX2 23.0 24.2 8.5 7.4 1.5

Table3. Relative growth and functionality potential of

selected isolates at 40°CRhizobial isolate

Growth on YEMA+

BTB

Growth (40°C)

Salinity tolerance

(%)

IAAproduction (µg/ml)

Phosphate solubilization (mg/100 ml)

Siderophore

production (dia. in

cm) LAR-6 Fast 1.30 5 32.3 8.9 2.2 LAR-2 Fast 1.08 5 31.1 9.5 1.9 LAR-3 Fast 0.86 4 27.0 8.7 1.8 LAR-4 Fast 1.00 5 28.5 8.6 1.8 LAR-8 Fast 1.28 5 30.0 8.7 2.0

Table 4. Effect of dual-inoculation on nodulation in pigeonpeaTreatment No.of

nodules /plant

Dry weight of nodules

(mg/plant)

Leghaemoglobin content

(mg/gm fresh wt. of

nodules)

Chlorophyll content

(mg/gm fresh wt. of leaves)

Control 8.0 10.8 3.1 1.03 LAR-6 20.4 31.4 4.2 1.12 LAR-6 + LAR-2 37.4 50.0 4.8 1.36 LAR-6 + LAR-3 21.7 37.4 4.4 1.23 LAR-6 + LAR-4 26.0 24.7 4.2 1.21 LAR-6 + LAR-8 30.0 48.7 4.6 1.33 CD (p=0.05) 2.4 6.0 0.6 . 025

Table 5. Effect of inoculation on dry weight of shoot and root ofpigeonpea

Treatment Shoot dry weight(gm/plant)

Root dry weight (gm/plant)

Control 4.4 0.46 LAR-6 5.6 0.55 LAR-6 + LAR-2 6.5 0.60 LAR-6 + LAR-3 4.7 0.50 LAR-6 + LAR-4 5.1 0.52 LAR-6 + LAR-8 5.7 0.61 CD(p=0.05) 0.63 0.41

Table 6. Effect of dual-inoculation on yield attributing traits

Table 7. Effect of dual inoculation on N-content percentagein pigeonpea

Treatment Primary Branches

/plant

Secondary branches/

plant

No. of pods/plant

Plant height in cm./plant

Control 19.6 28.7 50.3 132.7 LAR-6 20. 0 39.0 53.3 137.0 LAR-6 +LAR-2 25.0 43.7 69.0 156.0 LAR-6 +LAR-3 23.0 39.3 51.4 144.0 LAR -6 +LAR- 23.0 42.0 50.6 146.0 LAR-6+LAR-8 24.0 45.0 57.6 154.7 CD(p=0.05) 4.8 4.4 3.6 7.1

Fig. 2: Effect of inoculation with different strains ofRhizobium on grain yield of pigeonpea

N-content (%) Treatment Seed Straw Control 3.9 1.60 LAR-6 4.3 1.63 LAR-6 + LAR-2 5.6 1.94 LAR-6 + LAR-3 4.6 1.69 LAR-6 + LAR-4 4.4 1.71 LAR-6 + LAR-8 5.0 1.75 CD (p=0.05) 0.39 0.35


Phenotypic characterization of rhizobacteria associated with mungbean rhizosphereNAVPRABHJOT KAUR and POONAM SHARMA1

Department of Microbiology, Punjab Agricultural University-141004, Ludhiana, Punjab, India; 1Department of PlantBreeding and Genetics, Punjab Agricultural University-141004, Ludhiana, Punjab, India;E-mail : [email protected](Received : May 20, 2013 ; Accepted : October 21, 2013)

ABSTRACT

Plant growth promoting rhizobacteria have been identified ininfluencing the growth and yield of many plants by direct orindirect mechanisms. In search of efficient PGPR strains withmultiple plant growth promoting (PGP) activities, a total of 48isolates of rhizobacteria were isolated from 35 different samplesof mungbean rhizosphere. Out of 48, 34 isolates werecharacterized and tentatively identified as Bacillus spp. (14),Pseudomonas spp. (11) and Azotobacter spp. (9) on the basis oftheir morphological and biochemical activities. Thirty fivepercent of these rhizobacterial isolates were able to solubilizephosphate (P) and showed solubilisation index (SI) from 1.00to 3.83 being highest with rhizobacterial isolate B2 (3.83). Theserhizobacterial isolates were selected and screened in vitro fortheir PGP traits (Indole acetic acid (IAA) production), biocontrol(NH3 , HCN, chitinase and protease production) and stresstolerant activity (1-amino cyclopropane-1-carboxylic acid (ACC)deaminase). Rhizobacterial isolates (B2, P10 and A3) showedmaximum IAA production. Ammonia production was detectedin two isolates (B2 and A3) and 5 isolates (B2, B6, P4, P10 andA3) found positive for HCN production. None of the isolateswas positive for chitinase production whereas 52.9% of selectedisolates were able to produce protease on skimmed milk agar.Seventy percent of the isolates indicated the growth on platescontaining Dworkin and Foster (DF) minimal medium withACC as a sole nitrogen source indicated the presence of ACCdeaminase activity. Three rhizobacterial isolates (B2, P10 andA3) were found most promising for multiple activities (PGPtraits, biocontrol and stress tolerant activities) and havepotential to be used in future as PGP inoculants to improvemungbean crop.

Keywords: Azotobacter, ACC deaminase, Bacillus, Mungbean,Pseudomonas, Rhizobacteria,

Mungbean [Vigna radiata (L.) Wilczek], also known asgreen gram, has gained key importance in intensive cropproduction systems in India because of its short growingperiod and better storage ability. Mungbean not only hasgreat dietary value due to its high protein content but alsoimproves soil fertility by fixing atmospheric nitrogen Soilbacteria generally associated with legumes including free livingas well as associative and symbiotic rhizobacteria belongingto genera Acetobacter, Arthrobacter, Azorhizobium,Azospirillum, Azotobacter, Bacillus, Burkholderia,Enterobacter, Erwinia, Flavobacterium, Klebsiella,Pseudomonas, Proteus, Serratia, Rhizobium,Bradyrhizobium, Ensifer, Mesorhizobium and Xanthomons,

have reported to enhance plant growth (Bashan and de-Bashan2010). The application of PGPR in crop production is steadilyincreasing as it offers an attractive way to replace the use ofchemical fertilizers, pesticides and other inputs.

The exact mechanisms by which PGPR promote plantgrowth are not fully understood, but are thought to include :ability to produce or change the concentration of plant growthregulators like indole acetic acid (IAA) gibberellic acidcytokinins and ethylene ( ;asymbiotic nitrogen fixation; ( 3)exhibition of antagonistic activity against phytopathogenicmicroorganisms by producing siderophores, ß-1,3-glucanase,chitinases, antibiotics, fluorescent pigment and cyanide and(4) solubilization of mineral phosphates and other nutrients(Kumar et al. 2012, Sahai and Chandra 2010,Mehnaz et al.2010, Mishra et al. 2010, Bansal 2009, Joseph et al. 2007) Inaddition to these traits, plant growth promoting bacterialstrains must be rhizospheric competent, able to survive andcolonize in the rhizospheric soil The good response obtainedin vitro cannot always be dependably reproduced under fieldconditions (Zhender et al. 1999). The variability in theperformance of PGPR may be due to various environmentalfactors that may affect their growth and exert their effect onthe plant. The environmental factors include climate, weatherconditions, soil characteristics or the composition or activityof the indigenous microbial flora of the soil. To achieve themaximum growth promoting interaction between PGPR andseedlings it is important to discover how the rhizobacteriaexerting their effects on plant and whether the effects arealtered by various environmental factors, including thepresence of other micro-organisms (Bent et al. 2001).

Therefore, it is necessary to develop efficient strainsfor field conditions. One possible approach is to explore soilmicrobial diversity for PGPR having combination of PGPactivities and well adapted to particular soil environment. Sokeeping in view the above constrains, the present study wasdesigned to screen rhizospheric bacterial isolates for theirmultiple plant growth promoting activities from rhizosphereof mungbean crop.

Isolation and characterization of rhizobacteria

Rhizospheric soil samples (1 kg) were collected fromdifferent locations of mungbean growing area of Punjab. Soilsamples were stored in refrigerator till further use.

Ten gm of soil samples from mungbean rhizosphere wereshaken in 90 ml sterilized distilled water for 10 min (Saxena and

Kaur & Sharma : Phenotypic characterization of rhizobacteria associated with mungbean rhizosphere 8 5

Matta 2005). The bacterial strains were isolated by a serialdilution plate technique using Crystal Violet (CV) and MethylRed (MR) agar for the isolation of Gram negative and Grampositive bacteria, respectively. Plates were incubated at 28±2°C.The colonies were then further transferred on Nutrient Agar(NA) plates. Bacterial colonies were carefully isolated andstreaked over the surface their specific media viz. NA forBacillus species, King’s B (King et al. 1954) for Pseudomonasspecies and Jensen’s (Jensen 1942) for Azotobacter species.The bacterial isolates were maintained on Trypticase soybeanagar (TSA) slants (Narula et al. 2006) at 4°C temperature.

The thick bacterial smear of all the isolates was gramstained and morphological characterized on the basis of colonymorphology including shape, elevation, texture, margin, color,odour, size and pigmentation. Biochemical characterization ofPGPR was done on the basis of oxidase , catalase, citrateutilization, Methyl red (MR), Voges-Proskauer(VP), nitratereduction and indole production test as per standardprocedure (Cappuccino and Sherman 1992).

Plant Growth Promoting (PGP) activities

Assay for P solubilisation

P solubilization ability of plant associated bacteria wasdetermined qualitatively by streaking strains on NBRIP(National Botanical Research Institute’s Phosphate growthmedium). The presence of yellow clear zone around bacterialgrowth after one week incubation period at 28oC was used asindicator for positive P solubilisation (Nautiyal 1999).Solubilization index (SI) was calculated by using followingformula:

SI Index= A/BA= total diameter (colony + halo zone), B= diameter of

colony.Promising P solubilizers were further tested for growth

promotional, biocontrol and stress tolerant activities.Qualitative Analysis of Indole Acetic Acid (IAA)Selected bacterial isolates were cultured on Nutrient

Agar (NA) medium amended with L-tryptophan (Trp) andoverlaid with cellulose membrane (Whatman filter paper) andincubated for 48h at 28ºC (Shobha and Kumudini 2012).Salkowski’s reagent was added on the cellulose membraneafter 48h of incubation. Pink colouration indicated productionof IAA. The results were also analyzed visually on a threepoint scale (+ - low; ++ - medium and +++ - high).

Biocontrol activities

NH3 production

Selected rhizobacterial isolates were tested for theproduction of ammonia in peptone water. Freshly growncultures were inoculated into 10 ml peptone water in each

tube and incubated for 48 h at 28ºC. Nessler’s reagent (0.5 ml)was added to each tube. Development of brown to yellowcolour was a positive test for ammonia production (Cappuccinoand Sherman 1992).HCN production

Exponentially grown different selected rhizobacterialisolates were separately streaked on NA medium supplementedwith 4.4 g of glycine per litre with simultaneoussupplementation of a filter paper soaked in 0.5% picric acid in5% Na2CO3 in the upper lid of Petri dish. The plates wereincubated at 28±1ºC for 2to 3 days. Change in colour fromyellow to light brown for moderate (brown) or strong (reddish-brown) indicated HCN production (Bakker and Schippers1987).Chitinase and Protease production

Chitinase and protease activity (casein degradation)was determined from clear zone on chitin and skimmed milkagar respectively. The agar plates were prepared and spotinoculated with test organism and incubated at 30ºC for 5 days.Development of halo zone around the colony was consideredas positive for chitinase and protease production (Chaiharnet al. 2008).

Stress tolerant activity

ACC Deaminase activity

The qualitative estimation was done by the methodprescribed by Govindasamy et al. (2008). Rhizobacterialisolates were streaked on plates containing Dworkin Foster(DF) (Dworkin and Foster 1958) minimal medium with ACC asa sole nitrogen source. The plates were incubated for 3-4 daysat 28±1°C and observed for growth.

Morphological characterization of rhizobacteria

A total of 48 isolates of rhizobacteria from 18 soil samplescollected from different rhizospheric locations of Punjab wereisolated on crystal violet (CV) (28 isolates) and methyl red(MR) (20 isolates) agar media and further streaked on NA.Eleven isolates obtained at CV agar plates produced roundshaped and raised colonies having smooth, shiny surfacewith smooth margin and light yellow to off white in color, butall were odourless while these isolates produced a fluorescentgreen pigment on King’s B medium. These were tentativelyassigned to genera Pseudomonas on the basis of cultural andmorphological appearance Nine isolates from CV agarproduced transparent, glistening and shiny colonies whenstreaked on nitrogen-free Jensen’s medium and were assignedas Azotobacter species On MR agar, 14 out of 20 isolatesproduced large spreading, irregular shaped, off-white andrough colonies and were tentatively assigned to generaBacillus Microscopic examination also revealed somecharacteristics of rhizobacterial isolates on the basis of their


shape, gram’s reaction and motility (Table 1). Pseudomonasand Azotobacter species were rod shaped, motile and gramnegative in reaction whereas Bacillus species were also rodshaped and motile but gram positive in reaction.

Out of 48 isolates, 29.2% were Bacillus sp.( B1, B2, B3, B4,B5, B6, B7, B8, B9, B10, B11, B12, B13 and B14.), 22.9% werePseudomonas sp. (P1, P2, P3, P4, P5, P6, P7, P8, P9, P10 andP11) and 18.7% were Azotobacter sp. (A1, A2, A3, A4, A5, A6,A7, A8 and A9).

In our study, three different genera were identified viz.Bacillus, Pseudomonas and Azotobacter. Bacillus (17.9%)was dominant group followed by Pseudomonas andAzotobacter in mungbean rhizosphere. Earlier studies haveshown that Bacillus and Pseudomonas as dominant generain the rhizosphere probably due to their ability to efficientlyuse nutrients in the root exduates. (Joseph et al. 2007, Joshiand Bhatt 2011). Ahmad et al. (2008) reported Azotobacter(65.2%) as a predominant group in the rhizospheric soil ofdifferent crops (mustard, barseem, wheat, sugarcane, brinjal,onion, cauliflower, cabbage and chickpea) as compared toPseudomonas (12.5%) and Bacillus (13.8%). Similarly, Cattlenet al. (1998) reported Pseudomonas, Burkholderia, Bacillusand Alcaligens as predominant genera in rhizosphere ofsoybean. Dominance of these genera in rhizosphere ofdifferent crops is useful because of their significant ecologicalroles in soil and nutrient cycling (Gray and Smith 2005).

Plant Growth Promoting (PGP) activities

Phosphate solubilisation activity

Out of 34 rhizobacterial isolates, 57% of Bacillus, 45%of Pseudomonas and 44% of Azotobacter species showed P-solubilization and resulted into formation of sharp yellowphosphate solubilization zone on NBRIP mediumSolubilization Index (SI) revealed variation from 1.0-3.0.Bacterial isolates B6, B10 and P5 showed SI index as 1.0 withsolubilization zone as wide as the colony diameter (Fig. 1).Five isolates viz. B1 (2.19), B3 (2.33), B8 (2.34), P4 (2.28) andA1 (2.09) showed SI greater than 2.00. Three isolates i.e B2(3.83), P10 (3.62) and A3 (3.13) with SI greater than 3.00 showedhighest phosphate solubilization. This investigation has beenfound coherent with the result of Calvo et al. (2010) who

Table 1. Morphological cultural, and biochemicalcharacteristics of rhizobacteria

Isolates Bacillus Pseudomonas Azotobacter Cell shape Rod Rod Rod Elevation Umbonate Raised Raised Texture Mucoid Mucoid Mucoid Margin Irregular Smooth Entire Color Cream light yellow Tranparent

opaque Odour Odourless Odourless Odourless Size Medium Medium Medium

Pigmentation None Fluorescent green None Motility Motile Motile Motile

Gram reaction Gram positive Gram negative Gram negative Oxidase + + (with in 10 sec) + Catalase + + +

Citrate utilization + + + Methy red (MR) - - + Voges Proskauer

(VP) + - _

Nitrate reduction (NR)

+ + +

Indole - - +

Bacterial isolates

B2, P10, A3 B6, B11, P4 B3,B7,B8, P2, P8, A1, A7

B1, B10, P5, A9

Intensity +++ ++ + -

Table 2. Qualitative analysis of indole acetic acid (IAA)

(+ : low; ++ : medium and +++ : high, - : absence of IAA production)

Cultures NH3 HCN Chitinase activity

Protease activity

ACC deaminase Activity

B1 - - - + + B2 + + - + + B3 - - - + + B6 - + - - + B7 - - - - - B8 - - - - + B10 - - - - - B11 - - - + + P2 - - - + - P4 - + - - + P5 - - - + - P8 - - - - - P10 - + - + + A1 - - - - + A3 + + - + + A7 - - - - + A9 - - - + +

Table 3. Characterization of rhizobacteria for biocontrol andstress tolerant activities

Fig 1. P Solubilisation Index (SI) for rhizobacterial isolates

Biochemical characteristics of rhizobacteria

On the basis of biochemical characterization, all isolateswere found to be positive for catalase, citrate utilization andnitrate reduction. All rhizobacterial isolates were positive foroxidase test (Table 2). Bacillus and Pseudomonas specieswere positive for VP but negative for MR except Azotobacter.


reported Pseudomonas, Bacillus and Azotobacter as effectivephosphate solubilizing genera. Kumar et al. (2012) alsoreported 12 out of 30 rhizobacteria belonging to generaAcinetobacter Pseudomonas, Bacillus and Enterobacterisolated from french bean rhizosphere and produced clearzones ranging from 4 to 20mm. Similarly, Sitepu et al. (2007)reported phosphate solubilizing bacteria with SI equal to 1having solubilization zone as wide as the colony diameter andgreater than 3.00 for bacteria with efficient phosphatesolubilization on media containing calcium-triphosphate.Indole acetic acid production

After 48h of incubation, the cellulose membrane(Whatman filter paper) was removed and treated withSalkowski’s reagent. Observations showed that the membraneturned pink indicating the production of IAACellulosemembrane placed on cultures of all the isolated bacterial speciesexcept B1, B10, P5 and A9 showed pink coloration but withvarying intensity. Visual observation showed that B2, P10and A3 cultures showed maximum colorations whereas B3,B7, B8, P2, P8, A1 and A7 cultures showed the least (Table 2 -)

Our results are in well agreement with findings of Josephet al. (2007) who has reported the highest IAA production inall isolates of Bacillus, Pseudomonas and Azotobacter (100%)followed by Rhizobium (85.7%) in chickpea rhizosphere.Similarly, production of IAA has been reported in species ofBacillus, Pseudomonas, Azotobacter, Azospirillium,Phosphobacteria, Glucanoacetobacter, Aspergillus andPenicillium in rice (Ashrafuzzaman et al. 2009, Saharan andNehra 2011). B. megaterium from tea rhizosphere alsoproduced IAA and played an important role in plant growthpromotion (Chakraborty et al. 2006). Variation in IAAproduction with different isolates in present study was wellsupported with findings of Ashrafuzzaman et al. (2009) whoalso revealed that IAA production by PGPR can vary amongdifferent species and strains and is also influenced by culturecondition, growth stage and substrate availability. IAAfunctions as an important signal molecule in the regulation ofplant development and indirectly by influencing bacterialamino cyclopropane-1-carboxylate (ACC) deaminase activity(Ryu and Patten 2008, Wahyudi et al. 2011). Role of bacterialIAA in different plant-microbe interactions bacteria use thisphytohormone to interact with plants as part of theircolonization strategy, including phytostimulation andcircumvention of basal plant defense mechanisms (Ahmad etal. 2008, Samuel and Muthukkaruppan 2011). Enzymeindolepyruvic decarboxylase (IPDC) is the principal enzymewhich determines IAA biosynthesis and stimulates thedevelopment of the root system of the host plant (Erturk et al.2010).

Biocontrol activities

NH3 and HCN production

Development of yellow-brown color was observed afteraddition of Nessler’s reagent indicating a positive test forammonia production. Only two isolates B2 and A3 were ableto produce ammonia (Table 3 -) whereas no ammoniaproduction was observed with Pseudomonas isolates.Ammonia production indirectly influenced the plant growthand directly involves in biocontrol activities. Our results arewell corroborated with findings of Mishra et al. (2010) whorevealed B. subtilis strain MA-2 and Pseudomonasfluorescens strain MA-4 was efficient in ammoniaproduction as compared to Azotobacter isolates andsignificantly increased biomass of medicinal and aromaticplant such as Geranium. In present study, ammoniaproduction was recorded with 11.3% of the rhizobacterialisolates in mungbean rhizosphere. On the contrast, Samueland Muthukkaruppan (2011) detected ammonia productionin 95% of the isolates from the rhizosphere of rice, mangroveand effluent contaminated soil influencing plant growthpromotion. Similarly, Joseph et al. (2007) revealed theproduction of ammonia commonly, detected in the isolates ofBacillus (95%) followed by Pseudomonas (94.2%), Rhizobium(74.2%) and Azotobacter (45%).

Five isolates (B2, B6, P4, P10 and A3) among selectedisolates were found positive for HCN production frommungbean rhizosphere (Table 3 ). Similarly, rhizobacteriabelonging to genera Pseudomonas, Bacillus, and Azotobacterfrom rhizosphere of rice, mangrove, chickpea, frenchbean andeffluent contaminated soil showed HCN production (Josephet al. 2007; Samuel and Muthukkaruppan 2011, Kumar et al.2012). HCN production by rhizobacteria has been postulatedto play an important role in the biological control of pathogens(Kumar et al. 2012).Chitinase and Protease production

Production of fungal cell wall degrading enzymes wasanalysed because this is an important mechanism of fungalinhibition. All the selected isolates were negative for chitinaseproduction on chitin agar, whereas 52.9% of selected isolateswere positive for protease production on skimmed milk agar(Table 3). Similarly, Chaiharn et al. (2008) reported 14rhizosphere isolates (6%) positive for cellulase, a fungal cellwall degrading enzyme, detected chitinase activity in fifteenisolates (6%) and found eleven isolates (5%) producing halozones on skim milk agar that showed protease activity. Thescreening of isolates for protease production on skim milkagar plate according to Cattelan et al. (1999) showed thatPseudomonas isolates from soybean rhizosphere werepositive for the proteolytic activities which supported thework done by our study. Ruchi et al. (2012) also reported theproteolytic activity by 26 rhizobacterial isolates from therhizosphere of both apple and pear growing in normal and


replant sites. Evidence for suppression of soil borne plantpathogens by both antibiotic and lytic enzyme producingBacillus strains have recently been described (Kumar et al.2012).

Stress tolerant activity

ACC deaminase activity

Seventy percent of the selected isolates showed thegrowth on plates containing DF minimal medium with ACC asa sole nitrogen source indicating the presence of ACCdeaminase activity (Table 3). Out of 17 selected isolates, 100%of Azotobacter sp. detected ACC deaminase activity followedby 75% of Bacillus sp. and 40 % Pseudomonas sp. Similarly,several bacterial species belong to different genera such asAzospirillum, Agrobacterium, Achromobacter, Burkholderia,Enterobacter, Pseudomonas and Ralstonia have beenreported to possess variable ACC-deaminase activity in maizeand pea rhizosphere (Nadeem et al. 2007; Arshad et al. 2008).It is highly likely that rhizobacteria promoted root growth bylowering ethylene levels in plant and/or in the vicinity of rootsbecause of their ACC-deaminase activity. Many researchershave reported better root growth in plants inoculated withbacteria containing ACC-deaminase (Glick et al. 1995, Mayaket al. 2004, Shaharoona et al. 2006). Rhizobacteria containingACC-deaminase can facilitate plant growth to overcomeharmful effects of ethylene under water stress conditions.Inoculation with rhizobacteria containing ACC-deaminaseincreased the root length of the wheat seedlings ranging from21 to 23% over uninoculated control (Bangash et al. 2013).

This study showed that three rhizobacterial isolates (B2,P10 and A3) were found most promising for multiple activities(PGP traits, biocontrol and stress tolerant activities) and havepotential to be examined for their capability in enhancing plantgrowth. A better understanding on their diversity in therhizosphere along with their colonization ability andmechanism of action should facilitate their application as areliable component in the management of sustainableagricultural system.

REFERENCES

Ahmad F, Ahmad I and Khan MS. 2008. Screening of free-livingrhizospheric bacteria for their multiple growth promoting activities.Microbiological Research 163:173-181.

Arshad M, Shaharoona B and Mahmood T. 2008. Inoculation withPseudomonas spp. containing ACC-deaminase partially eliminatesthe effects of drought stress on growth, yield, and ripening of Pea(Pisum sativum L.). Pedosphere 18: 611-620.

Ashrafuzzaman M, Hossen FA, Ismail MR, Hoque Md. A, Islam MZ,Shahidullah SM and Mcon S. 2009 Efficiency of Plant growthpromoting rhizobacteria (PGPR) for the enhancement of ricegrowth. African Journal of Biotechnology 8:1247-1252.

Bakker AW and Schippers B. 1987. Microbial cyanide production inthe rhizosphere in relation to potato yield reduction and

Pseudomonas spp-mediated plant growth-stimulation. Soil Biologyand Biochemistry 19:415-457.

Bangash N, Khalid A, Mahmood T and Siddique MT. 2013. Screeningrhizobacteria containing ACC-deaminase for growth promotion ofwheat under water stress. Pakistan Journal of Botany 45: 91-96.

Bansal RK 2009. Synergistic effect of Rhizobium, PSB and PGPR onnodulation and grain yield of mungbean. Journal of Food Legumes22:37-39.Bashan Y and de-Bashan LE. 2010. How the plant growth-promoting bacterium Azospirillum promotes plant growth–a criticalassessment. Advances in Agronomy 108:77–136.

Bent E, Tuzun S, Chanway CP and Enebak S. 2001. Alterations in plantgrowth and in root hormone levels of lodgepole pines inoculatedwith rhizobacteria. Canadian Journal of Microbiology 47:793–800.

Calvo P, Orrillo EO, Martínez-Romero E and Zúñiga O. 2010.Characterization of Bacillus isolates of potato rhizosphere fromandean soils of Peru and their potential PGPR characteristics.Brazilian Journal of Microbiology 41: 899-906.

Cappuccino JC and Sherman N. 1992. In: Microbiology: A LaboratoryManual,. New York, Pp 125-179.

Cattelan AJ, Hartel PG and Fuhrmann JJ. 1999. Screening for plantgrowth-promoting rhizobacteria to promote early soybean growth.Soil Science Society of American Journal 63:1670–1680.

Cattlen AJ, Hartel P G and Fuhrmann J J. 1998. Bacterial compositionin the rhizosphere of nodulating and non-nodulating soybean. SoilScience Society of American Journal 62:1549-1555.

Chaiharn M, Chunhaleuchanon S, Kozo A and Lumyong S. 2008.Screening of rhizobacteria for their plant growth promotingactivities. Science and Technology Journal 8:18-23.

Chakraborty U, Chakraborty B and Basnet M. 2006. Plant growthpromotion and induction of resistance in Camellia sinensis byBacillus megaterium. Journal of Basic Microbiology 46: 186-195.

Dworkin M and Foster J. 1958. Experiments with some microorganismswhich utilize ethane and hydrogen. Journal of Bacteriology75: 592-601.

Erturk Y, Ercisli S, Haznedar A and Cakmakci R. 2010. Effects of plantgrowth promoting rhizobacteria (PGPR) on rooting and root growthof kiwifruit (Actinidia deliciosa) stem cuttings. Biological Research43:91–98.

Glick B. 1995. The enhancement of plant growth by free living bacteria.Microbiology 41:109-117.

Govindasamy V, Senthilkumar M, Gaikwad K and Annapurna K. 2008.Isolation and characterization of ACC deaminase gene from twoplant growth-promoting rhizobacteria. Current Microbiology 57:312–317.

Gray EJ and Smith DL. 2005. Intracellular and extracellular PGPR:commonalities and distinctions in the plant-bacterium signallingprocesses. Soil Biology and Biochemistry 37:395–412.

Jensen HL. 1942. Nitrogen fixation in leguminous plants. I. Generalcharacters of root nodule bacteria isolated from species of Medicagoand Trifolium. Proceedings of the Linnean Society of New SouthWales 66:98-108.

Joseph B, Patra RR and Lawrence R. 2007. Characterization of plantgrowth promoting rhizobacteria associated with chickpea (Cicerarientinum L.). International Journal of Plant Production 1:141-151.

Joshi P and Bhatt AB. 2011. Diversity and function of plant growthpromoting rhizobacteria associated with wheat rhizosphere in northHimalayan region. International Journal of Environmental Sciences1:1135-1143.


King EO, Ward MK and Raney DE. 1954. Two simple media for thedemonstration of pyocyanin and fluorecein. Journal of Laboratoryand Clinical Medicine 44: 301-07.

Kumar A, Kumar A, Devi S, Patil S, Payal C and Negi S. 2012. Isolation,screening and characterization of bacteria from rhizospheric soilsfor different plant growth promotion (PGP) activities: an in vitrostudy. Recent Research in Science and Technology 4: 1-5.

Martinez-Viveros O, Jorquera MA, Crowley DE, Gajardo G and MoraML. 2010. Mechanisms and practical considerations involved inplant growth promotion by rhizobacteria. Journal of Soil Scienceand Plant Nutrition 10: 293–319.

Mayak S, Tirosh T and Glick BR. 2004. Plant growth-promoting bacteriaconfer resistance in tomato plants to salt stress. Plant Physiologyand Biochemistry 42: 565–572.

Mehnaz, Samina, Baig DN and George L. 2010. Genetic and phenotypicdiversity of plant growth promoting rhizobacteria isolated fromsugarcane plants growing in Pakistan. Journal of Microbiology andBiotechnology 20: 1614–1623.

Mishra M, Kumar U, Mishra PK and Prakash V. 2010. Efficiency ofplant growth promoting rhizobacteria for the enhancement of Cicerarietinum L. growth and germination under salinity. Advances inBiological Research 4: 92–96.

Nadeem SM, Zahir ZA, Naveed M and Arshad M. 2007. Preliminaryinvestigations on inducing salt tolerance in maize through inoculationwith rhizobacteria containing ACC deaminase activity. CanadianJournal of Microbiology 53: 1141-1149.

Narula N, Deubel A, Gans W, Behl RK and Merbach W. 2006. Paranodulesand colonization of wheat roots by phytohormone producingbacteria in soil. Plant soil and Environment 52: 119–129.

Nautiyal CS. 1999. An efficient microbiological growth medium forscreening phosphate solubilizing microorganisms. FEMSMicrobiology Letters 170: 265-270.

Ruchi, Kapoor R, Kumar A, Kumar A, Patil S, Thapa S and Kaur M.2012. Evaluation of plant growth promoting attributes and lyticenzyme production by fluorescent Pseudomonas diversityassociated with apple and pear. International Journal of Scientificand Research Publications 2: 1-8

Ryu R and Patten CL. 2008. Aromatic amino acid-dependent expressionof indole-3-pyruvate decarboxylase is regulated by 4 TyrR in

Enterobacter cloacae UW5. American Society for Microbiology190: 1-35.

Sahai P and Chandra R 2010. Co-inoculation effect of liquid and carrierinoculants of Mesorhizobium ciceri and PGPR on nodulation,nutrient uptake and yields of chickpea. Journal of Food Legumes23:159-161Saharan BS and Nehra V. 2011. Plant growth promotingrhizobacteria: A Critical Review. Life Sciences and Medical Research21: 1-30.

Samuel S and Muthukkaruppan SM. 2011. Characterization of plantgrowth promoting rhizobacteria and fungi associated with rice,mangrove and effluent contaminated soil. Current Botany 2: 22-25.

Saxena MAK and Matta NK. 2005. Selection and cultivable PGPRfrom diverse pool of bacteria inhabiting pigeonpea rhizossphere.Indian Journal of Microbiology 45: 21-26.

Shaharoona B, Arshad M, Zahir ZA and Khalid A. 2006. Performanceof Pseudomonas spp. containing ACC-deaminase for improvinggrowth and yield of maize (Zea mays L.) in the presence ofnitrogenous fertilizer. Soil Biology and Biochemistry 38: 2971–2975.

Shobha G and Kumudini BS. 2012. Antagonistic effect of the newlyisolated PGPR Bacillus spp. on Fusarium oxysporum. InternationalJournal of Applied Science and Engineering Research 1: 463-474.

Sitepu IR, Hashidoko Y, Erdy SS and Satoshi T. 2007. Potent phosphate-solubilizing bacteria isolated from dipterocarps grown in peat swampforest in central Kalimantan and their possible utilization forbiorehabilitation of degraded peatland. Proceedings of theInternational Symposium and Workshop on Tropical PeatlandYogyakarta, Gadjah Mada University, Indonesia. Pp. 133-138.

Wahyudi AT, Astuti RP, Widyawati A, Meryandini A and NawangsihAA. 2011. Characterization of Bacillus sp. strains isolated fromrhizosphere of soybean plants for their use as potential plant growthfor promoting rhizobacteria. Journal of Microbiology andAntimicrobiol 3: 34-40.

Zhender GW, Yao C, Murphy JF, Sikora ER, Kloepper JW, Schuster DJand Polston JE. 1999. Microbe-induced resistance against pathogensand herbivores: evidence of effectiveness in agriculture. In: Agarwal,A.A., Tuzun, S., Bent., E. (Eds.), Induced Plant Defenses AgainstPathogens and Herbivores: Biochemistry, Ecology and Agriculture.APS Press, St Paul, MN, Pp 33.


Root morphology and architecture (CRIDA indigenous root chamber-pin boardmethod) of two morphologically contrasting genotypes of mungbean under variedwater conditionsV. MARUTHI, K. SRINIVAS, K.S. REDDY, B.M.K. REDDY, B.M.K. RAJU, M. PURUSHOTHAM REDDY,D.G.M. SAROJA and K. SURENDER RAO

Central Research Institute for Dryland Agriculture (CRIDA), Saidabad post, Hyderabad, Andhra Pradesh, India;E-mail : [email protected](Received : June 29, 2013; Accepted : November 18, 2013)

ABSTRACT

An experiment was conducted in the root chambers during2010-11 under the net-house conditions at Central ResearchInstitute for Dryland Agriculture (CRIDA) Hyderabad, India tostudy the effect of soil moisture deficit on root morphology androot architecture of two morphologically contrasting cultivarsof mungbean in comparison with the irrigated treatment. ML267(short stature) and WGG37 (tall stature) were studied with twowatering treatments viz., soil moisture up to FC (irrigated)and another up to 33.3% Available Water Content (deficitwatered). Soil moisture stress affected total root length atflowering stage (42DAS) of mungbean by 30% irrespective ofcultivar and also expressed drought resistance of ML267 atvegetative stage (22DAS) and at pod filling stage (69DAS) ofWGG37. Deficit soil moisture conditions affected WGG37 morethan ML267. It is concluded that soil moisture deficit conditions(33.3%AWC) though reduced the root dry weight at the top soildepth, increased Total Root Length (TRL), Root Length Density(RLD), Root Surface Area (RSA) at deeper soil depths especiallyat 42DAS resulting in high root shoot ratio and fine root lengthof ML267. 2D Root architecture image of a single plant androot measurement at different soil profile depths could bepossible in Root chamber-Pin board methodology. Therefore,this indigenized Root chamber- Pin board method was adoptedand is recommended for study of root architecture undercontrolled conditions.

Key Words: Mungbean , Root architecture, Root chamber-Pin boardmethodology, root length density, root morphology, soil moisturestress, total root length.

Plants vary in their abilities to survive under extremeenvironmental conditions. Though visible above groundbiomass is the manifestation of the extreme situation beingfaced, below ground biomass stabilizes the system by playinga crucial role for resilience. Plants capability to proliferate rootsand responses to heterogeneous environments andspecifically of species and varieties (Campbell et al. 1991,Bauerle et al. 2008) differ. With the dynamic nature of soil,changes in root distribution may be observed both horizontallyand vertically. Further this is aggravated by the problems oflate onset of monsoon, intermittent dryspells/ droughts duringthe crop growth period etc.

Mungbean "Vigna radiate (L.) R. Wilczek" also called‘Greengram’ is gaining importance due to its contribution tothe health of both rich and poor worldwide. Mungbean is ashort duration legume of 65-75 days yielding protein rich seedsfor human beings, husk and haulms for fodder concurrentlyimproving the soil health through nitrogen fixation. It isgenerally grown in the rainfed lands of South India, parts ofU.P., Madhya Pradesh, Maharashtra and parts of Eastern India.Due to its growing under marginal rainfed situations,production and productivity improvement is not considerable.Therefore efforts are on to break the plateau in the productionof these legumes. Generally the first casualty under droughtsituation is the root system which is an interface between theplant and the soil. Consequently the water saving mechanismsof the plant would come into the scene along with the watercapturing abilities of the root system. However, till now thedrought management measures were formulated and validatedbased on the study of only above ground biomass. But thestudy of below ground biomass and its relation with the yieldmay help us in finding not only the moisture sensitive stagesof the crops accurately and to manage it effectively but alsowill generate information on critical root traits for extremesituation for plant breeders.

Understanding the root distribution soil profile wise inorder to estimate the capabilities of the plant to extract soilmoisture and nutrients for its sustenance is incomplete withoutthe standard methodologies for root architectural study. Tillnow the plant root studies mostly were in the form ofexcavating the total root biomass and estimating the rootparameters of the total root system. However, the data did notgive much clue about the distribution of roots at different soildepths in the soil profile which primarily affect the acquisitionof soil moisture and nutrients. But after long periods of rootresearch, methods like root chamber-pinboard were in voguesince 60s. However, the improvements in this method tookplace in terms of materials used to fabricate root boxes,methodology to sample etc. Therefore, an attempt was madeto indigenize the above mentioned pin board methodology tosuit the mungbean root architecture sampling requirements.Mostly these methodologies work with the narrow or thinroot boxes which were helpful to get 2D root architecture but

Maruthi et. al., : Root morphology and architecture (CRIDA indigenous root chamber-pin board method) 9 1

to thwart criticism on restricted space for the plant, in Indiawe worked with the objective of single plant field spacing(SPFS), by providing boxes of size equivalent to field spacingof a single plant while methodology of extracting rootarchitecture was one another objective being addressed.

Moisture within the soil profile is heterogeneous andvaries within soil but the root systems must forage for thislimited resource. Root system in some cultivars grows verticallywith more root angle to the soil surface might have the geneticcomponent (Vegapareddy et al. 2010) to exploit more moisturefrom deeper layers of the soil with the top soil layers dried out(Doussan et al. 2003). For the transient soil moistureavailabilities and deficits, root system of the plant should begeared up to seek soil moisture for either maintenance of theroot under dry soil conditions or for sustaining the roots(Eissenstat and Caldwell 1988, Hodge 2004, Kosola andEissenstat 1994, Eissenstat et al.1999). Therefore an experimentwas conducted to assess the effect of soil moisture deficitson rooting variability of two morphologically contrastingmungbean cultivars for their suitability to various fieldtransient soil moisture dynamics.


The experiment included two mungbean cultivars grownunder limited soil moisture (irrigated at 33.3% available watercontent or 66.7% depletion of AWC) and at unlimited waterconditions (Field Capacity). Of these two mungbean cultivars,ML267 a more popular and short statured while WGG37 fromWarangal Research Station of ANGRAU of Andhra Pradeshin India is a tall growing variety. This experiment wasconducted under the net-house conditions at CentralResearch Institute for Dryland Agriculture (CRIDA)Hyderabad, India during 2010.

Experimental details

The crop was grown in Red Sandy Loam soil profilefilled root chambers of 30x15x45cm dimension. Two seeds weresown in each chamber and thinned to one plant aftergermination. As per the recommendation, fertilizer wassupplied to each chamber. For one set of chambers, irrigationwas carried out whenever the soil moisture fell below FC andfor another set of chambers, whenever the soil moisturerecorded 33.3%AWC using surface moisture probe upto 20cm depth. Each chamber uniformly received fertilizer and watercontent as per the treatment. The soil with 75% sand, 3% siltand 22% clay has neutral PH (7.2), normal EC (0.16ds/s-1), lownitrogen content (171kg ha-1), medium available phosphorus(17.7 kg ha-1) and high potassium (307 kg ha-1) as the soil wasfrom the long term fallow land . Plants were sampled at 22, 42and 69 days after sowing (DAS). Shoot parameters wererecorded as above ground biomass. Spatial configuration ofplant roots in soil (Root architecture) was studied byunderstanding the distribution of Total Root Length (TRL)

and Root Length Density (RLD) in the soil profile.Methodology of sampling (Illustration) for RootArchitecture (Indigenized Root chamber-Pin boardmethodology)

The methodology explained by Price et al. (2002) wasIndigenised to suit the size of the root chamber in which theplants were grown.

Construction of Root chambers: As our test crop ismungbean, the field spacing of 30 x15cm was taken intoaccount and acrylic chambers of 30cm X 15cm x 15cm rectangleboxes were constructed and three boxes were arranged oneabove the other so as to have the total depth of 45cm. Theboxes were glued with a tape to avoid leakage of water from it.A drainage hole was made to the bottom most boxes. On oneside (length side) of the box, acrylic sheet opens like a doorwhich is fitted with the hasps and hinges.

Pin Board: A PVC board with spokes (motor bike spokesof 16.5cm length, 3.5mm diameter with a screw at the bottompart) fixed at grid lines distance of 2.5 cm in alternate rows andpainted black.

Sampling Protocol: For sampling, the door of eachchamber was opened, fitted with the black pin board bypushing the spokes into the soil until it touches the box andturned it around lifting up the chamber leaving whole soilmass with root system on the pin board.

Root washing: Roots were washed by keeping the pinboard in the wheel barrow. After washing, the mounted rootsystem on the pin board was placed in the water tray, wasphotographed after it was allowed to gently align on its own.

Photography: By placing the black pin board with rootsystem in the water tray, digital images were generated usinghigh end digital camera at a perpendicularly fixed objectdistance using boom stand.

Root Scanning and image analysis: After sampling andphotography, the roots were cut for sub sampling, stored inwater of glass bottles in a refrigerator at 4ºC until they werescanned using flat bed scanner of STD 4800 and analyzedTRL (cm) using “WinRHIZO” (Regular 2009c Version). Rootscans were stored in tiff format and data were generated intext file, later converted into Excel files for further analysis.After scanning, the roots were dried at 40°C for four days forroot dry weights.

According to Price et al. (2002) the root boxes made ofglass and of 1.5 cm in width and 70cm and 50cm in length anddepth respectively, while in our case it is an acrylic box of30x15x45cm dimension which led to changed pinboard sizeand the pins. In our experiment, we used the bike spokes of16.5cm length in place of nails but could not paint them toblack. These spokes have got bolts to fix and remove at thebottom. On contrary to the nails, the spokes were of 3.5cm indiameter. Further to take the photographs without spokes


obstructing the vision, earbuds painted black were fixed inplace of spokes.Statistical Design

Complete randomized Block design with one wayanalysis of ANOVA was employed with four replications(Gomez and Gomez 1984) to estimate the treatmentaldifferences.

moisture deficit conditions which was 0.184 in ML267 while0.123 was recorded at field capacity indicating the increasedroot weights with soil moisture deficits which might havehappened either due to suberization of big roots and stimulatedproliferation of roots during moderate to severe moisture stressor due to reduced shoot weight.

Big roots (maximum mean root diameter) of 0.10-0.25mmwere recorded in ML267 at FC over moisture stressed.Generally wider roots are prominent at reduced soil moisturelevels which did not happen in case of ML267. In this context,smaller root diameter in dry soil can be due to greater resistanceto penetration which happened in case of ML267 at moisturestressed condition. Therefore, presence of fine roots (smallroot diameter) under moisture stress may be one of the droughttolerant traits of this cultivar.

Illustration on Methodology of Mungbean RootArchitectural Sampling


Variability in root morphology of cultivar ML267

At field capacity, there was a gradual increase in totalroot length (TRL) and root length density (RLD) of ML267cultivar up to 42 DAS which was declined later at 69DAS.However, moisture deficits (33.3%AWC) reduced TRL at allthe three stages (22, 42 and 69DAS) to an extent of 4, 25 and42% respectively indicating more root length reduction andsensitivity of the stages for moisture deficits especially at 42and 69DAS (Fig 2.). This indicates the maximum negativeeffect of moisture stress on this variety at both flowering andpod filling stages compared to the vegetative stage.

Maximum root dry weight was observed under wellwatered conditions while under moisture deficit conditionsshoot dry weight was more affected (Table 1). Among all thestages, root shoot ratios at 69DAS observed to be more under

Maximum RSA (1571 cm2) was recorded at 42DAS underwell watered conditions and lowest was recorded at soilmoisture deficit conditions. Soil moisture deficit conditionsreduced RSA on an average to an extent of 25% and thisreduction was more at 69DAS (45%).Variability in root morphology of cultivar WGG37

Unlike ML267, WGG37 recorded maximum TRL and RLDat 69DAS under both water sufficient and deficit conditions.However, the moisture deficits reduced TRL and RLD to agreat extent at 22DAS followed by 42 and 69DAS (44, 35 and19% respectively) as the crop duration was progressingemphasizing the moisture susceptibility of this cultivar startingfrom vegetative stage.

Root shoot ratio was more with WGG37 under moisturedeficit conditions especially at 22 (0.222) and 69DAS (0.254).This might not be only due to greater root weight of the plantbut also because of reduced shoot biomass at respective

Fig. 1: Effect of water treatments on TRL (cm) ofmungbean cultivars during the crop growth period


stages further emphasizing the moisture sensitivity of thiscultivar (Zhang et al. 2009).

Both well watered and moisture stressed WGG37registered greater mean root diameter both at initial stages(22DAS) as well as at later stages (69DAS) signifying thepresence of bigger roots from the initial stages itself whichaccount for increased root dry weights (Eissenstat and Yanai2002, Waisel and Eshal 2002). As the crop progressed, therewas increase in root dry weights both under sufficient anddeficit water conditions (Table 1). High TRL at 69DAS underboth well watered and moisture stressed conditions was thegenetic trait of the cultivar.This was the genetic trait of thecultivar as TRL peaked at 69 DAS.

As regards RSA at moisture sufficient conditions,maximum was achieved by WGG37 at all the stages while underdeficit conditions, it increased with moisture stress at laterstages (69DAS) which may not be helpful for the crop toachieve better yields as argued by Gooding et al 2005 andAndersson et al. (2005) that growing roots compete with grainsfor all the resources. However, more RSA at 69DAS (1082cm2)may be an indication of greater resistance to penetration byroot as claimed by Munoz-Romero et al. (2010).Root morphology of ML267 Vs WGG37

Under irrigated conditions, WGG37 recorded maximumtotal root length (16145cm) which was 27.5% more than thetotal root length registered by ML267 while moisture deficitsreduced TRL of WGG37 by 27% which is 3% more than theTRL reduction in ML267. However, Vice Versa was observedwith Root Surface Area (RSA) as more RSA (1571cm2)registered by ML267 compared to WGG37 (1477cm2

respectively). Mungbean crop in general registered reducedroot parameters due to moisture deficits however; thisreduction was more in WGG37. Cultivars vary in their abilityto counteract drought through root component as the cropgrowth progresses which may be considered for differentstages. Stage-wise discussion was carried out in the nextparagraph. ML267 recognized for drought resistance,registered increased trend in almost all the parametersincluding root dry weights with limited moisture over moisturestressed WGG37 (Table 1). However, WGG37 showed

increasing trend in root dry weights and RSA with increasedage, apart from TRL which may imply more partitioning towardsroot component at later stages may not be of much help inrealizing higher yields as optimal partitioning of drymatterbetween root and shoot is crucial under conditions of moisturestress (Kage et al. 2004) and also the stage at which it happens.ML267 expressed sensitivity to soil moisture deficits afterflowering stage onwards through reduced TRL, RLD and RSA.However, WGG37 showed increasing trend in the abovementioned root parameters throughout the crop growthperiod.Different stages of the crop (ML267 Vs WGG3)

Irrespective of the cultivar and water treatment, maximumroot surface area was recorded at 42DAS (flowering stage).Of all the stages and cultivars, crop at 42DAS showed moreroot surface area and small root diameter compared to all otherstages signifying the presence of more fine roots at this stage(Table 1). However, regarding TRL, WGG37 registered 18 and22% more TRL than ML267 at vegetative (22DAS with 1252cm) and at pod filling stages (69DAS with 13146 cm)respectively while at flowering stage (42DAS) it was 22% lessthan ML267 (16754 cm) (Fig 2 & 3). This varied TRL of both

Root dry weight (g/plant)

DAS

Shoot dry weight (g/plant)

DAS

Root Shoot Ratio (weight)

DAS

Mean Root Diameter (mm) DAS

Mean Root Surface Area (cm2)

DAS

Treatments Yield (kg ha-1)

22 42 69 22 42 69 22 42 69 22 42 69 22 42 69 ML267 FC 678 0.07 0.49 0.47 0.20 3.45 3.89 0.237 0.163 0.123 0.30 0.29 1.10 118 1571 1132 ML267 at 33.3%AWC 462 0.05 0.47 0.31 0.22 2.68 1.73 0.240 0.161 0.184 0.28 0.35 1.02 103 1286 617

WGG37FC 729 0.09 0.45 0.73 0.42 2.94 3.82 0.216 0.153 0.185 0.35 0.33 0.88 201 1477 971 WGG37 at 33.3%AWC 338 0.04 0.42 0.66 0.18 2.74 2.60 0.246 0.152 0.232 0.33 0.34 1.01 90 997 1082

SEd ± 18.6 0.013 0.098 0.101 0.012 0.375 0.319 0.030 0.016 0.017 0.003 0.032 0.020 3.14 124 39.5 CD at 5% 41 0.029 NS 0.220 0.026 NS 0.696 NS NS 0.37 0.006 0.069 0.043 6.8 271 86

Table 1.Yield, root and shoot parameters of mungbean as affected by the water treatments

Figure 2. Root architecture of a) ML267 andb) WGG37 at 42DAS


the cultivars under sufficient soil moisture conditions mightbe due to the genotypic influence of the cultivars. Further,maximum TRL was achieved at a late stage by WGG37 whichis significantly conspicuous as was quoted by Jordan et al.(1979) while high value was observed at 42DAS for ML267(Subba Reddy et al. 1999). This was in conformity with theresults obtained by Yantai et al. (2011) as was quoted earlier,that the pulses peak at flowering stage in achieving maximumroot component. Further according to Sharma et al. (2007) thebiomass allocation to roots reduced from 22% to 12.3% fromfull bloom stage to harvest. More fine roots and increasedTRL sustained ML267 in countering drought effectively.Variability in Root Architecture (ML267 Vs WGG37)

Root architecture is the study of spatial configurationof roots profile wise. In this experiment, we considered TRL,RLD, RSA (Root Surface Area) depth wise to explain rootarchitecture of these two genotypes of mungbean both underwater sufficient and limited environments.

During water sufficient conditions, total root length(TRL) and root length density (RLD) in both the genotypeswere decreasing as we go deep into the soil since the soilmoisture available was sufficient at top soil depth. However,initial soil moisture deficits (veg stage) increased root lengthin WGG37 at a soil depth of 15-30cm and further to the deeperdepths as we go into the soil profile with the progressing cropgrowth. This shift of root length and root length density wassignificant in ML267. Cultivar ML267 when grown under waterlimited environment (Fig 3 & 4), resulted in more TRL andRLD at deeper depths 15-45cm (42DAS) and increased RLDover WGG37 might have enhanced water uptake from deeperlayers (Zhang et al. 2009) contributing to the drought toleranceof the cultivar. As proved by Songsri et al. (2008) though thesurface layers dried out, the small root part in the subsoilmight be responsible for major water uptake. Therefore,adaptive spatial root distribution is one of the droughtalleviation strategies of the dryland crop plant. Therefore,

according to Mannur et al. (2009) root length has someimportance with respect to moisture extraction from deeperlayers of the soil.

Figure 3. Root architecture of ML267 with and withoutsoil moisture at 42DAS

Figure 4. Effect of soil moisture treatments on RLD of twomungbean cultivars in the soil profile

ML267FC

0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40

0-15

15-30

30-45

Soil

dept

h(c

m)

Root Length Density (cm cm-3)

ML267 33.3%AWC

0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40

0-15

15-30

30-45

Soil

dep t

h(c

m)


WGG37FC

0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40

0-15

15-30

30-45

Soil

dept

h(c

m)


WGG37 33.3%AWC

0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40

0-15

15-30

30-45

Soil

dept

h(c

m)


22DAS

42DAS

69DAS


Conspicuous root proliferation in the top soil depth at69DAS in WGG37 specifies more root partitioning even atlater stages which may not be conducive to rapid recovery ofcrop growth and efficient pod set (Turk et al. 1980).

Both the genotypes recorded maximum RSA at 42DAS.Root surface area recorded by these two genotypes underwell watered and moisture limited environments was same,except that cultivar WGG37 with sufficient irrigation wasobserved to have more RSA at 42DAS than at later stage (69DAS) while it was vice versa under soil moisture deficitconditions (Table 1).Relationship between Root Parameters and Yield

At field capacity, WGG37 with its more TRL, RLD at69DAS, more root dry weight and root shoot ratio with lowmean root diameter yielded 729 kg ha-1 which was 7% morethan ML267 (678 kg ha-1). However, under soil moisture deficitenvironments, ML267 performed (462 kg ha-1) better thanWGG37 (338 kg ha-1) by 27%. This might be due to more TRL,RLD with deeper soil depths at 42DAS for soil moisture. Incase of WGG37, more partitioning towards root componentsat delayed age of 69DAS and confinement of roots at the topsoil depth due to sensitivity to water deficits at 22 DAS hasled to reduced yields (Table 1).Methodology

Though every researcher appreciate the efficiency of3D imaging, still 2D imaging techniques are easily accessible,technically simple (Pierret et al. 2003) and may be consideredas a possible relevant option for observing positioning ofroots. In this methodology, although limitation in the size ofroot box is a constraint, care was taken to consider field levelsingle plant spacing for the chamber size. 2D Root architectureimage and root measurement at different soil profile depthscould be possible in this methodology.

The results suggest the suitability of the cultivar ML267to conditions ensconced with intermittent moisture stressperiods due to enhanced TRL, RLD and fine roots at deeperdepths especially at 15-45cm and during water sufficientsituations, WGG37 though performed significantly better thanML267 could further be improved by reducing morepartitioning towards root at later stages of crop growth.

Further, Root chamber-Pin board method may be helpfulin studying the effect of soil and fertility factors on rootarchitecture in addition to soil moisture. Therefore, thisindigenized Root chamber-Pin board method is recommendedfor study of root architecture under controlled conditions.

ACKNOWLEDGEMENT

The authors are thankful to the SERC of ‘Department ofScience and Technology, Govt. of India’ for funding theproject on “Root Proliferation” and also to ICAR., India.

REFERENCES

Andersson A, Johansson E and Oscarson P. 2005. Nitrogen redistributionfrom roots in post-anthesis plants of spring wheat. Plant Soil 269:321-332.

Bauerle TL, Richards JH, Smart DR and Eissenstat DM. 2008. Importanceof internal hydraulic redistribution for prolonging the lifespan ofroots in dry soil. Plant,Cell & Environment 31: 177–186.

Campbell BD, Grime JP and Mackey JML. 1991. A trade-off betweenscale and precision in resource foraging. Oecologia 87: 532–538.

Doussan C, Pagès L and Pierret A. 2003. Soil exploration and resourceacquisition by plant roots: an architectural and modeling point ofview. Agronomie 23: 419–431.

Eissenstat DM and Caldwell MM. 1988. Competitive ability is linkedto rates of water extraction. A field study of two aridland tussockgrasses. Oecologia 75: 1–7.

Eissenstat DM, Whaley EL, Volder A and Wells CE. 1999. Recovery ofcitrus surface roots following prolonged exposure to dry soil. Journalof Experimental Botany 50: 1845–1854.

Eissenstat DM and Yanai RD. 2002. Root lifespan, efficiency andturnover. Plant Roots, the hidden half Pp 221-238. Waisel Y EshelA and Kafkafi U (Eds) Marcel Dekker, NewYork.

Gomez KA and Gomez AA. 1984. Statistical procedures for Agriculturalresearch. Published by John Wiley & Sons, Inc.

Gooding M J, Pepler S, Ford KE and Gregory PJ. 2005. Cultivar, fungicideand foliar urea effects on wheat grain yields of dry matter, nitrogenand sulphur: associations with root distributions after ear emergence.In: Roots Soil Environment II pp179-186. Foulkes J Russell GHawkesford M Gooding M Sparkes D and Stockadale E (Eds) Aspectsof Applied Biology 73. Association of Applied Biology, UK.

Hodge A. 2004. The plastic plant: root responses to heterogeneoussupplies of nutrients. New Phytologist 162: 9–24.

Jordan WR, Miller FR and Morris DE. 1979. Genetic variation in rootand shoot growth of sorghum in Hydroponics. Crop Science 19:465-472.

Kage H, Kochler M and Stutzel H. 2004. Root growth and drymatterpartitioning of cauliflower under drought stress conditions:measurement and simulation. European Journal of Agronomy 20:379-394.

Kosola KR and Eissenstat DM. 1994. The fate of surface roots of citrusseedlings in dry soil. Journal of Experimental Botany 45: 1639–1645.

Mannur DM, Salimath PM and Mishra MN. 2009. Evaluation ofsegregating populations for drought related morphological andphysiological traits in chickpea. Journal of Food Legumes 22(4):233-238.

Munoz-Romero Veronica, Benitez- Vega Jorge, Lopez-Bellido Luis andLopez-Bellido Rafael. 2010. Monitoring wheat root developmentin rainfed vertisol-tillage effect. European Journal of Agronomy33: 182-187.

Pandey RK, Herrera WAT, Villegas A N and Pendleton JW. 1984. Droughtresponse of grain legumes under irrigation gradient: III. Plant growth.Agronomy Journal 76: 557- 560.

Pierret alain, Claude Doussan, Emmanuella Garrigues and John McKirby. 2003. Observing plant roots in their environment: currentimaging options and specific contribution of two-dimensionalapproaches. Agronomie 23: 471-479.


Price A H, Steele K A, Moore BJ and Jones RGW. 2002. Upland ricegrown in soil-filled chambers and exposed to contrasting waterdeficit regimes. I: Root distribution, water use and plant water status.Field Crops Research 76: 11–24.

Sharma KD, Pannu RK, Tyagi PK, Chaudhary BD and Singh, DP. 2007.Effect of soil moisture stress on biomass partitioning and yield ofchickpea genotypes. Journal of Food Legumes 20(1): 71-74.

Songsri P, Jogloy S, Vorasoot N, Akkasaeng C, Patanothai A and HolbrookCC. 2008. Root distribution of drought resistant peanut genotypesin response to drought. Journal of Agronomy and Crop Science.194: 92-103.

Subba Reddy G, Gangadhar Rao D, Maruthi V and Kameshwar Rao V.1999. Root growth of sorghum, castor and pigeonpea exposed tointermittent drought. Indian Journal of Dryland AgriculturalResearch & Development 14(2): 118-122.

Turk KJ, Hall AE and Asbell CW. 1980. Drought adaptation of cowpea.I. Influence of drought on seed yield. Agronomy Journal 72: 412-420.

Vegapareddy M, Richter GM and Goulding KWT. 2010. Using digitalimage analysis to quantify the architectural parameters of rootsgrown in thin rhizotrons. Plant Biosystems 144: 2, 499-506.

Waisel Y and Eshel A. 2002. Functional diversity of various constituentsof a single root system. Plant Roots, the hidden half pp157-174.Waisel Y Eshel A Kafkafi U (Eds) Marcel Dekker, NewYork.

Yantai Gan, Liping Liu, Herb Cutforth, Xiaoyu Wang and Greg Ford.2011. Vertical distribution profiles and temporal growth patternsof roots in selected oilseeds, pulses and spring wheat. Crop andPasture Science 62(6): 457-466.

Zhang Xiying, Suying Chen, Hongyong Sun, Yanmei wang and LiweiShao. 2009. Root size, distribution and soil water depletion asaffected by cultivars and environmental factors. Field CropsResearch 114: 75-83.


Selection parameters for pigeonpea (Cajanus cajan L. Millsp.) genotypes at earlygrowth stages against soil moisture stressANUJ KUMAR SINGH, J.P. SRIVASTAVA, R.M. SINGH1, M.N. SINGH1 and MANOJ KUMAR1

Department of Plant Physiology, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi - 221005,Uttar Pradesh, India; Department of Genetics and Plant Breeding1, Institute of Agricultural Sciences, Banaras HinduUniversity, Varanasi - 221005, Uttar Pradesh, India; Email: [email protected](Received : July 11, 2013 ; Accepted : December 09, 2013)

ABSTRACT

Twenty pigeonpea genotypes were screened for terminalmoisture deficit at early growth stages to identify suitablephysiological parameters. Seeds were sown in plastic bags(30cm×15cm) containing 2.5 kg soil. Moisture stress wasimposed after 24 days of sowing. The physiological parametersviz., relative water content (RWC), cell membrane injury (CMI)due to thermal and osmotic stresses and chlorophyll stabilityindex (CSI) were determined using first fully mature leafletsfrom top of the plants grown in net house. These parameterswere correlated with their yield and yield attributes grown infield under rainfed conditions. Genotypes with higher RWC,lower CMI and high CSI during moisture deficit periodexhibited higher pods plant-1, seeds pod-1 and grain yield plant-

1. These physiological traits may be utilized for developmentof high yielding drought tolerant varieties and/or developmentof CMS based drought tolerant hybrids.

Key words: CMI, CSI, RWC, correlation, moisture stress tolerance.

Pigeonpea (Cajanus cajan L. Millsp.), is one of the majorfood legume crops of the tropics and sub-tropics. India hasthe largest acreage under pigeonpea (3.90 mha) with a totalproduction and productivity of 2.89 mt and 741 kg ha-1,respectively (DAC, 2011). Among several abiotic factors,drought is a key factor reducing crop productivity due towater loss which leads to decrease in CO2 uptake adverselyaffecting rate of photosynthesis and stomatal conductance(Federick et al. 1989). As pigeonpea is drought tolerant cropand has a large variation for maturity periods it is widelyadapted to a range of environments and cropping systems.Broadly, four maturity groups are recognized in pigeonpea,i.e., extra early (90 – 120 days), early (120 – 150 days), medium(150 – 200 days) and late (200 – 300 days). Variations of differentmaturity groups have direct relevance on the survival andfitness of the crop in different agro-ecological niches(Choudhary, 2011).

According to Kumar et al. (2011) a progressive waterstress causes significant physiological and biochemicalchanges in pigeonpea. They suggested that RWC could beused to select high yielding genotypes under water deficitenvironment as they maintain high cell turgor. Cell damagedue to abiotic stresses may also be quantified by measuringcell membrane injury and chlorophyll stability index (Singh et

al. 1992; Kumar et al. 2011). Chlorophyll stability duringdrought had been a promising criterion for selection againstdrought in peanuts (Arunyanark et al. 2008). It had beenpointed out that drought stress, imposed at differentphonological stages influenced yield differently in pigeonpea(Nam et al. 2001). In present study, an attempt was made tocorrelate the physiological parameters like cell membrane injurydue to thermal and osmotic stress, chlorophyll stability indexand relative water content under moisture stress at earlyphenological stages with yield and yield attributes inpigeonpea.


Twenty pigeonpea genotypes viz., KPBR 80-2-1, SON103, F358-B, ICP 6579, IPA 16-F, ICP 11204, MA96 SBH-56, ICP11887, NDA 1, MAL 13, BAHAR, MA 6, ICP 2506, MA98PTH-2, SL 22-2-3, ICP 13857, JKM 7, ICP 5458, MA98 DEO-89and ICP 8451 were selected for present study. The experimentswere conducted in plastic bags (30cm×15cm, containing 2.5kg soil) in the wired net house as well as in field during 2011-12 at Agricultural Research Farm, BHU, Varanasi and protectedfrom rains using polythene sheets. After germination threehealthy seedlings of uniform size were maintained in eachbag. Moisture stress was created by withholding irrigationafter 24 days of sowing. Observations were recorded at 6, 12and 18 days after withholding irrigation pertaining to relativewater content, cell membrane injury and chlorophyll stabilityindex. All observations were recorded on first fully expandedleaflets from top of the plants in three replications. Leaf sampleswere collected in plastic bag between 10 – 11 AM. The leafdisks of 1 cm in diameter were used for the analysis.

The relative water content (RWC) was estimatedfollowing procedure of Weatherley (1950) using the formula;RWC= (Fresh weigh – Dry weigh) / (Saturated weigh – Dryweigh) × 100. The cell membrane injury due to osmotic orthermal stress was estimated in uppermost fully expandedleaf according to procedure of Blum and Ebercon (1981) andcalculated by the formula CMI= [1-(1-T1/T2)/ (1-C1/C2)] × 100,where, T and C refer to the conductivity of treatment andcontrol and subscripts 1 and 2 indicates initial (beforeautoclaving) and final (after autoclaving) conductivity,respectively. The chlorophyll extraction was done by the


method of Hiskox and Israelstam (1979) and total chlorophyllwas calculated as per Arnon (1949). The chlorophylldestruction due to temperature stress was measured by methodof Murthy and Majumdar (1962) called chlorophyll stabilityindex CSI= (C1/C2) × 100 where, C1 and C2 are chlorophyllcontents in temperature treated and control samples,respectively.

Above mentioned genotypes were also grown inRandomized Block Design under rainfed field condition withthree replications and five plants were randomly selected fromeach genotype in each replication for yield and yield attributesviz., days to maturity, pods plant-1, seeds pod-1, 100-seedweight (g) and seed yield plant-1 (g).


Physiological parameters: Significant differences wererecorded for RWC among genotypes, stages and theirinteractions (Table 1). On an average RWC decreased steadilywith an increase of stress duration. Through averageperformance over stages, it was observed that differentgenotypes had variable RWC. Some of the genotypes viz.,KPBR 80-2-1, SON 103, F358 B, ICP 6579, IPA 16-F, ICP 11204,NDA-1, MAL 13 and BAHAR maintained average RWC morethan 80%, while genotypes viz., ICP 13857, SL 22-2-3, ICP5458 and ICP 8451 registered less than 70% and rest of thegenotypes showed values between 70-80%. It is interesting

to note that KPBR 80-2-1 (89.68%) maintained the maximumRWC at all the stages, and ICP 8451 the minimum among allthe studied genotypes. Decrease in relative water content,water potential, osmotic potential and turgor potential due tomoisture stress has also been observed by other workers(Coyne et al. 1982 and Kimani et al. 1994). If the ability tomaintain high water status can be considered as an indicationof drought tolerance, as suggested by Matin et al. (1989),then among the studied genotypes KPBR 80-2-1 may be rankedas the most tolerant and ICP 8451 as highly susceptible.

Data regarding chlorophyll stability index (CSI) showedsignificant differences with respect to genotypes, stages andtheir interactions (Table 2). Chlorophyll stability indexdecreased with the increase in stress duration. On an averageCSI was the maximum in KPBR 80-2-1 (91.20%) and theminimum in ICP 8451 (44.38%). Genotypes KPBR 80-2-1, SON103, F358-B and ICP 6579 having more than 80% CSI after 18days of stress show high stability of chlorophyll under thermalstress, while those with less than 50% (ICP 13857, MA98-DE-O89 and ICP 8451) indicate susceptibility to thermal stress.Reduction in chlorophyll stability also indicates reduction ofchlorophyll content as has been reported in drought stressedcotton (Mssacci, 2008) Chlorophyll content also decreasedsignificantly under higher water deficit in sunflower plants(Kiani et al. 2008) and Vaccinium myrtillus (Tahkokorpi et al.2007).

Table 1. Relative water content (%) in leaves of pigeonpea genotypes at increasing moisture stress period.Stage (Days after withholding irrigation) Genotype

0 6 12 18 Mean

KPBR80-2-1 95.50 (77.75) 91.23 (72.74) 86.00 (68.03) 86.00 (68.03) 89.68 SON103 94.00 (75.82) 90.23 (71.76) 81.50 (64.53) 80.34 (63.65) 86.52 F3 58B 85.54 (67.62) 81.34 (64.38) 85.54 (67.62) 80.56 (63.79) 83.25 ICP6579 91.00 (72.54) 79.56 (63.08) 80.50 (63.79) 77.56 (61.68) 82.16 IPA16F 90.56 (72.05) 83.56 (66.03) 80.20 (63.58) 76.45 (60.94) 82.69 ICP11204 85.65 (67.80) 85.64 (67.70) 70.76 (58.00) 79.50 (45.00) 80.39 MA96SBH56 85.00 (67.21) 84.00 (66.42) 71.35 (57.61) 70.00 (56.79) 77.59 ICP11887 89.56 (71.09) 75.50 (60.33) 81.23 (64.30) 71.20 (57.54) 79.37 NDA1 85.66 (67.70) 81.23 (64.30) 80.67 (63.87) 75.00 (60.00) 80.64 MAL13 91.00 (72.54) 85.00 (67.21) 74.50 (59.67) 70.10 (56.85) 80.15 BAHAR 88.89 (70.45) 82.00 (64.90) 86.45 (68.44) 77.00 (61.34) 83.59 MA6 88.50 (70.18) 71.00 (57.42) 75.50 (60.33) 55.00 (47.87) 72.50 ICP2506 91.45 (72.95) 77.00 (61.34) 75.00 (60.00) 70.00 (56.79) 78.36 MA98PTH2 81.34 (64.45) 72.34 (58.31) 65.54 (54.03) 65.00 (53.73) 71.06 SL22-2-3 85.00 (67.21) 73.00 (58.69) 66.00 (54.33) 53.00 (46.72) 69.25 ICP13857 88.86 (70.45) 70.00 (56.79) 64.80 (53.61) 55.65 (48.22) 69.83 JKM7 88.00 (69.73) 75.50 (60.33) 60.00 (50.77) 59.00 (50.18) 70.63 ICP5458 85.00 (67.21) 74.00 (59.34) 65.50 (54.03) 50.50 (45.29) 68.75 MA98DEO89 85.45 (67.54) 78.00 (62.03) 63.40 (52.77) 55.00 (47.87) 70.46 ICP8451 81.00 (64.16) 70.20 (56.91) 33.90 (35.60) 26.20 (30.80) 52.83 Mean 87.85 79.02 72.42 66.65

Particular SE (d) CD (1%) Genotype 1.05 2.10

Stage 0.47 1.21 Genotype × Stage 2.10 5.40

The value in parenthesis represents the angular transformed values. Plants were grown in plastic bags of size (30cm×15cm) containing 2.5 kg soil.Water deficit stress was imposed by withholding irrigation after 24 days of sowing.

Singh et. al., : Selection parameters for pigeonpea (Cajanus cajan L. Millsp.) genotypes at early growth stages against soil 9 9

Table 2. Chlorophyll stability index (%) of pigeonpea genotypes at incresing moisture stress period.

Values in parentheses represent the angular transformed values. Plants were grown in plastic bags of size (30cm×15cm) containing 2.5 kg soil. Waterdeficit stress was imposed by withholding irrigation after 24 days of sowing.

Stage (Days after withholding irrigation) Genotype 0 6 12 18

Mean

KPBR80-2-1 95.80 (78.17) 95.00 (77.08) 88.00 (69.73) 86.00 (68.03) 91.20 SON103 94.00 (75.82) 89.40 (71.00) 85.00 (67.12) 80.00 (63.43) 87.10 F3 58B 94.50 (76.44) 88.46 (70.09) 80.50 (63.79) 78.65 (62.44) 85.53 ICP6579 88.43 (70.09) 86.26 (68.19) 82.45 (65.20) 75.23 (60.13) 83.09 IPA16F 84.25 (66.58) 80.00 (63.43) 75.00 (60.00) 70.20 (56.91) 77.37 ICP11204 85.00 (67.21) 81.23 (64.30) 75.34 (60.20) 71.20 (57.54) 78.19 MA96SBH56 83.70 (66.19) 80.65 (63.87) 70.00 (56.79) 59.50 (50.48) 73.46 ICP11887 82.90 (65.57) 75.60 (60.40) 69.60 (56.54) 65.57 (54.03) 73.42 NDA1 88.24 (69.91) 78.00 (62.03) 68.76 (55.92) 72.45 (58.31) 76.86 MAL13 81.00 (64.16) 70.60 (57.17) 65.50 (54.03) 60.40 (51.00) 69.38 BAHAR 81.80 (64.75) 71.50 (57.73) 60.90 (51.30) 51.00 (45.57) 66.30 MA6 79.80 (63.29) 67.80 (55.43) 55.00 (47.87) 48.50 (44.14) 62.78 ICP2506 80.14 (63.43) 65.40 (53.97) 50.45 (45.43) 45.60 (42.48) 60.40 MA98PTH2 79.50 (63.08) 62.40 (52.18) 45.50 (42.42) 39.00 (38.65) 56.60 SL22-2-3 77.70 (61.80) 58.30 (49.80) 40.80 (39.70) 33.70 (35.50) 52.63 ICP13857 75.50 (60.33) 55.60 (48.22) 35.00 (36.27) 29.80 (33.09) 48.98 JKM7 85.50 (67.62) 60.90 (51.30) 30.65 (33.58) 30.90 (33.71) 51.99 ICP5458 84.40 (66.66) 58.90 (50.13) 35.67 (36.63) 25.80 (30.53) 51.19 MA98DEO89 85.10 (67.29) 65.00 (53.73) 25.10 (30.65) 18.80 (25.76) 48.50

ICP8451 86.00 (68.03) 61.80 (51.83) 19.20 (26.00) 10.50 (18.90) 44.38 Mean 84.66 72.64 57.92 52.64




Table 3. Cell membrane injury (%) due to osmotic stress in leaf tissues of pigeonpea genotypes at increasing moisture stress period.


Mean

KPBR80-2-1 7.86 (16.22) 11.80 (20.09) 15.60 (23.26) 20.90 (27.20) 14.04 SON103 15.00 (22.79) 22.00 (27.97) 25.00 (30.00) 31.00(33.83) 23.25 F3 58B 17.80 (24.95) 21.20 (27.42) 28.50 (32.27) 28.00 (31.95) 23.88 ICP6579 16.88 (24.20) 25.50 (30.33) 35.00 (36.27) 38.00 (38.06) 28.85 IPA16F 15.90 (23.50) 28.45 (32.20) 34.50 (35.97) 37.00 (37.46) 28.96 ICP11204 17.80 (24.95) 33.00 (35.06) 29.00 (32.58) 42.00 (40.40) 30.45 MA96SBH56 19.87 (26.42) 24.50 (29.67) 44.00 (43.85) 46.00(42.71) 33.59 ICP11887 17.80 (24.95) 28.00 (31.95) 45.30 (42.30) 48.50 (44.14) 34.90 NDA1 18.45 (25.40) 29.00 (32.58) 42.00 (40.40) 50.00 (45.00) 34.86 MAL13 19.50 (26.21) 35.00 (36.27) 49.50 (44.71) 51.50 (45.86) 38.88 BAHAR 21.00 (27.27) 35.50 (36.57) 45.50 (42.42) 55.50 (48.16) 39.38 MA6 19.20 (25.99) 38.00 (38.06) 45.00 (42.13) 50.50 (45.29) 38.18 ICP2506 20.00 (26.57) 35.27 (36.39) 48.51 (44.14) 50.00 (45.00) 38.45 MA98PTH2 18.70 (25.62) 35.00 (36.27) 54.00 (47.29) 58.56 (49.89) 41.57 SL22-2-3 14.56 (22.38) 36.00 (36.87) 58.67 (49.95) 61.55 (51.65) 42.70 ICP13857 18.97 (25.77) 37.80 (37.94) 49.00 (44.43) 56.80 (50.07) 40.64 JKM7 17.80 (24.95) 36.50 (37.17) 51.00 (45.57) 54.00 (47.29) 39.83 ICP5458 22.34 (28.18) 37.98 (38.00) 54.00 (47.29) 55.00 (47.87) 42.33 MA98DEO89 21.80 (27.83) 41.89 (40.28) 55.50 (48.16) 60.00 (50.77) 44.80 ICP8451 23.00 (28.66) 42.34 (40.57) 65.00 (53.73) 72.00 (58.05) 50.59 Mean 17.34 30.51 42.22 46.90




Table 4. Cell membrane injury (%) due to thermal stress in leaf tissues of pigeonpea genotypes at increasing moisture stressperiod


Mean

KPBR80-2-1 9.00 (17.46) 11.50 (19.80) 24.80 (29.87) 32.57 (34.76) 19.47 SON103 13.50 (21.72) 24.70 (29.36) 42.54 (40.69) 57.80 (49.49) 34.64 F358B 14.50 (22.38) 26.80 (31.20) 33.76 (41.38) 35.90 (36.80) 30.24 ICP6579 17.80 (24.95) 28.43 (32.20) 42.89 (40.86) 49.50 (44.71) 34.66 IPA16F 18.50 (25.47) 32.67 (34.82) 41.40 (40.05) 48.00 (43.85) 35.14 ICP11204 18.00 (25.10) 32.00 (34.45) 42.80 (40.86) 47.80 (43.74) 35.15 MA96SBH56 17.89 (24.95) 35.00 (36.27) 46.00 (42.71) 51.25 (45.69) 37.54 ICP11887 19.50 (26.21) 40.00 (39.23) 48.56 (44.14) 55.50 (48.16) 40.89 NDA1 19.90 (26.49) 36.00 (36.87) 45.67 (42.48) 58.00 (49.60) 39.89 MAL13 23.40 (28.93) 37.80 (37.94) 48.70 (44.26) 55.00 (47.87) 41.23 BAHAR 26.00 (30.66) 38.50 (38.35) 48.00 (43.85) 52.50 (46.43) 41.25 MA6 22.60 (28.39) 42.80 (40.86) 51.50 (45.86) 58.00 (49.60) 43.73 ICP2506 27.50 (31.63) 41.20 (39.93) 50.34 (45.17) 56.56 (48.73) 43.90 MA98PTH2 26.50 (30.98) 43.76 (41.38) 50.67 (45.34) 65.34 (53.91) 46.57 SL22-2-3 27.80 (31.82) 44.50 (41.84) 58.00 (49.60) 68.00 (55.55) 49.58 ICP13857 25.30 (30.20) 45.80 (42.59) 59.00 (50.18) 65.00 (53.73) 48.78 JKM7 19.90 (26.49) 44.67 (41.90) 61.00 (51.35) 68.00 (55.55) 48.39 ICP5458 28.70 (32.39) 49.76 (44.83) 64.50 (53.43) 68.50 (55.86) 52.87 MA98DEO89 26.80 (31.18) 47.65 (43.62) 64.89 (53.81) 80.60 (63.90) 54.99 ICP8451 25.00 (30.00) 48.90 (44.37) 65.76 (54.15) 84.40 (66.70) 56.02 Mean 20.39 36.12 48.23 56.01 40.18




Table 5. Yield and yield attributes of pigeonpea genotypes under rainfed condition.

Genotype Days to maturity Pods plant-1 Seeds pod-1 Test weight (g) Seed yield plant-1 (g) KPBR 80-2-1 234.33 802.33 3.60 12.47 173.29 SON 103 244.67 386.67 4.00 12.58 165.56 F3 58 B 225.33 726.17 3.37 9.37 161.44 ICP 6579 236.00 786.00 3.57 7.62 147.05 IPA 16F 229.00 577.56 3.59 9.69 143.88 ICP 11204 235.33 728.33 3.70 8.47 137.21 MA96SBH56 233.67 411.00 3.63 10.65 117.27 ICP 11887 212.00 601.33 3.23 7.88 93.82 NDA 1 226.44 211.11 3.74 10.06 77.73 MAL 13 205.44 266.76 3.41 13.73 67.99 BAHAR 242.00 378.30 3.37 11.51 66.26 MA6 225.33 283.89 3.27 10.73 56.93 ICP 2506 213.00 365.17 3.30 7.21 60.50 MA 98PTH2 224.67 112.67 4.52 15.57 52.16 SL 22-2-3 243.00 140.33 4.32 12.28 47.78 ICP 13857 239.67 372.33 4.26 7.21 31.06 JKM 7 230.00 105.33 5.76 13.35 33.40 ICP 5458 211.67 155.33 5.21 10.96 28.70 MA 98DEO89 225.00 104.93 4.32 9.72 17.66 ICP 8451 222.00 152.33 3.57 7.41 15.76 SE mean± 0.090 53.35 0.17 0.10 1.12 CD (5%) 0.183 108.04 0.35 0.21 2.26

Plants were grown in field under rainfed condition with three replications and five plants from each genotype were selected in each replication foryield and yield attributes.

Singh et. al., : Selection parameters for pigeonpea (Cajanus cajan L. Millsp.) genotypes at early growth stages against soil 101

Per cent cell membrane injury (CMI) due to osmoticstress in first fully expanded leaves from top is presented inTable 3. Among genotypes, stages and their interactions thesignificant differences were observed for this trait. It isobserved that CMI due to osmotic stress intensified withadvancement in stress duration. On an average, the genotypesviz., KPBR 80-2-1, SON 103, F358-B, ICP-6579, IPA 16-F, ICP11204, ICP 11887, MA96 SBH-56 and NDA 1 exhibited lessthan 35% CMI due to osmotic stress, whereas, genotypesMAL 13, BAHAR, MA 6 and ICP 2506, ICP 13857, SL 22-2-3,JKM 7, ICP 5458, MA 98-PTH-2, MA 98-DEO-89 and ICP 8451exhibited 40% or more CMI due to osmotic stress. Saadalla etal. (1990) reported that heat tolerant genotypes of wheat onthe basis of electrolyte leakage, out yielded sensitive ones by19% under field conditions. Kuo et al. (1993) showed thatvegetable species with low cell membrane injury were morestable in different growing seasons.

Significant differences were recorded in CMI withrespect to genotypes, stages and their interactions due toincrease in thermal stress duration (Table 4). On an average,CMI due to thermal stress was minimum (19.47%) in genotypeKPBR 80-2-1 and the maximum in genotype ICP 8451 (56.02%).The genotypes KPBR 80-2-1, SON 103, F358-B, ICP 6579, IPA16-F, ICP 11204, MA96 SBH-56 and NDA 1 registered lessthan 40% CMI whereas, ICP 5458, MA98 DEO-89 and ICP8451 showed more than 50% CMI due to thermal stress. CMIanalysis being simple, rapid and reproducible is ideal forscreening large populations. The results suggest that thetemperatures in the range of 45 to 55 °C are suitable fordetermining genotypic variation. It is interesting to note thatgenotypes which had higher chlorophyll stability index (CSI)also had less cell membrane injury (CMI) due to thermal aswell as osmotic stress and vice-versa.

Yield attributes and correlation with physiologicaltraits: Significant genotypic differences were observed for20 genotypes under rainfed condition in respect of varioustraits (Table 5). The maturity duration of genotypes rangedfrom 205 (MAL 13) to 244 (SON 103) days. Pods plant-1 wasthe minimum in genotype MA98DEO-89 (104) and themaximum in KPBR 80-2-1 (802). It was evident that genotypeswith relatively longer duration generally produced more pods.The maximum seeds pod-1 were recorded in genotype JKM 7(5.76) and the minimum in ICP 11887 (3.23). 100-seed weightwas maximum in genotype MA98 PTH-2 (15.57 g) and theminimum in ICP 2506 (7.21 g). Seed yield plant-1 ranged from15.76 g to 173.29 g, being the maximum in KPBR 80-2-1 (173.29g) and the minimum in ICP 8451 (15.76 g). The genotypesKPBR 80-2-1, SON 103, F358-B and ICP 6579 having high grainyield plant-1 also had high 100-seed weight, seeds pod-1 andpods plant-1 and high RWC, low CMI due to osmotic as wellas thermal stresses and high chlorophyll stability duringincreasing moisture deficit. Reddy (2001) reported genotypesLRG 30, ICPL 85063 and ICPL 332 as the most suitable for

cultivation under rainfed condition, as they maintained higherRWC and yielded more under soil water deficit. On the basisof present investigation, it is opined that higher RWC in waterdeficit tolerant genotypes leads to maintenance of higher cellmembrane stability and chlorophyll integrity, resulting inhigher pods plant-1 and thereby higher yield. It is also observedthat physiological traits viz., RWC, CSI are positively andsignificantly associated with pods plant-1 and seed yield plant-

1 and CMI (due to osmotic and thermal stress) is negativelycorrelated with pods plant-1 and seed yield plant-1 (Table 6).

In general, high RWC and CSI along with low CMI (dueto osmotic and thermal stress) were exhibited by genotypesSON 103, KPBR 80-2-1, F358-B, ICP 6579, IPA 16-F and ICP11204. These genotypes belong to medium to late durationgroups and gave higher seed yield plant-1 ranging from 137.21to 173.29 g, under rainfed condition. Thus, these genotypesmay be used for development of high yielding drought tolerantvariety and/or development of CMS based drought toleranthybrids. Physiological traits like RWC, CSI and CMI (due tothermal or osmotic stresses) may be used for identification ofsuitable genotypes for rainfed conditions.

ACKNOWLEDGEMENT

Authors greatly acknowledge the financial support fromU.P. Council of Agricultural Research (UPCAR), Lucknowunder Sodh Nidhi Project ‘Development of Drought TolerantCultivars of Pigeonpea’ and the Banaras Hindu University forproviding infrastructure facilities.

REFERENCES

Arnon DI. 1949. Copper enzymes in isolated chloroplasts,polyphenoxidase in Beta vulgaris. Plant physiology 24: 1-15.

Arunyanark A, Jogloy S, Akkasaeng C, Vorasoot N, Kesmala T,Nageswara RC, Wright GC and Patanothai A. 2008. ChlorophyllStability is an Indicator of Drought Tolerance in Peanut. JournalAgronomy and Crop Science 194: 113–125.

Blum A and Ebercon A. 1981. Cell membrane stability as a measure ofdrought and heat tolerance in wheat. Crop Science 21: 43-47.

Choudhary AK. 2011. Effects of pollination control in pigeonpea andtheir implication. Journal of Food Legumes 24: 50-53.

Coyne PI, Bradford JA and Dewald CL. 1982. Leaf water relations andgas exchange in relation to forage production in four Asiaticbluestems. Crop Science 22: 1036-1040.

Table 6. Association of physiological traits with yield andyield components under moisture deficit condition.

**Significant correlation

Parameter Days to

maturity Pods

plant-1 Seeds pod-1

Test weight

Seed yield plant-1

RWC 0.21 0.69** -0.40 0.13 0.81** CMI due to Osmotic Stress

-0.30 -0.81** 0.32 -0.06 -0.94**

CMI due to Thermal Stress

-0.26 -0.84** 0.47* -0.07 -0.94**

CSI 0.21 0.80** -0.51* 0.02 0.96**


DAC 2011. Fourth Advance Estimates of Production of Food grainsfor 2010-11. Agricultural Statistics Division, Directorate ofEconomics & Statistics, Department of Agriculture & Cooperation,Government of India, New Delhi.

Federick JR, Alm DM and Hesketh, JD. 1989. Leaf photosyntheticrates, stomatal resistance and internal CO2 concentrations of soybeancultivars under drought stress. Photosynthetica 23: 575-584.

Hiskox JD and Israelstam GF. 1979. A method for the extraction ofchlorophyll from leaf tissue without maceration. Canadian Journalof Botany 57: 1332-1334.

Kiani SP, Maury P, Sarrafi A and Grieu P. 2008. QTL analysis ofchlorophyll fluorescence parameters in sunflower (Helianthusannuus L.) under well-watered and water stressed conditions. PlantScience 175: 565–573.

Kumar RR, Karajol K. and Naik G.R. 2011. Effect of PolyethyleneGlycol Induced Water Stress on Physiological and BiochemicalResponses in Pigeonpea (Cajanus cajan L. Millsp.). Recent Researchin Science and Technology 3: 148-152.

Kuo CG, Chen HM and Sun HC. 1993. Membrane thermostability andheat tolerance of vegetable leaves. In: C.G. Kuo (Ed.). Adaptationof Food Crops to Temperature and Water Stress. Asian VegetableResearch and Development Center, Shanhua, Taiwan, pp. 160-168.

Matin MA, Brown JH and Ferguson H. 1989. Leaf water potential,relative water content and diffusive resistance as screening techniquesfor drought resistance in barley. Agronomy Journal 81: 100-105.

Mssacci A, Nabiev SM, Pietrosanti L, Nematov SK, Chernikova TN,

Thor K and Leipner J. 2008. Response of photosynthetic apparatusof cotton (Gossypium hirsutum) to the onset of drought stressunder field conditions studied by gas-exchange analysis andchlorophyll fluorescence imaging. Plant Physiology andBiochemistry 46: 189–195.

Murthy KS and Majumdar SK. 1962. Modifications of the techniquefor determination of chlorophyll stability index in relation to studiesof drought resistance in rice. Current Science 31: 470-471.

Nam NH, Chauhan YS and Johansen C. 2001. Effect of timing ofdrought stress on growth and grain yield of extra short durationpigeonpea lines. Journal of Agricultural Science 136: 179-189.

Reddy PJ. 2001. Screening of pigeonpea genotypes for drought toleranceunder black cotton soils of Krishna Godavari zone. Annals of PlantPhysiology 15: 104.

Saadalla MM, Shanahan JF and Quick JS. 1990. Heat tolerance in winterwheat Hardening and genetic effects on membrane thermostability.Crop Science 30: 1243-1247.

Singh M, Srivastava JP and Kumar A. 1992. Cell membrane stability inrelation to drought tolerance in wheat genotypes. Journal ofAgronomy and Crop Science 168: 186-190.

Tahkokorpi M, Taulavuori K, Laine K and Taulavuori E. 2007. After-effects of drought related winter stress in previous and current yearstems of Vaccinium myrtillus L. Environmental and ExperimentalBotany 61: 85–93.

Weatherley PE. 1950. Studies in the water relations of the cottonplant. I. The field measurement of water deficits in leaves. NewPhytologist 49: 81-87.


Optimization of extrusion process variables for development of pulse-carrot pomaceincorporated rice based snacksMD. SHAFIQ ALAM , BALJIT SINGH1 , HARJOT KHAIRA, JASMEEN KAUR and SUNIL KUMAR SINGH

Department of Processing and Food Engineering, Punjab Agricultural University, Punjab, India; 1 Department of FoodScience and Technology, Punjab Agricultural University, Punjab, India; E-mail: [email protected](Received : April 10, 2013 ; Accepted : August 09, 2013)

ABSTRACT

Different experimental combinations of extrusion processvariables i.e. screw speed, die temperature, moisture contentand proportion of ingredients were tried using Box- Behnkendesign of experiments. Response surface methodology (RSM)was used to investigate the effect of screw speed (300-500 rpm),die temperature (120-180° C), moisture content (14-20%) andproportion of ingredients (rice flour: pulse flour: carrot pomacepowder- 60-80%: 10-30%: 10%) on protein, fiber, overallacceptability, colour and texture of extruded products. Theextrusion process was optimized for maximum protein, fiber,overall acceptability and minimum hardness with colourdifference within experimental range. The optimum operatingconditions using selective quality parameters for screw speed,die temperature, moisture content and rice proportion iningredient composition was 340 rpm, 120°C, 20% and 60%,respectively. An analysis of variance (ANOVA) revealed thatamong the process variables, sample formulation followed byscrew speed had the most significant effect on all the responses;die temperature and moisture content had the significantlyhigher effect on overall acceptability and hardness.

Keywords: Carrot pomace, Extrusion, Overall acceptability, Pulseflour, Texture

Extrusion cooking technology is a versatile and efficientmethod of converting raw materials into finished foodproducts. It can replace many conventional processes in foodand feed industry because of its uniqueness among the heatprocesses by subjecting the moistened starchy orproteinaceous foods to intense mechanical shear resultinginto viscous, plastic-like dough which cooks before beingforced through the die. Extrusion cooking has been widelyused in formation of various types of products. However, theincorporation of fruit and vegetable wastes and pulses in ricebased extruded products to make a healthy nutritious snackis still not fully explored.

The food processing industry produces large quantitiesof waste by-products. They are inexpensive, available in largequantities, characterized by a high dietary fiber contentresulting with high water binding capacity and relatively lowenzyme digestible organic matter (Serena and Bach-Knudsen2007). Due to the high dietary fiber content and contrastingdietary fiber properties, the co-products could be used to

change physicochemical properties of diets. A number ofresearchers have used fruits and vegetable by-products suchas apple, pear, orange, peach, blackcurrant, cherry, artichoke,asparagus, onion, carrot pomace (Nawirska and Kwasnievska2005, Grigelmo-Miguel and Martin-Belloso 1999, Ng et al. 1999)as sources of dietary fiber supplements in food. Carrot pomaceis a by-product obtained during carrot juice processing. Thejuice yield in carrots is only 60–70%, and even up to 80% ofcarotene may be lost with left over carrot pomace (Bohm et al.1999). The carrot pomace has good residual amount of all thevitamins, minerals and dietary fiber. The dried carrot pomacecan be used to develop high in fiber content extruded products.

The extruded products which are high in fiber contentcan be further improved in its overall nutritional quality andtaste by the incorporation of pulses. The pulses in the extrudedproduct can pave the way for a snack which is rich in bothfiber and protein content. Lentil (also known as red dahl,masur, massar, and split pea) high in protein especially rich inlysine and leucine, low in fat, and is an excellent source ofdietary ûber and complex carbohydrates. Lentil also containsvitamins and minerals such as B vitamins, calcium,phosphorous and potassium, along with oleic, linoleic andpalmitic acid (Adsule 1996, Agriculture and Agri-Food Canada2006). The nutritional value of lentil and its use in a variety ofculinary applications make it an important commodity in termsof production, and trade.

Every extruded product needs a base raw material whichprovides the overall structure to the product. The major wasteproduct of the cereal industry is broken rice kernels. The brokenrice is a by-product of modern rice milling process. The riceportion can have varying percentages (5 - 7%) of brokenkernels which contain nutritive value similar to whole rice andare available readily at relatively lower cost. These can beeasily used in the formation of rice flour which is an attractiveingredient in the extrusion industry due to its bland taste,attractive white color, hypoallergenicity and ease of digestion(Kadan et al. 2003).

Keeping these points in mind the present study wasplanned with an objective to develop a novel extruded productfrom pulse flour, carrot pomace and rice flour and to study theeffect of extrusion process variables on quality attributes ofdeveloped snacks.



Experimental design: Response surface methodology(RSM) was adopted in the design of experimental combinations(Montgomery 2001, Ding et al. 2005, Altan et al. 2008 a and b,Yagci and Gogus 2008, Alam et al. 2011). A four-factor threelevels Box- Behnken experimental design was employed (Table1). The ingredients used for the carrot pomace based ready-to-eat snack preparation were: Rice flour (R); pulse powder (P,red lentil) and carrot pomace (C). The independent variablesincluded the ingredient composition (pulse powder (10-30%),rice flour (60-80%) and carrot pomace (10%), moisture content(14–20%), screw speed (300-500 rpm) and die temperature (120-180°C). The three levels of the process variables were codedas -1, 0, +1 (Montgomery 2001).The developed extrudedproduct was evaluated on the basis of response variables likecolour (L, a, b, colour difference, chroma and hue angle), texture(hardness, adhesiveness, springiness, cohesiveness,gumminess, chewiness and resilience) and overallacceptability.

Sample preparation: Ingredient formulations forconducting extrusion experiments are given in Table 2. Riceflour (R) was replaced with pulse powder (P) at levels of 10, 20and 30%. In each sample, carrot pomace (C) was added at thelevel of 10% in order to increase the fibre content. Compositeflour (300 gm) was prepared for each sample. In order toenhance the taste of developed product 2% salt was added toeach sample. After mixing, samples were stored in polyethylenebags at refrigerated temperature for 24 h (Stojceska et al. 2008).The moisture content of all the samples was determined afterpreparation by halogen moisture analyzer (Make: MettlerToledo, HR83 Halogen) prior to extrusion experiments.

Levels Independent Variables Symbol Coded Uncoded

1 500 0 400 Screw Speed (rpm) A -1 300 1 180 0 150 Die Temperature (°C) B -1 120 1 20 0 17 Moisture Content (%) C -1 14 1 80:10:10 0 70:20:10 Proportion of

Ingredients-R: P: C (%) D -1 60:30:10

Table 1. Box-Behnken design for response surface methodology

Ingredients preparation

Dry carrot pomace powder preparation: Commercialvariety of carrot was procured from local market, Ludhiana,India. These were washed in running tap water two times toremove extraneous material. Trashes were removed with a planestainless steel knife and trimming was also done. A grinder(Make: Sujata 750 W) was used to extract carrot juice. Thepomace was collected for further studies. The carrot pomacewas pretreated with 1% w/v citric acid. The pretreated pomacewas then kept in a tray dryer at 65°C to bring the desiredmoisture content of dried carrot pomace to 6.0% d.b. Thedried pomace was ground to powder using the same grinder(Make: Sujata 750 W). The pomace powder was stored insealed laminated aluminum films for further use.

Rice and pulse flour preparation: The broken rice andpulse brokens were procured from local market in Ludhiana,Punjab. Those samples were then ground to powder withgrinder (Make: Sujata 750 W).

Extrudates preparation

Extrusion of samples was performed using laboratoryscale co-rotating twin- screw extruder with intermeshingscrews (Model BC21; Clextral, Firminy Cedex, France). Thelength to diameter (L/D) ratio of extruder was 16:1. Temperatureof the first, second and third zone was maintained at 40, 70and 100° C respectively throughout the experiments, whilethe temperature of last zone was varied according toexperimental design. The diameter of die opening was 6mm.Theextruder was thoroughly calibrated with respect to thecombinations of feed rate and the screw speed to be used. Avariable speed die face cutter with four blade knives was usedto cut the extrudates. The product was collected at the dieend and kept at 60 ± 0.5°C in an incubator for 1 h duration toremove extra moisture from the product. The samples werepacked in polythene bags for further analysis.

Quality Parameters

Crude Protein: Macro-kjeldhal method was used todetermine nitrogen. Conversion factor of 5.95 and 6.25 wasused for crude protein estimation of extruded products. 1g ofgrounded sample was digested in Kjeldhal flask with digestionmixture (copper sulphate and potassium sulphate in 1:9 ratio)and concentrated H2SO4 (20 ml) till light green colour appearedand finally cooled. Ammonia released by distillation ofdigested samples with saturated NaOH (80 ml) was capturedin 0.1 N HCl and percent N was estimated. The protein contentwas calculated as per cent nitrogen × factor (Ranganna 1997).

Crude Fiber: Crude fibre of extruded snacks wasestimated using Fibertec (Foss instrument, Sweden). Capsules(for holding the sample) were kept in hot air oven at 100 °C for20 minutes for drying, cooled and weighed. One gram of thegrounded sample was weighed in the capsule (Defatting of

Table 2. Ingredient formulations

Proportion of ingredients (Blends- R:P:C) Ingredients

60:30:10 70:20:10 80:10:10 Rice (gm) 180 210 240 Red Lentil (gm) 90 60 30 Carrot Pomace (gm) 30 30 30 Total (gm) 300 300 300

Alam et. al. : Optimization of extrusion process variables for development of pulse-carrot pomace incorporated rice based 105

samples was done if necessary). Capsules were fixed in therotating stand and put it into the extraction cup; 250 - 275 mlof 1.25 per cent H2SO4 was added to the extraction cup andimmersed the stand into the beaker. Acid extraction was doneby boiling it for 30-40 minutes followed by its washing withhot water. Then alkali washing was done with 1.25 per centNaOH for the same time duration followed by hot waterwashing. Finally, capsules were dried in oven for 2 hours at130 °C and then placed at 550 °C for 5 hours, cooled andweighed for crude fibre estimation (AOAC 2005).

Texture Profile Analysis (TPA)

Textural attributes of extrudates were determined bytexture profile analysis (TPA) using Texture Analyzer, modelTA-XT2i (Stable Micro-Systems, Surrey, England) equippedwith a compression plate P75. The tests were conducted atpre–test speed of 1.0 mm/sec, test speed of 5 mm/sec, posttest speed of 5 mm/s at strain of 25% and trigger force of0.4903 N using load cell of 50kg.

Hardness: Mechanical properties of the extrudates weredetermined by crushing method using a TA-XT2i (StableMicro-Systems, Surrey, England) with a compression plate of75 mm diameter (Kumar et al. 2009). The tests were conductedat pre–test speed of 1.0 mm/sec, test speed of 5 mm/sec, posttest speed of 5 mm/s, strain- 25%, trigger force of 0.4903 N andload cell of 50 kg. The highest first peak value was recordedas this value indicated the first rupture of snack at one pointand this value of force was taken as a measurement forhardness (Stojceska et al. 2008)

Cohesiveness: The ratio of positive force areas underthe second and first compression (A2/A1) was defined ascohesiveness.

Firmness: The height of the force peak on the firstcompression cycle (first bite) was defined as firmness (N).

Springiness or elasticity: The distance that the samplerecovered its height during the time elapsed between the endof the first bite ad start of the second bite (mm).

Gumminess: It is defined as the product of firmness xcohesiveness (N).

Chewiness: It is defined as the product of hardness xcohesiveness x springiness (N-mm)

Adhesiveness: The work necessary to overcome theattractive forces between the surface of the food and thesurface of other materials with which the food comes intocontact (e.g. tongue, teeth, palate).

Colour: The colour property of extruded samples wasmeasured by using Colour Reader CR-10 (Konica MinoltaSensing Inc. Japan). For determination of colour, the samplewas ground to powder with the help of Grinder (Make: Sujata750 W). The powder was completely filled in petridishprovided that no light is allowed to pass during the measuring

process. The ‘L’, ‘a’ and ‘b’ values were recorded at D 65/10°.The colour difference was measured by the equation givenby (Gnanasekharan et al. 1992).

Colour difference = [ (L-L0) 2 + (a-a0)

2 + (b-b0) 2 ]

ORColour difference = [ (L-L0)

2 + (a-a0) 2 + (b-b0)

2 ]1/2

Where; L0, a0 and b0 represent the respective readingsof developed raw sample before extrusion.

The chroma and Hue angle were estimated as-Chroma = (a2 + b2)Chroma = [ (a2 + b2)]1/2

Sensory evaluation: Hedonic scale evaluation methodfor sensory analysis was used to find out the order ofpreference of extruded samples. The samples were evaluatedfor sensory quality on the basis of overall acceptability on a 9point hedonic scale (9-liked extremely to 1-disliked extremely)on the basis of colour, flavour and mouthfeel from semi-trainedpenal of 10 panelists according to the method described byAmerine et al. (1965).

Optimization of process parameters: Response surfacemethodology was applied to the experimental data using acommercial statistical package, Design-Expert version 8.0.7.1(Statease Inc, Minneapolis, USA, Trial version). The samesoftware was used for the generation of response surfaceplots, superimposition of contour plots and optimization ofprocess variables. The response surface and contour plotswere generated for different interaction for any twoindependent variables, while holding the value of other twovariables as constant (at the central value). Such three-dimensional surfaces could give accurate geometricalrepresentation and provide useful information about thebehavior of the system within the experimental design(Cochran and Cox et al. 1964). The optimization of the extrusionprocess aimed at finding the levels of independent variablesviz. Moisture content, Screw speed, Die temperature, and riceflour, which could give maximum protein, fiber and overallacceptability; and minimum hardness with colour change inrange. Desirability, a mathematical method was used forselecting the optimum process values. For several responsesand factors, all goals get combined into one desirabilityfunction. The numerical optimization finds a point thatmaximizes the desirability function.


Protein Content: The protein content of extruded snacksranged from 11.74 to 7.89% (table 3). The results revealed thatthe ingredient composition and screw speed had a significantimpact on the protein content. The other extrusion parametersviz. die temperature and moisture content had a non-significantimpact on protein content of extrudates (table 2).


Contour plots reveal that protein content decreased withthe increase in rice percentage in ingredient composition (fig1). For a given value of screw speed i.e. 300 rpm, the proteindecreased from 11.56% for ingredient proportion containing60% rice to 10.32% for ingredient proportion containing 70%rice and further to 8.26% for ingredient proportion containing80% rice. This trend can be easily explained by the decreasein the percentage of pulse flour.

The screw speed also had a significant impact on theprotein content of extrudates. The protein content in extrudatesdecreased consistently with the increase in screw speed.Contour plots reveal that for given moisture content of 14%,the protein content decreased from 10.25% at the screw speedof 300 rpm to 9.93% at the screw speed of 400 rpm. This decreasefurther continued to 9.54% at 500 rpm screw speed.

Fiber content: The fiber content of the snacks rangedbetween 11.92 to 9.89% respectively with significant impactof ingredient proportion and screw speed (table 3). The other

Fig 1: Contour plots depicting the effect of processparameters on protein content (%)

processing parameters viz. die temperature and moisturecontent had a non-significant impact on the fiber content ofthe extrudates (table 2). Contour plots reveal that fiber contentdecreased with the increase in rice percentage in ingredientcomposition (fig 2). For a given value of screw speed i.e. 300rpm, the protein decreased from 12.00% for ingredientproportion containing 60% rice to 10.78% for ingredientproportion containing 70% rice and further to 10.17% foringredient proportion containing 80% rice.

The screw speed also had a significant impact on theprotein content of extrudates. The protein content in extrudatesdecreased consistently with the increase in screw speed.Contour plots reveal that for given moisture content of 14%,

Fig 2. Contour plots depicting the effect of processparameters on fiber content (%)


the protein content decreased from 10.46% at the screw speedof 300 rpm to 10.26% at the screw speed of 400 rpm. Thisdecrease further continued to 9.54% at 500 rpm screw speed.

Overall acceptability: The overall acceptability forextruded samples ranged from 4.33 to 8.33 on a 9 point hedonicscale (Table 4). The process parameters viz. moisture content,screw speed and die temperature had a significant (P<0.05)effect on overall acceptability of extruded samples whereasthe effect due to ingredient composition was non- significant(Table 3). Contour plots reveal that overall acceptability ofthe product increased with increase in screw speed (fig 3). Fora given moisture content of 14%, the overall acceptabilityincreased from 5.78 at 300 rpm to 7.10 at 400 rpm and finally to8.58 at 500 rpm respectively. This may be explained by bettermixing of components during intensive baro-thermal treatment(higher shearing stress), formation of starch-protein matrixduring processing at the temperature higher than starchgelatinization temperature and higher moisture content in rawmaterials (Moscicki et al. 2007). On the other and the overallacceptability first decreased and then increased with thesubsequent increase in moisture content. For a given value ofscrew speed i.e. 300 rpm, the overall acceptability was 5.78 at14.5% moisture content which decreased to 5.09 at 17%moisture content. With further increase in the moisture contentthe overall acceptability indicated a slight increase to 5.61%at 20% moisture content.

Contour plots reveal that overall acceptability increasedwith the increase in the die temperature. At a given ingredientproportion containing 60% rice the overall acceptabilityincreased from 5.66 to 5.98 with increase in die temperaturefrom 120 to 150°C. The overall acceptability further increasedto 6.81 with the increase in die temperature to 180°C. Althoughthe effect of ingredient composition on overall acceptabilitywas non-significant but it was observed that the overallacceptability decreased with the increase in percentage of

Note: *, ** significant at P<0.05 and P<0.01 respectively; Least Squares Means analysis.

Protein (%) Fiber (%) Overall Acceptability Extrusion Process Variables F value F value F value

Moisture Content (A) 1.63 2.54 14.24* Screw Speed (B) 90.13* 101.96* 42.67*

Die Temperature (C) 0.00 0.00 23.76* Ingredient Composition-R:P:C (D) 1453.55* 739.69* 7.559

AB 0.02 0.02 3.38** AC 4.40** 0.13 0.69 AD 0.41 0.22 0.029 BC 1.53 0.10 0.54 BD 7.27** 11.45* 0.69 CD 0.20 0.46 0.24 A2 2.72 2.83 8.08* B2 0.28 3.14 0.15 C2 0.07 3.36** 1.35 D2 47.99* 52.89* 0.020

C.V (%) 1.37 0.90 7.81 S.D (p=0.05) 0.13 0.096 0.50

Table 3. Analysis of variance of extrusion process variables on protein, fiber and overall acceptability

Fig 3. Contour plots depicting the effect of processparameters on overall acceptability


rice in ingredient composition. For a given value of dietemperature i.e. 120°C, the overall acceptability decreased from5.66 at 60% rice proportion in ingredient composition to 5.39at 80% rice proportion in ingredient composition.

Colour attributes of extrudates

The colour difference (“E) in extruded samples whencompared to the fresh samples ranged from 7.6 to 16.55 (Table6). The overall effect of moisture content, die temperaturescrew speed and flour composition on colour difference was

non-significant (Table 5). The colour difference first increasedand then decreased with the increase in moisture content (fig4). For a given value of screw speed i.e. 300 rpm, the colourdifference increased from 10.53 at 14% moisture content to12.39% at 17% moisture content. The colour difference furtherdecreased to 10.49 at 20% moisture content. On the otherhand colour difference increased with the subsequent increasein screw speed. For the given value of moisture content 14%,the colour difference increased from 10.53 to 11.64 for theincrease in screw speed from 300 to 500 rpm.

Table 4. Experimental data for protein, fiber and overall acceptability using four factor three level Box- Behnken designExtrusion Process Variables

Moisture content (%) Screw speed (rpm) Die temp (°C) Ingredient Composition-R:P:C (%)

Protein (%) Fiber (%) Overall Acceptability

17 400 150 70:20:10 10.01 10.47 5.5 14 400 120 70:20:10 9.83 10.51 7.5 17 300 150 60:30:10 11.74 11.92 5.33 17 400 150 70:20:10 9.99 10.4 6.17 17 300 120 70:20:10 10.24 10.83 4.33 14 400 150 60:30:10 11.02 11.56 6.5 17 400 150 70:20:10 9.94 10.44 6.17 20 300 150 70:20:10 10.2 11.01 6 17 500 150 60:30:10 10.62 11.02 7.17 17 400 120 80:10:10 8.11 10.16 5.17 17 300 150 80:10:10 8.29 10.21 5 20 400 180 70:20:10 9.8 10.62 7 20 400 150 60:30:10 10.74 11.6 5.83 20 400 120 70:20:10 10.11 10.57 5.5 17 300 180 70:20:10 10.12 10.76 5.5 14 400 150 80:10:10 8.09 9.89 6.67 17 400 120 60:30:10 10.93 11.61 5.83 17 500 180 70:20:10 9.74 10.29 8 17 500 120 70:20:10 9.53 10.3 6.1 20 400 150 80:10:10 7.98 10.02 6.17 17 400 180 80:10:10 8.02 10.11 7 14 400 180 70:20:10 10.08 10.49 8.17 17 500 150 80:10:10 7.89 9.96 7.67 20 500 150 70:20:10 9.29 10.39 6.33 14 500 150 70:20:10 9.41 10.32 8.33 17 400 180 60:30:10 10.96 11.69 7.17 14 300 150 70:20:10 10.28 10.91 6.17

Fig 4. Contour plots depicting the effect of process parameters on colour difference


The colour difference decreased and then increased withthe increase in die temperature. According to contour plots,at a given value of rice percentage in ingredient proportioni.e. 60%, the colour difference decreased from 15.72 at 120°Cto 13.69 at 150°C. This value indicated a slight increased to13.85 till the die temperature of 180°C.

The results for L-value for extruded samples rangedfrom 70.95 to 78.1 with most of the samples lying in the rangeof 74 to 76 (Table 6). There was an almost non-significanteffect of various levels of screw speed, moisture contentsand die temperatures on the L-value of extrudates (Table 5).The highest L-values (above 76) were attained above screw

Table 5. Analysis of variance of extrusion process variables on colour attributesColour Attributes

L a b ?E Chroma Hue Angle Extrusion Process Variables

F value F value F value F value F value F value Moisture Content (A) 0.45 6.72* 12.09* 0.45 11.92* 4.83*

Screw Speed (B) 3.02 0.45 0.033 0.034 0.052 0.85 Die Temperature (C) 0.08 1.72 1.53 0.051 1.64 1.27

Ingredient Composition-R:P:C (D) 4.991 2.90 8.77* 3.41** 8.35* 1.20 AB 1.497 1.48 0.70 0.14 0.75 2.39 AC 0.066 1.48 0.050 0.41 0.11 1.91 AD 0.23 0.073 0.31 0.25 0.29 0.057 BC 0.18 0.036 0.87 0.14 0.75 0.013 BD 5.989 0.018 0.089 0.14 0.078 0.030 CD 0.54 0.57 3.13 0.88 2.449 1.02 A2 5.51* 2.47 0.089 3.53** 0.20 3.78** B2 0.62 0.023 0.86 0.017 0.68 0.38 C2 0.06 0.34 0.68 1.18 0.64 0.28 D2 3.466 0.050 3.22 0.033 6.964 0.053

C.V (%) 2.72 21.90 6.16 19.01 6.54 2.45 S.D (p=0.05) 2.04 0.92 1.34 2.31 1.45 1.94

Note: *,** significant at P<0.05 and P<0.01 respectively; Least Squares Means analysis.

Table 6. Experimental data for colour attributes using four factor three level Box- Behnken designExtrusion Process Variables Colour Attributes

Moisture content (%)

Screw speed (rpm) Die temp (°C) Ingredient Composition-

R:P:C (%) L a b ?E Chroma Hue angle

17 400 150 70:20:10 71.7 5.4 22.5 14.96 23.14 76.5014 400 120 70:20:10 77.1 2.85 22.2 10.85 22.38 82.6817 300 150 60:30:10 73.8 4.7 22.5 13.22 22.99 78.2017 400 150 70:20:10 76.6 3.4 21.05 11.01 21.32 80.8217 300 120 70:20:10 71.55 4.7 21.25 15.48 21.76 77.5314 400 150 60:30:10 75.7 5.1 23.4 11.58 23.95 77.7017 400 150 70:20:10 73.6 4.35 20.6 11.99 21.05 78.0820 300 150 70:20:10 74.8 4.25 22.15 11.07 22.55 79.1417 500 150 60:30:10 73.75 5.4 23.9 16.55 24.50 77.2717 400 120 80:10:10 74.35 3.4 19.45 11.04 19.74 80.0817 300 150 80:10:10 76.75 2.9 19.4 7.6 19.62 81.5020 400 180 70:20:10 75.15 3.6 20.75 12.95 21.06 80.1620 400 150 60:30:10 77.15 3.2 21.15 9.92 21.39 81.4020 400 120 70:20:10 75.4 3.85 20.75 11.05 21.10 79.4917 300 180 70:20:10 73.3 4.85 22.9 13.32 23.41 78.0414 400 150 80:10:10 75.45 5.05 22.4 13.37 22.96 77.3017 400 120 60:30:10 74.6 4.85 21.8 14.75 22.33 77.4617 500 180 70:20:10 77.65 4.55 22.7 13.54 23.15 78.6717 500 120 70:20:10 74.15 4.75 23.55 13.99 24.02 78.6020 400 150 80:10:10 74.95 2.65 18.65 9.38 18.84 81.9117 400 180 80:10:10 70.95 5.35 21.55 15 22.20 76.0614 400 180 70:20:10 77.9 4.85 22.8 9.8 23.31 77.9917 500 150 80:10:10 76.8 3.85 21.6 9.2 21.94 79.8920 500 150 70:20:10 77.5 1.35 17.75 9.12 17.80 85.6514 500 150 70:20:10 78.1 4.35 22.2 11.53 22.62 78.9117 400 180 60:30:10 74.2 5.4 24.05 14.36 24.65 77.3514 300 150 70:20:10 75.45 5 24.35 11.76 24.86 78.40


speed of 450 rpm for the samples having moisture contentupto 18% whereas lowest L-values were attained by thecombination of low screw speed (below 350 rpm) and highermoisture content (above 18%). The ingredient compositionhad a non- significant effect on the L-value of extrudedsamples. The die temperature also had an influence on L-value with lower die temperatures led to lower L-values andvice–versa. Thus, highest L-values were obtained by thecombination of higher screw speed, die temperature and lowestmoisture content.

The a-values for extrudates ranged from 1.35 to 5.4 (Table6). The a-value was significantly (P<0.05) influenced bymoisture content (Table 5). The a-value decreasedconsistently with increasing moisture content.

Since the red lentil gives an yellow colour to the sampleafter extrusion cooking, the b-value ranged from 17.75 to 24.35(Table 6). The moisture content and ingredient compositionhad a significant (P<0.05) influence on b-value of flour.Whereas, the screw speed had a non-significant effect on theb-value of extruded samples (Table 5).The highest b-valueswere observed in samples having higher percentage of redlentil in sample and lower moisture content. The higher b-values were recorded below the moisture content of 15%. Onthe other hand, the ingredient composition also had asignificant (P<0.05) impact on b-values. The highest b-valueswere recorded for the composition of 60: 30:10 and vice-versa.This can be easily explained by the high ratio of red lentil inthe composite flour which gave yellow colour to the samplesand increased b-value of the product. The screw speed didnot influence the b-value of extruded samples.

The chroma value for extruded samples ranged from17.80 to 24.86 (Table 6). Chroma value was significantly(P<0.05) influenced by moisture content and ingredientcomposition (Table 5). The highest value of chroma wasrecorded for samples at lowest moisture content having lowestpercentage of rice flour and vice- versa. These results can bedirectly related to the influence of total moisture and ratio ofred lentil on the samples. Screw speed and die temperaturehad a non- significant effect on the chroma value of extrudates.Chroma was also influenced by the die temperature. Thehighest value of chroma was recorded above the dietemperature of 170°C. On the other hand, the screw speed hadalmost no influence on the chroma values of the extrudedsamples.

The values for hue angle for the extruded samples variedfrom 76.05 to 85.65 (Table 6). The hue angle was significantly(P<0.05) influenced by the moisture content of the extrudedsamples (Table 5). The highest hue values were recorded abovethe moisture content of 18%. The screw speed, die temperatureand composition had a non- significant effect on the hue angleof extruded samples. The lowest hue angle was obtained inthe samples having screw speeds below 420 rpm. Also, higherdie temperatures led to lowest hue angle in extruded products

and vice- versa. The ingredient composition also influencedthe hue angle of the extruded products developed with theingredients lowest values being recorded for proportion withrice component below 70% i.e. 70R:20P:10C.

Texture Profile Analysis (TPA)

Fig 5. Contour plots depicting the effect of processparameters on hardness (N)

Hardness: The hardness for extruded samples indicateda variation from 59.89 to 194.31 N (Table 8) with significant(P<0.05) influence of moisture content, screw speed and dietemperature on overall hardness quality of extrudates (Table7). It is clear from fig 5 that the hardness of the extrudedproduct decreased with the increase in the moisture content.At a given value of 300 rpm screw speed, the hardness of theextruded product decreased from 154.29 N to 111.69 N withthe subsequent increase in the moisture content from 14 to20%. The hardness also indicated an increase with the increasein the screw speed of the extrudates. At a given moisturecontent of 14%, the hardness of the sample increased from


Textural Quality Attributes (F values) Extrusion Process Variables Hardness Adhesiveness Springiness Cohesiveness Gumminess Chewiness Resilience

Moisture Content (A) 5.25* 0.99 6.99 3.30* 3.47 2.76 3.12** Screw Speed (B) 10.45* 0.40 0.11 6.92 0.57 0.53 4.02

Die Temperature (C) 5.78* 0.86 0.084* 5.93** 0.041** 1.14* 0.27** Ingredient Composition-R:P:C (D) 34.25 0.076 21.08* 4.34* 3.45 7.54 4.06*

AB 0.35 6.37 6.62* 6.57** 0.68 2.49 10.93** AC 0.29 3.46 8.62 4.64* 1.48* 1.89* 3.77* AD 0.64 1.15 1.70 5.48 6.28 7.27 5.22 BC 1.70 8.89 0.11 0.17 0.30 0.51 0.66 BD 3.18 2.43 0.66** 0.33 0.071 0.60 0.60 CD 1.56 6.70 4.44* 0.56 1.95 1.93 0.14 A2 0.041* 1.12** 19.86* 0.38 0.21 1.78 0.57 B2 6.10 4.11 6.46* 0.20* 2.84* 0.085* 0.69* C2 0.82* 3.08 18.42* 12.31 26.51* 11.26 7.96 D2 10.37 1.30* 27.06* 3.16 16.96* 2.57 2.76

C.V (%) 11.71 225.12 9.55 36.46 41.77 50.98 34.03 S.D (p=0.05) 17.74 7.46 0.027 0.056 1014.79 393.55 0.044

154.28N at 300 rpm to 168.89N at 400 rpm. This value furtherincreased to 169.44N at 500 rpm respectively.

Fig 5. clearly indicates that the hardness of extrudatesincreased with the increase in die temperature while showing

a slight decrease at the higher die temperatures. For a givenrice percentage of 60% in ingredient composition, the hardnessincreased from 117.85N to 181.38N with the increase in dietemperature from 120 to 180°C. The effect of ingredientcomposition on hardness of extrudates was non-significant.

Table 7. Analysis of variance of extrusion process variables on textural attributes

Table 8. Experimental data for textural attributes using four factor three levels Box- Behnken design

Note: *, ** significant at P<0.05 and P<0.01 respectively; Least Squares Means analysis.

Extrusion Process Variables Textural Quality Attributes

Moisture content (%)

Screw speed (rpm)

Die temp (°C)

Ingredient Composition-

R:P:C (%)

Hardness (N) Adhesiveness Springiness Cohesiveness Gumminess Chewiness Resilience

17 400 150 70:20:10 149.4067 -0.314 0.3335 0.126 3924.62 637.488 0.112 14 400 120 70:20:10 110.0807 -0.3565 0.23 0.1225 1801.45 640.04 0.1025 17 300 150 60:30:10 173.2098 -0.516 0.2645 0.074 1339.316 370.134 0.0645 17 400 150 70:20:10 194.3099 -24.3815 0.3665 0.269 5279.393 1287.68 0.2395 17 300 120 70:20:10 107.5563 -0.2625 0.222 0.0675 747.448 166.3805 0.0675 14 400 150 60:30:10 179.4418 -0.053 0.2965 0.151 3644.306 1258.282 0.1445 17 400 150 70:20:10 170.0219 -17.842 0.3695 0.2385 5872.374 1702.16 0.1295 20 300 150 70:20:10 125.8026 -0.02 0.3125 0.211 2543.502 772.2165 0.1905 17 500 150 60:30:10 177.9249 -0.3655 0.228 0.0495 908.79 206.97 0.0515 17 400 120 80:10:10 128.3039 -0.2285 0.2105 0.1905 2477.736 777.0685 0.1545 17 300 150 80:10:10 130.811 -0.01 0.272 0.132 987.87 251.964 0.136 20 400 180 70:20:10 149.2116 -16.1585 0.3425 0.36 5538.055 2101.696 0.284 20 400 150 60:30:10 112.5082 -0.776 0.302 0.278 3628.075 1062.306 0.1535 20 400 120 70:20:10 59.89665 -0.517 0.2315 0.1435 892.704 225.1135 0.115 17 300 180 70:20:10 144.449 -0.2635 0.2635 0.095 1299.693 244.246 0.073 14 400 150 80:10:10 185.323 -0.6895 0.2865 0.17 2017.37 726.46 0.1465 17 400 120 60:30:10 115.3241 -0.031 0.2555 0.071 1485.328 404.8765 0.063 17 500 180 70:20:10 175.9571 -0.3505 0.279 0.1315 576.028 794.6505 0.1095 17 500 120 70:20:10 138.4315 -23.6265 0.194 0.0395 563.4055 107.953 0.0365 20 400 150 80:10:10 164.6938 -0.005 0.274 0.25 3111.04 1093.03 0.226 17 400 180 80:10:10 192.2227 -0.7425 0.404 0.283 3821.6 1976.78 0.2305 14 400 180 70:20:10 171.0555 -0.01 0.271 0.076 1359.559 394.714 0.0725 17 500 150 80:10:10 179.869 -0.246 0.3485 0.1915 3393.573 1182.995 0.1555 20 500 150 70:20:10 151.0783 -0.6875 0.2335 0.0675 1127.829 329.99 0.061 14 500 150 70:20:10 161.1556 -0.235 0.3295 0.1885 3207.361 1105.898 0.1505 17 400 180 60:30:10 186.402 -0.3865 0.21 0.0945 1901.415 553.497 0.0735 14 300 150 70:20:10 154.8279 -0.446 0.251 0.09 2149.839 466.951 0.111


Adhesiveness: Adhesiveness values ranged from -0.005to -24.38 (Table 8). Adhesiveness of extruded samples wasnon-significantly influenced by the process parameters.However, the maximum adhesiveness was observed in thesamples maximum moisture content, screw speeds andminimum die temperatures. The ingredient proportions showednon-significant effect on adhesiveness (Table 7).

Springiness: Springiness ranged from 0.194 to 0.404 inthe extruded samples (Table 8). The statistical results indicatethat springiness was significantly (P<0.05) influenced by dietemperature and ingredient composition used during extrusionprocessing (Table 7). The springiness indicated a significant(P<0.05) increase with subsequent increase in die temperaturewith highest value recorded beyond 168°C. This can be directlyrelated to increase in the level of chemical reactions like starchgelatinization with increasing temperature which influence theplastic nature of the product. The flour composition alsodirectly influenced springiness of the sample as springinessincreased with decrease in ratio of pulse in sample. But, therewas no significant effect of screw speed and moisture onspringiness of extruded products.

Cohesiveness: Cohesiveness values varied from 0.36to 0.39 (Table 8). The overall effect of different processparameters viz. screw speed, die temperature, moisture contentand composition on the cohesiveness of extruded sampleswas significant (P<0.05) (Table 7). It was statistically evaluatedthat cohesiveness was significantly (P<0.05) influenced bymoisture content and flour composition. Lower moisturecontent indicated lower values of cohesiveness in the extrudedsamples and vice versa. However, the cohesiveness was alsodirectly influenced by higher content of rice flour in the sampleas the higher cohesiveness values were recorded for samplescontaining higher rice contents in their composition. The screwspeed and die temperatures had a little influence on thecohesiveness of extruded samples. The higher die temperaturesdenoted to higher values of cohesiveness and vice versa.

Gumminess: The gumminess values of extrudedproducts indicated a large variation from 563.405 to 5872.37(Table 8). The gumminess of extruded products was

significantly (P<0.05) influenced by the combination ofprocess parameters (Table 7). The screw speed, die temperatureand flour composition influenced the overall gumminess ofthe product. The gumminess of product increased withincrease in die temperature indicating maximum value abovethe temperature of 180°C. On the other hand, the minimumvalues were observed below 130°C. The higher moisturecontent also led to increase in gumminess of the product withhighest value recorded above 19 percent. The effect of screwspeed and flour composition on the gumminess of extrudedproducts was minimal. However, the gumminess of extrudedproducts increased subsequently with the increase in screwspeed and percentage of rice in the flour.

Chewiness: The chewiness of extruded productsindicated a large variation from 107.953 to 2101.7 (Table 8).The chewiness of extruded products was significantly (P<0.05)influenced the combination of process parameters with largesignificant (P<0.05) effect due to die temperature (Table 7).The chewiness indicated a large increase with subsequentincrease in die temperature with highest value recorded above162° C. The increase in chewiness due to increase in dietemperature can be owed to the increase in more chewisubstances due to faster chemical reactions which take placeat high temperature. On the other hand, the minimum valueswere observed below 126°C. The screw speed, moisturecontent and flour composition influenced the overallchewiness of the product. The higher chewiness values wererecorded at higher moisture content and screw speed. Theeffect of flour composition on the chewiness of extrudedproducts was also pronounced as greater chewiness wasrecorded for the samples containing rice above 75% and viceversa.

Resilience: The resilience values varied between 0.036to 0.284 (Table 8). The effect of process parameters on theresilience of the extruded products was significant (P<0.05)with greater influence of ingredient composition (Table 7).The ingredient composition used had a large influence on theresilience with higher values recorded for the flour containingrice flour above 75%. On the other hand, the lower resilience

Table 9. Optimum values of extrusion process parameters and responses

Target Experimental Range Extrusion process parameters Min Max

Optimum value Desirability

Moisture content (%) In range 14 20 20 Screw speed (rpm) In range 300 500 340 Die temperature (0C) In range 120 150 120 Rice flour (%) In range 60 80 60 Pulse flour (%) In range 10 30 30 Carrot pomace flour (%) In range 10 10 10 Responses Predicted values Protein (%) Maximize 7.89 11.74 11.32 0.737 Fiber (%) Maximize 11.7 11.92 11.91 Overall Acceptability Maximize 4.33 8.33 5.45 Hardness (N) Minimize 59.89 70.00 58.05 Colour difference In range 7.6 16.55 13.36


values were recorded for flour composition containing riceflour below 65%. Moisture content, screw speed and dietemperature also influenced the resilience of extrudedproducts. The highest values of resilience were obtained athigher moisture contents and die temperature. The screwspeed had a non- significant effect on the resilience of theextruded products.

Optimum conditions for ready-to-eat extruded

hardness with colour difference in range. These constraintsresulted in “feasible zone” of optimum conditions (shadedarea in the superimposed contour plots) (fig 6). The optimumranges of process parameters obtained for development ofextrudetes were: 19.47-20% of moisture content, 120 to 125°Cdie temperature, 333 to 381 rpm screws speed and 60 to 61 %of rice flour with 10% carrot pomace in ingredient composition(table 9).

In order to optimize the process conditions for extrusionprocess by numerical optimization, which finds a point thatmaximizes the desirability function; importance of ‘4’ wasgiven to protein and fiber content while importance of ‘3’ wasgiven to all other parameters. The optimum operatingconditions for screw speed, die temperature, moisture contentand rice content in ingredient composition was 340 rpm, 120°C,20% and 60%, respectively. Corresponding to these values ofprocess variables, the values obtained were 11.32% proteincontent, 11.91%, fiber content, 58.05 N hardness, 5.45 overallacceptability and 13.36colour difference (Table 4). The overalldesirability, which ranges from zero outside of the limits toone at the goal, was 0.737.

It could be concluded from the present study that theresponse surface methodology is effective in optimizingextrusion process parameters for red lentil-carrot pomaceincorporated ready-to-eat rice based expanded product withfeed moisture in the range of 14 to 20%, die temperature 120-180°C, screw speed 300-500 rpm and formulation (rice flour:pulse flour; 60-80%: 10-30%) with 10% carrot pomace flour.Graphical techniques, in connection with RSM, aided inlocating optimum operating conditions, which wereexperimentally verified and proven to be adequatelyreproducible. The optimum process parameters obtained fordevelopment of extrudates were 20% feed moisture, 340 rpmscrew speed, 120°C die temperature and formulation of60:30:10; rice flour: pulse flour: carrot pomace flour; forachieving the maximum possible protein content, fiber content,overall acceptability with minimum hardness and colourdifference.

REFERENCES

Adsule RN. 1996. In E Nwoloko and J Smartt (Eds.), Food and feedfrom legumes and oilseeds. Chapman and Hall Pub. Pp. 84-110.

Agriculture and Agri-Food Canada. 2006. Lentils: Situation and outlook.Bi-weekly Bulletin, 19(7). Retrieved 21.08.08.

Alam MS, Kumar Mahesh, Kumar Satish and Bhandari Arjun 2011.Optimization of process parameters for osmo-mechanicaldehydration of shelled peas (Pisum sativum). Journal of FoodLegumes 24(3): 218-24.

Altan A, McCarthy KL and Maskan M. 2008a. Twin-screw extrusionof barley-grape pomace blends: Extrudate characteristics anddetermination of optimum processing conditions. Journal of FoodEngineering 89: 24-12.

Altan A, McCarthy KL and Maskan M. 2008b. Evaluation of snackfood from barley-tomato blends by extrusion processing. Journal

Fig 6. Overlaid contours of different responses foroptimization of extrusion process parameters

product: Graphical multi-response optimization technique wasadopted to determine the workable optimum conditions forthe development of extruded product using design expertsoftware (Stat ease, DE 8.0.6.1). The contour plots for all theresponses were superimposed and regions that best satisfiedall the constraints were selected as optimum conditions. Themain criteria for constraints optimization were maximumpossible protein, fiber and overall acceptability and lower


of Food Engineering 84: 231-242.

Amerine MA, Panngborn RM and Roessler EB. 1965. Principles ofSensory Evaluation of Food. Pp 5. Academic Press, London.

AOAC (2005) Official Methods of Analysis of AOAC International.Pp 20-35. 18th ed. USA

Bohm V, Otto K and Weissleder F. 1999. Yield of juice and carotenoidsof the carrot juice production”, In: Symposium Jena-Thuringen,Germany. Pp 115-119.

Cochran WG and Cox GM. 1964. Experimental designs. New York:John Wiley & Sons, Inc. Asd

Ding QB, Ainsworth P, Tucker G and Marson H. 2005. The effect ofextrusion conditions on the physicochemical properties and sensorycharacteristics of rice based expanded snacks. Journal of FoodEngineering 66: 283-289.

Gnanasekharam V, Shewfelt RL and Chinnan MS. 1992. Detection ofcolour differences in green vegetables. Journal Food Science 57:149-54.

Grigelmo-Miguel N and Martín-Belloso O. 1999. Comparison of dietaryfibre from by-products of processing fruits and greens and fromcereals. LWT – Food Science Technology Pp. 503-508.

Kadan RS, Bryant RJ and Pepperman AB. 2003. Functional propertiesof extruded rice flours. Journal of Food Science 68: 1669-1672.

Kumar Mahesh, Alam MS, Kumar Satish and Singh Jarnail. 2009.Textural degradative kinetics of selected legumes of Punjab. Journalof Food Legumes 22(4): 291-295.

Montgomery DC. 2001. Design and Analysis of Experiments. NewYork Wiley. Pp. 416-419.

Moscicki L, Mitrus M, Wojtowicz A, Technika ER. 2007. PWRiL,Warszawa

Nawirska A and Kwasniewska M. 2005. Dietary fibre fractions fromfruit and vegetable processing waste. Food Chemistry 91(2): 221-225.

Ng A, Lecain S, Parker ML, Smith AC and Waldron KW. 1999.Modification of cell wall polymers of onion waste. III. Effect ofextrusion-cooking on cell wall material of outer fleshy tissue.Carbohydrate Polymers. 39: 341-349.

Ranganna S (1997) Handbook of Analysis and Quality Control for fruitand vegetable Products. 2nd edn. Pp 1112. Tata Mc.Graw HillPub.Co.Ltd., New Delhi, India.

Serena A and Bach Knudsen KE. 2007. Chemical and physicochemicalcharacterization of co-products from the vegetable food and agroindustries. Animal Feed Science and Technology. 139: 109–124.

Stojceska V, Ainsworth P, Plunkett A, Ibanoglu E and Ibanoglu S. 2008.Cauliflower by-products as a new source of dietary fibre, antioxidantsand proteins in cereal based ready-to-eat expanded snacks. Journalof Food Engineering 87: 554-563.

Yagci S and Gogus F. 2008. Response surface methodology for evaluationof physical and functional properties of extruded snack foodsdeveloped from food-by-products. Journal of Food Engineering86: 122-132.


Area expansion under improved varieties of lentil through participatory seedproduction programme in Ballia District of Uttar PradeshS. K. SINGH, RIYAJUDDEEN, VINAY SHANKAR OJHA and SANJAY YADAV

Indian Institute of Pulses Research, Kanpur – 208024,Uttar Pradesh, India; E-mail : [email protected](Received : April 02, 2013 ; Accepted : August 12, 2013)

ABSTRACT

Attempts have been made through a pilot project to introducelentil crop in rice-fallow of Ballia district of eastern U.P. tobreak the mono-cropping and to introduce improved varieties .A block Sohown was selected and data were collected from therespondent through PRA survey and structured interviewschedule. The socio-economic status is related to adoption ofrecommended package of practices for cultivation of lentil,opinion of the farmers and impact of the project. Maximum55.83 % farmers adopt 2% solution of urea improves the plantgrowth as well as yield. Almost all the farmers usedrecommended seed rate 16 kg/acre (40 kg/ha) of lentil after twoyears of participatory lentil production programme. NDL-1variety of lentil performs better and PL-6 variety has beenchosen as short duration (105-115 days) under monocroppedrainfed farming situation. Participatory Varietal SelectionTrials are beneficial for selection of best performing variety ina particular farming situation. Efforts made to Register farmersassociation under “Uttar Pradesh society Registration Norms-1860” in the project implementing area for the production ofquality seed on large scale through close linkage with NationalSeed Corporation, Seed Certification Agencies, Private dealersand local traders. Thus farmers should be trained properlyabout improved production technology of lentil and thesetrained farmers would be able to educate and transfer thetechnology more electively among the lentil growers.Productivity enhancement, nutritional security and rurallivelihood could be achieved through participatory farmers seedproduction programme.

Key words: Farmers Association, FPVST(s), Impact, Lentil,, PRA

Lentil (Lens culinaris) is one of the major rabi pulsecrops grown in India since time immemorial and contributessignificantly to food, feed and sustainable farming systems.In India, lentil is grown in an area of 1.48 million hectare witha total production 1.03 million tons with an average yield 697.00kg / ha. Recent estimates suggested that approximately 11.65million hectare area is under rice-fallow in the country. 0.35million hectare area in UP as a rice-fallow providing amplescope for expansion of lentil crop in the state.

Farmers must use pure and healthy seeds which haveslandered germination percentage. The high quality seed arethose which have genetic purity, physical purity, healthstandards, germiniability and moisture percentage inaccordance with the minimum seed certification standards.Hence the farmers can increase approximately 20% production

by use of quality seed of lentil. Unfortunately, this could nothappen because of farmers lack of awareness about improvedvarieties and matching production technologies, inadequatesupply of seed of appropriate varieties. The farmer does makearrangements of many inputs but the seed is the chief inputamong other inputs. To promote the improved varieties andproduction technologies of lentil in r ice-fallow theparticipatory seed production has been initiated, developedas a community based seed production approach for asustainable seed supply for farmers, it is an approach ofproducing and distributing seed with the participatoryinvolvement of farmers group. In this approach, seed producerfarmers associations are formed to multiply the seed of farmer-preferred varieties using a cost effective approach havingseveral unique features. Thus helping to expand area underlentil and also improve the productivity by way of augmentingthe supply of quality seeds and popularizing the refinedpackage of practices it takes account of the entire seedinnovation system from initial identification of new varietiesthrough participatory varietal selection through to commercialseed production. The good quality of seed true to its type,free from ad mixture of other variety seed, having highpercentage of germination and free from seed born diseases.Hence keeping these variables in mind, farmers should betrained properly about improved production technology oflentil and these trained farmers would be able to educate andtransfer the technology more effectively among the farmersof neighboring villages.

RESEARCH METHODOLOGY

DAC-ICARDA-ICAR collaborative project “Enhancinglentil Production for Food, Nutritional Security and Improvedrural Livelihood” is being implemented since October 2010.Sohown block is the project site of the Ballia district the total09 village where lentil is grown in large scale were selected forgathering information.

Base line Survey: A baseline survey was conducted in2010 in partner villages of Sohown block of Ballia districttoassess the situation from production to marketing.The majorsteps used in conducting base line survey are as follows-l Semi structured interviewwere conducted in the villages

with active involvement of farmers.

l PRA survey was conducted in the village with the groupof farmers (Participatory mapping, Transect Walk,


scoring, Matrix Ranking, change and trends).

l Collection of data from farmers mainly related to socio-economic, adoption of improved package of practices,farmers opinion and constraints in seed production.

l Collection of Secondary data of the selected villagesfrom the office of District Agriculture/lekhpal.

The data collected were processed, summarized andtabulated for statistical analysislike percentage, average andscaling for meaningful interpretation of results.

Farmers Participatory Varietal Selection Trial(FPVST):Farmers Participatory Varietal Selection Trials hashelped in building of confidence among farmers for promotingas well as ensuring seed sufficiency at village level. Farmersparticipatory Varietal Selection Trial (s)on farmers field withfour improved varieties NDL-1, HUL-57 PL-6 and WBL-77alongwith local variety was conducted to identify farmer-preferred varieties. Each FPVST was conducted in an acre.The varieties were evaluated for seed yield and other economicparameters besides taking into consideration the farmersperception on their performance.

Seed Production: To as certain farmers preferred as wellas shifting of area under improved varieties of lentil was sownin normal condition in first week of November whereas latevariety were sown after second fortnight of November to firstweek of December with recommended Seed rate (16-20 kg/acre). Before the start of cropping season, farmers meetingwere organized to decide our seed production programme.

Following activities were also undertaken to developfarmers capacity in quality seed production, processing andmarketing by facilitating them to form their association.(1) Farmers Training in Crop Management and Seed

Production: To ensure seed sufficiency at village levelefficient and effective quality seed production of lentilfarmers were trained in various technological aspectson crop production and seed production includedvarietal description, seed treatment, nutr ientmanagement, Insect-pest and disease, Isolationdistance, roguing in seed production fields and cropharvesting technology etc.

(2) Close Linkage with Formal Seed Sector: The selectedimproved varieties growers were linked with UttarPradesh State Seed Certification Agency, Mau for seedcertification to strengthen formal Seed sector for lentilSeed Production. KVK were also linked with farmers toprovide them day to day latest technical informationand ensure quality of seed produced.

(3) Formation of Registered Farmers Association: ForPromotion of Formal and Informal seed system tworegistered farmers association has been formed to ensurethe seed sufficiency of farmers preferred variety of lentil

for multiplication of seed at village level.”Madaura KisanSewa Samiti” (25 active member) and “Jai Vigyan KisanSewa Samiti” (18 active member)formed underthe “UttarPradesh Society Registration Norms -1860” in 2012.


Socio-economic characteristics of the Lentil SeedProducers:The table-1 showed the socio-economic status ofthe farmers that 10.00% farmers are illiterate and 41.66% arehaving graduation and above level of education. Maximum51.67% farmers are having 5-8 members in his family and 40.00%farmers were having joint family. Majority of 41.67% farmershaving 5-6 ha of land holding whereas 15.83% farmers comesunder the category of less than 2 ha area. Due to large landholdings 94.17% farmers used tractor drawn seed drill in linesowing. Majority of farmers 55.83% depends on tube wellsfor irrigation.

Table-1 Socio-economic Status of the Farmers of District BalliaSl. No. Particulars No. of farmers Percentage

1. Educational Status- Illiterate Primary Middle High School Intermediate Graduation Post-Graduation

12 07 10 22 19 43 07

10.00 05.83 08.33 18.33 15.83 35.83 05.83

2. Size of Family- Below 5 member 5-8 member 8-10 member Above 10 member

10 62 29 19

08.33 51.67 24.17 15.83

3. Size of land holding- <2 ha 2-4 ha 5-6 ha Above 6 ha

19 29 50 22

15.83 24.17 41.67 18.33

4. Sowing Method- Broad casting Line sowing by Seed drill Conventional Plough Zero tillage

07 113 00 00

05.83 94.17 00.00 00.00

5. Source of irrigation- Canal Tube well (Diesel

Pumping set) Electric Motor tube well Govt. Tube well No irrigation Facility

00 48 19 00 53

00.00 40.00 15.83 00.00 44.17

Farmers Participatory Varietal Selection Trial (s):

Table 2 showed the performance of improved varieties of lentilunder farmers field condition. Farmers Participatory VarietalSelection Trial(s) were organized at farmers field during 2010-11. Three improved varieties NDL-1, HUL-57, IPL-81 alongwithlocal variety were sown at five farmers fields. Narendra Lentil-1 has been assessed as higher yielder 13.00 q/ha undermonocropped rainfed situation followed by HUL-57, IPL-81

Singh et. al., : Area expansion under improved varieties of lentil through participatory seed production programme in Ballia 117

and local variety yielded 10.50, 11.00 and 8.00 qt/harespectively. NDL-1 varieties of lentil perform better undermonocropped rainfed situation.Majority of farmers completedsowing of lentil in First fortnight of November to Secondfortnight of November 2011 after harvesting of long durationpaddy. During rabi 2011-12 three improved varieties namelyPL-6, HUL-57, WBL-77 alongwith last year farmers preferredvariety NDL-1 were used in FPVSTs among the new selectedfarmers field. PL-6 variety has been chosen as short duration(105-115 days) and higher yielder (16-18 q/ha) under rainfedmonocropped situation in Ballia district. Farmers alsoperceived that seed size of PL-6 to be attractive and bold incomparison to other varieties of lentil.

Farmers Opinion UnderTechnological Aspects: Thetable 3(A) showed the technological opinion of the farmerson six statements. Maximum 94.17% farmers are agreed withthe statement “application of Trichoderma minimizedincidence of wilt” and 80.00% farmers are strongly agreedwith “use of recommended seed rate 16.00 kg/acre instead of25.00 kg/acre for small seed of lentil”. Besides of these 34.17%farmers gave negative opinion about the statement “oneirrigation is beneficial at pod formation stage”. Pal et al. (2004)also reported the same finding.

Table-2: Performance of Farmers Participatory Varietal Selection Trials(FPVSTs)Ballia

Productivity (qt/ha) Micro farming Situation No. of fields Plot Size Varieties Maximum Minimum Average

2010-11 NDL-1 13.00 08.00 10.50 HUL-57 10.50 06.00 08.20 IPL-81 11.00 06.00 08.50

Clay loam and loam mono cropped rainfed situation Five (5) 0.5 ha

Local 08.00 03.00 5.50 2011-12

PL-6 18.29 14.00 16.14 NDL-1 16.40 13.70 15.05 HUL-57 14.50 12.60 13.55 WBL-77 16.20 13.30 14.70

Clay loam double cropped rainfed and Partial irrigated

Five (5) 0.5 ha

Local 11.80 9.50 10.65

Sl. No. Particulars Strongly Agree

(1)

Agree (2)

Un-decided (3)

Dis-agree (4)

Strongly Dis-agree

(5) 1. (A) Technological aspects:

Use of recommended Seed rate 16 kg/acre instead of 25 kg/acre for small seed of lentil.

96 (80.00)

24 (20.00)

00 (00.00)

00 (00.00)

00 (00.00)

2. Basal dose of application of DAP is beneficial. 12 (10.00)

55 (45.83)

53 (44.17)

00 (00.00)

00 (00.00)

3. Application of Trichoderma minimized incidence of wilt. 00 (00.00)

113 (94.17)

07 (05.83)

00 (00.00)

00 (00.00)

4. Spraying of 2% Solution of urea improves the plant growth as well yield advantages.

00 (00.00)

67 (55.83)

53 (44.17)

00 (00.00)

00 (00.00)

5. Spraying of Insecticide minimizes the damage by insect/pest.

19 (15.83)

84 (70.00)

17 (14.17)

00 (00.00)

00 (00.00)

6. One irrigation is beneficial at pod formation stage. 00 (00.00)

48 (40.00)

31 (25.83)

14 (11.67)

27 (22.50)

Table-3(A) Farmers Opinion on Enhancing Lentil Production Programme.

Economic Aspects: It is clear from the Table 3(B) 84.17%farmers gave positive opinion whereas 15.83% are not decidedthat “Participatory varietal selection trial is beneficial forselection of best performing variety in particular farmingsituation”. Maximum 100.00% farmers are agreed “paddy –lentil is less expensive cropping pattern in comparison toothers” while 84.17% farmers strongly agreed that his “annualincome increased after adoption of paddy-lentil croppingpattern”. Farmers gave positive opinion (70.00% agree and30.00% strongly agree) on “improved varieties gave higheryield in comparison to local varieties”.

Marketing Aspects: Farmers opinions are taken on 7statements related to marketing aspects. Majority of 58.33%farmers are agreed with “formation of farmers associationcreates confidence amongst the farmers in seed production”whereas 41.67% farmers cannot decide and gave neutralresponse on the above statement. Maximum farmers 100.00%are disagree with the statement “only resource rich farmerscan participate in participatory seed production programme”.Same number of farmers are neutral on the statement “farmersreceived more remuneration from NSC in compression to locallevel seed sale”, “NSC paid sufficient remunerative for intakeof seed by the farmers”, “Delayed payment by NSC


(B) Economic Aspects:


(1)

Agree (2)

Un-decided (3)

Dis-agree (4)

Strongly Dis-agree

(5) 1.

Sowing of lentil after harvesting of paddy is profitable. 89 (74.17)

31 (25.83)

00 (00.00)

00 (00.00)

00 (00.00)

2. Improved varieties are less affected by diseases. 89 (74.17)

31 (25.83)

00 (00.00)

00 (00.00)

00 (00.00)

3. Participatory varietal selection trial is beneficial for selection of best performing variety in particular farming situation.

17 (14.17)

84 (70.00)

19 (15.83)

00 (00.00)

00 (00.00)

4. Improved varieties of lentil preferred by the farmers are suitable in your farming situation.

84 (70.00)

36 (30.00)

00 (00.00)

00 (00.00)

00 (00.00)

5. PL-6 variety was short duration and higher yielder in existing farming situation.

101 (84.17)

00 (00.00)

19 (15.83)

00 (00.00)

00 (00.00)

6. Area under improved varieties will increase in coming season.

19 (15.83)

101 (84.17)

00 (00.00)

00 (00.00)

00 (00.00)

7. Improved varieties gave higher yield in comparison to local varieties.

36 (30.00)

84 (70.00)

00 (00.00)

00 (00.00)

00 (00.00)

8. Paddy-lentil is less expensive cropping pattern in comparison to others.

00 (00.00)

120 (100.00)

00 (00.00)

00 (00.00)

00 (00.00)

9. Income increased after adoption of paddy-lentil cropping pattern.

101 (84.17)

19 (15.83)

00 (00.00)

00 (00.00)

00 (00.00)

10. Availability of quality seed can be ensured through participatory seed production.

00 (00.00)

120 (100.00)

00 (00.00)

00 (00.00)

00 (00.00)

(C) Marketing Aspects:


(1)

Agree (2)

Un-decided (3)

Dis-agree (4)

Strongly Dis-agree

(5) 1.

Formation of farmers association creates confidence amongst the farmers in seed production.

00 (00.00)

70 (58.33)

50 (41.67)

00 (00.00)

00 (00.00

2. Only resource rich farmers can participate in participatory seed production programme.

00 (00.00)

00 (00.00)

00 (00.00)

120 (100)

00 (00.00)

3. Farmers received more remuneration from NSC in comparison to local level seed sale.

00 (00.00)

00 (00.00)

120 (100)

00 (00.00)

00 (00.00)

4. NSC paid sufficient remunerative for intake of seed by the farmers.

00 (00.00)

00 (00.00)

120 (100)

00 (00.00)

00 (00.00)

5. Delayed payment by NSC discouraged the farmers. 00 (00.00)

00 (00.00)

120 (100)

00 (00.00)

00 (00.00)

6. Access of seed of preferred varieties at village level through promotion of informal seed system

00 (00.00)

00 (00.00)

120 (100)

00 (00.00)

00 (00.00)

7. Close linkage with ICAR institutes/SAUs/KVKs/Deptt. of Agriculture, seed production Agencies, seed certification Agencies, NGOs, local traders etc.

31 (25.83)

89 (74.17)

00 (00.00)

00 (00.00)

00 (00.00)

Table-4 (A) Performance of Improved Varieties of Lentil UnderFull Technological Management

Sl. No. Name of village

No. of farmer

Area (ha) Average Yield (kg/ha)

1. Karo 12 22.80 1516 2. Basudeva 18 16.40 1420 3. Marchikhurd 06 12.70 1460 4. Bagahi 07 10.00 1565 5. Narahi 04 11.50 1535 6. Katharia 03 06.30 1610 7. Daulatpur 02 05.20 1490 8. Laddupur 04 10.50 1530 9. Firozpur 01 02.50 1580 Total 57 97.90 1523.22

Table-4 (B) Performance of Improved Varieties of Lentil UnderPartial Technological Management

Sl. No. Name of village

No. of farmer

Area (ha) Average Yield (kg/ha)

1. Karo 09 18.40 1360.00 2. Basudeva 11 21.50 1320.00 3. Marchikhurd 10 24.80 1375.00 4. Bagahi 07 17.40 1412.00 5. Narahi 06 14.60 1478.00 6. Katharia 04 13.20 1320.00 7. Daulatpur 08 21.00 1380.00 8. Laddupur 05 12.00 1375.00 9. Firozpur 03 08.30 1340.00 Total 63 151.20 1373.33

Singh et. al., : Area expansion under improved varieties of lentil through participatory seed production programme in Ballia 119

discouraged the farmers”, and “Assess of seed of preferredvarieties at village level through promotion of informal seedsystem”. 74% farmers agree with the statement that they areclosely attached with ICAR institute/SAUs/KVKs/Departmentof seed production, seed certification agencies, NGOs andlocal traders.

Performance of lentil under different managementPractices:Table 4 (A) showed that farmers adopt completetechnological management practices (optimum seed rate, seedtreatment with Rhizobium culture and Trichoderma, sowingafter harvesting of paddy, sowing with seed drill and spray2% solution of urea) obtained maximum 1610.00 kg/ha andlowest yield advantage is 1420.00 kg/ha. It is also clear fromtable 4 (B) total 63 farmers including project partners and otherneighboring adopted partial technological package. Theaverage productivity is 1370.00 kg/ha covering 151.20 ha area.This finding is in line with the finding of Mishra et al. (2009).

Farmers showed positive opinion and attitude towardsapplication of full and partial technological package. It hasbeen cleared that small and medium category of farmers mainlyadopted full technological package whereas marginal and bigcategories of farmers only adopted partial technologicalmanagement practices in lentil.

51.10% (Kaithauli), 48.19% (Sahabuddinpur), and 44.25%(Firozpur) and 42.33% (Katharia), respectively.Yadav andDadlani (2009) also reported the same finding.

Maximum farmers are illiterate and having 5-8 membersin his family. Majority of farmers were having 5-6 ha of landholding and used tractor drawn seed drill for line sowing.Maximum farmers applied Trichoderma for minimized wiltincidence. Under economic aspects maximum farmers stronglysatisfied with the statement “Annual income increased afteradoption of Paddy-lentil cropping pattern. Small and mediumcategories of farmers mainly adopted full technologicalpackage where as marginal and big categories only adoptedpartial technological management. Farmers adopt completepackage of practices obtained maximum 1610.00 kg/ha yield.In compression to 2010-11, 57.14% area increased in 2011-12after adoption of improved package of practices. To ensurethe seed sufficiencya registered farmers association wasestablished and Farmers Participatory varietal selection Trial(FPVST) has been conducted in large scale in projectimplementing site of Ballia district. Farmers actively engagedin participatory seed production programme under thesupervision of ICAR Scientists and KVK Experts and thetrained farmers would be able to educate and transfer thetechnology more effectively among the non- participant’sfarmers.

REFERENCES

Ponnusamy, K; Venlalagurunathan, P. and Jarial, S. (2004).”Developmentof appropriate farm message through PRA techniques”. Nationalworkshop on communication support for sustaining Extensionservices held at Banaras Hindu University, Varanasi Feb. 17-18,2004page 275-276.

Pal, Chandra; Singh J. P; Singh N. K; Singh, L. B; Verma Nootan andTripathi N. C. (2009). “Farmers Participatory Research foridentification of technological gap in Sugarcane production, inwestern U.P.” 5 th National Extension Education Congress, March05-07, 2009 held at C.S.A.U.A. & T. Kanpur Page 46.

Yadav, Shiv K. and DadlaniMalvika (2009). “Farmers ParticipatorySeed Production: an Auto-Driven Extension Approach.” 5th NationalExtension Education Congress, March 05-07, 2009 held atC.S.A.U.A. & T. Kanpur Page 178.

Mishra, P. K; Khare, Y. R; Singh Vinita and Singh Mamta (2009). “5 th

National Extension Education Congress, March 05-07, 2009 heldat C.S.A.U.A. & T. Kanpur Page198.

Table-5 Village-wise area increased under improved varieties

2010-11 2011-12 Sl. No.

Village Total Area (ha)

Area under local

variety

Area under improved

variety

Area under local

variety

Area under improved

variety

1. Kathariya 75.30 59.17 16.13 27.30 48.00 2. Daulatpur 78.85 67.50 11.35 22.45 56.40 3. Laddupur 35.30 27.20 08.30 14.30 21.20 4. Firozpur 45.20 32.20 13.00 12.20 33.00 5. Kaitholi 52.45 43.25 09.20 16.45 36.00 6. Ethai 30.50 22.25 08.25 14.30 16.20 7. Sahabuddin

pur 33.20 27.20 05.00 12.20 21.00

8. Sobantha 42.70 32.55 10.15 15.50 27.12 Total 393.50 311.32 81.38 134.70 258.92

Area expansion under improved varieties:Table 5

showed the impact of project in terms of increase in area.Withinclusion of improved varieties farmers shifted area from localto improved varieties. Maximum 57.14% area increased underimproved varieties of lentil in village Daulatpur followed by


Performance of chickpea in varied conditions of Uttar PradeshLAKHAN SINGH and A.K. SINGH

Zonal Project Directorate, Zone-IV (ICAR), Kanpur-208002, Uttar Pradesh, India; E-mail : [email protected](Received : June 04, 2013 ; Accepted : September 02, 2013)

ABSTRACT

The technology assessment and demonstration programme onchickpea was carried by KVKs for demonstrating productionpotential of newly developed technologies of chickpea atfarmers’ fields in the country. 836 demonstrations on chickpeawere organized in rainfed conditions of 18 districts of UttarPradesh. Technology modules were prepared including all therecommended package of practices. Technology performancein respect to productivity and per unit area profitability fromchickpea was taken up as important intervention. On an average17.77 q/ha yield was realized by the farmers underdemonstration which was significantly higher as compared tolocal check, state and national average yield. More than 16 q/ha yield was provided by DCP 92-3, Pusa 362, Pusa 256, RSG-888, GNG-663 and Awarodhi varieties of chickpea. More thanRs. 37000 per ha of net return was obtained with the cultivationof DCP 92-3, GNG- 663, Pusa 362 and Awarodhi cultivars. Onan average, 60% increased income was accrued to the farmersas compared to local check. The technology disseminationmodel developed and utilized for scientific demonstrations ofchickpea, played a great role for enhancing productivity andnet return to the farmers along with creating a platform forinterface with different stakeholders. This paper discussesperformance of chickpea in different agro-eco and croppingsystems.

Key words: Chickpea, Demonstrations, Productivity, Profitability

Pulses are very important in Indian agriculture both interms of enriching soil health and for food and nutritionalsecurity of country’s ever growing population. Pulses beingpredominantly rainfed crop grown in constrained and limitingfactor environment, the increase in productivity had remaineda major challenge for several decades. There has not beenremarkable increase in area and productivity of pulses aswitnessed in other commodities over the years. There hasbeen number of technological breakthroughs with promise toraise the productivity levels which need to be demonstratedat farmers’ fields with their active participation so as to buildtheir confidence in new technologies. India produced 17.21million tonnes of pulses from an area of 24.78 million hectares(Nadarajan, 2013). The important pulse crops are chickpea(48%), pigeonpea (15%), mungbean (7%), urdbean (7%), lentil(5%) and fieldpea (5%). The major producing states areMadhya Pradesh, Maharashtra, Rajasthan, Uttar Pradesh andAndhra Pradesh, which together account for about 80% ofthe total production. However, about 3 million tonnes of

pulses are imported annually to meet the domesticconsumption requirement (Chaturvedi, et al 2010). Indiaproduced 7.5 million tonnes of chickpea covering 8.32 millionha area with productivity of 9.12 q/ha in 2011-12. Uttar Pradeshproduced 0.72 million tonnes of chickpea with productivity of12.48 q/ha in 2011-12 (Directorate of Economics and StatisticsDepartment of Agriculture and Cooperation-2012). The areaunder chickpea has reduced in entire Indo-Gangetic plains. Incase of Uttar Pradesh, it has come down to 0.58 million ha in2011-12. Therefore, raising productivity may be the importantoption to deal with it.

The technology assessment and demonstrationprogramme on chickpea was carried by KVKs fordemonstrating production potential of newly developedtechnologies and varieties of pulses at farmers’ fields as tobring in enhanced application of modern technologies toaddress the issues related to production of pulses in thecountry. Technology performance in respect to productivityand per unit area profitability from chickpea was taken up asimportant intervention. This paper discusses performance ofchickpea in different agro-eco and cropping systems.


The programme on chickpea (Cicer arietinum L.) wasorganized in 18 districts of Bundelkhand zone, Vindhyan zone,Central Plain zone and Eastern Plain zone of Uttar Pradesh.Technology modules were prepared including all therecommended package of practices. Analysis of agro-ecosystems was made.

The cropping systems followed are urdbean-chickpea,fallow-chickpea, rice-chickpea and maize-chickpea. Theprevalent varieties grown are Udai, Radhey, Awarodhi and K-850 in the study area. The technology module introducedincluded:

Seed rate: 32 kg (normal sown), 35.0 kg (late sown) seed/acre. Seed treatment with Trichoderma (6g/kg) and Vitavax(Carboxin) (1g/kg). Application of Rhizobium culture onepacket (200 g)/10 kg seed. Sowing time: Rainfed: 1st fortnightof Oct., Irrigated: Last week of Oct. to 1st week of November.Spacing: 30cmx10cm (line sowing). Cultivars: DCP 92-3, KWR108, KPG 59, HK 2 (K), Pusa 372, IPCK 2002-29 (K), GujaratGram-4. Irrigation: Two irrigations first at branching and 2nd atpod initiation stage. Fertilizer dose and plant protectionmeasures were followed as per locations of the district.

Singh & Singh : Performance of chickpea in varied conditions of Uttar Pradesh 121

The sample included 18 districts and 826 farmers of 4agroclimatic zones of Uttar Pradesh. Critical inputs wereprovided to the participating farmers. Training of participatingfarmers and extension workers were orgainized through KVKs.Statistical techniques like percentage, weighted mean, yieldgap analysis, technology index were used. The technologygap, extension gap and technology index were estimated usingthe following formula:

Technology gap = (Potential yield) - (Demo. yield)Extension gap = (Demo. yield) - (Farmer’s yield)Technology index = Pi - Di ×100

PiwherePi=Potential yield of ith crop.Di=Demonstration yield of ith crop.A technology dissemination model was evolved and

utilized for effective delivery of district specific technologymodules (Fig. 1). This model produces representation ofnetworks and deliverables.


In the year 2011-12, the productivity of chickpea hasbeen highest in Uttar Pradesh as compared to other states,where as it was lagging earlier to states like Andhra Pradesh,Gujarat, Haryana, Bihar and West Bengal, etc. The crop ismainly grown in the rainfed situations under different croprotations viz urdbean-chickpea and fallow-chickpea.

A total of 836 demonstrations were conducted withaverage productivity of 17.77 q/ha which was about 37.86%higher to local check, 137.57 % to state and 122.40 % to nationalaverage. The average net return of Rs. 34400 per ha was realizedagainst Rs. 22115 per ha from local check. In some of thedistricts, average returns were more than Rs. 35000 per ha.50% net economic gain was higher under demonstrations ascompared to local check (Table 1). The encouraging results ofcrop productivity and net returns are attributed to skill trainingprovided to the farmers, extension workers and application ofimproved varieties and package of technologies. Agro-climaticarea-wise yield performance of chickpea cultivars are givenbelow.

Rainfed condition: Under rainfed situation(Bundelkhand and Vindhyan Zone), 362 demonstrations wereorganized (196.28 acre) in 8 districts. The demonstrations werelaid out in fallow-chickpea cropping system. On an average,17.25 q/ha yield was realized by the farmers which was 36.47% higher over local check, 130.61 % over state and 115.89 %over national average with net return of Rs. 37145 per ha.More than 16 q/ha yield was obtained using cultivars likeDCP 92-3, Pusa 362, GNG-663, BG-256 and Awarodhi (Table 1and Fig. 2).

Central Plain Zone: In this zone, 5 districts (KanpurDehat, Hardoi, Raebareli and Sitapur) were included fortechnology demonstration under rice-chickpea, maize-chickpeacropping systems with the participation of 179 farmers on94.5 acre area. On an average, 21.0 q/ha yield was achievedunder demonstration which was 33.84 % higher over farmerspractice, 183.42 % over state and 165.33 % over nationalaverage. The net profit of Rs. 35975 per ha was realized by thefarmers which was 58 % higher as compared to local check.More than 21 q/ha yield was attained by Awarodhi and RSG-

Fig.1: Technology Adaptation Model for HarnessingProductivity

Fig. 2: Yield performance of chickpea in rainfed condition :2010-11 * 2011-12


888 cultivars with maximum net profit of Rs. 37172 per ha (Table2 and Fig. 3).

attained by the farmers which was 52.94 % higher over localcheck, 202.81 % over state and 183.48 % higher over nationalaverage (Table 3). The net return of Rs. 38401 per ha wasrealized by the participating farmers which was 71.55 % moreas compared to local check (Fig. 4).

Under late sown condition, PKG-59 and Pusa-372varieties were experimented at farmers fields (87 farmers)covering 92.5 acre area. The average yield of 14.63 q/ha wasachieved which was 45.72 % superior over local check (10.04q/ha), 95.59 % over state and 83.1 % over national average(Fig. 5 and Table 4). Net return of Rs. 31654 per ha was realizedby the farmers.

Table 1: Performance of Chickpea demonstrations in rainfed situation

Yield (q/ha) Net Return (Rs./ha) Varieties Districts No. of Farmers Area

(acre) Demo Check

% Increase

Demo. Local Check % Income

KGD-1168 Chitrakoot 39 11.00 12.78 10.00 27.80 26795 21790 22.97KWR-108 Chitrakoot, Jalaun 24 12.50 14.88 10.60 40.38 33830 22800 48.38Awarodhi Chitrakoot, Hamirpur,

Jhansi, Sonbhadra, Banda 145 108.00 17.39 12.69 37.04 35650 23560 51.32

DCP-92-3 Chitrakoot, Lalitpur 50 16.40 16.78 11.92 40.77 37844 25960 45.78Radhey Jalaun 1 1.13 15.25 12 27.08 33825 24900 35.84GNG-663 Jhansi 5 6.25 20.2 16.2 24.69 48200 28745 67.68BG-256 Lalitpur 22 20 17 11.4 49.12 38095 19730 93.08Pusa-362 Sonbhadra, Mirzapur 76 21.00 20.09 15.72 27.80 47666 35234 35.28

Total/Wt. Mean 362 196.28 17.25 12.64 36.47 37145 24644 50.73

Fig. 3: Yield performance of chickpea inUttar Pradesh : 2010-11 & 2011-12

Yield (q/ha) Net Return (Rs./ha) Varieties District No. of Farmers

Area (acre) Demo Check

% Increase Demo. Local Check % Income

Awarodhi Kanpur Dehat, Hardoi 143 67.50 21.85 15.98 36.73 37172 22478 64.00 Pusa-256 Unnao, Raebareli 24 15.00 18.11 15.32 18.21 31842 24839 26.00 RSG-888 Sitapur 12 12 21.4 15.7 36.31 34408 22648 51.93

Total/Wt. Mean 179 94.50 21.20 15.84 33.84 35975 22874 58.00

Table 2: Performance of Chickpea demonstrations in Central Plain Zone

Fig. 4: Yield performance of chickpea in eastern plain zone :2010-11 & 2011-12

Eastern Plain Zone: In this agroclimatic zone, 4 districts(Ghazipur, St. Ravidas Nagar, Sultanpur and Mau) wereincluded under demonstrations with the involvement of 198farmers on 14 acre area. The average yield of 22.65 q/ha was

Fig. 5: Yield performance of chickpea under late sowncondition: 2010-11 & 2011-12

Singh, et al (2005) reported that on an average 22 q/hayield was obtained by the farmers in eastern districts. Chickpeayield ranging between 8.7 to 23.4 q/ha was observed in thedemonstrations.

Singh & Singh : Performance of chickpea in varied conditions of Uttar Pradesh 123

Table 3: Performance of Chickpea demonstrations in Eastern Plain ZoneYield (q/ha) Net Return (Rs./ha) Varieties District No. of Farmers Area

(acre) Demo Check % Increase

Demo. Local Check % Income Awarodhi Ghazipur 25 2.5 22 14.5 51.72 38500 22650 69.98 DCP-92-3 SRD Nagar 137.5 5.5 23.4 16.25 44 39052 22960 70.09 GNG-663 Sultanpur 10 1 21.5 15.4 39.61 37350 25300 47.63

Pusa-256 Mau 25 5.00 22.38 13.25 68.91 37840 21040 79.85 Total/Wt. Mean 198 14.00 22.65 14.81 52.94 38401 22385 71.55

Table 4: Performance of Chickpea demonstrations under late sown condition

Yield (q/ha) Net Return (Rs./ha) Varieties Districts No. of Farmers

Area (acre) Demo Check

% Increase Demo. Local Check % Income

PKG-59 Jalaun, Hamirpur, Kanpur Dehat 82 90.00 14.53 10.00 45.30 31579 16400 92.55 Pusa-372 Auraiya 5 2.5 18.38 11.5 59.83 34357 17992 90.96

Total/Wt. Mean 87 92.50 14.63 10.04 45.72 31654 16443 92.51

The yield gap of 2.71 q/ha was obtained betweendemonstrated and local check condition. The technology gapof 2.04 q/ha was also observed between potential anddemonstrated yield of chickpea. Technology Index (8.91%)was computed for different chickpea cultivars which show asignificant difference of technology and extension gap (Fig.6). There is a great scope for enhancing productivity ofchickpea with reduction in yield gap and technology gap. Itmay be possible by adoption of district specific technologymodules, advance planning, critical monitoring, observationrecording, critical input support, organization of field days,etc. related to demonstrations. Feedback to the technicalinstitutions may play an important role to make furthercorrections in technology demonstration mechanism. Thetechnology dissemination model followed duringdemonstrations can be adapted for other commodities for thebenefit of farmers.

Organization of technology demonstrations onchickpea included special attention on planning, capacitybuilding, district specific technology modules development,

observations recording, regular monitoring andimplementation. On an average 17.77 q/ha yield was realizedby the farmers under demonstration which was significantlyhigher as compared to local check, state and national averageyield. More than 16 q/ha yield was provided by DCP 92-3,Pusa 362, Pusa 256, RSG-888, GNG-663 and Awarodhi varietiesof chickpea. More than Rs. 37000 per ha of net return wasobtained with the cultivation of DCP 92-3, GNG- 663, Pusa 362and Awarodhi cultivars. On an average, 60% increased incomewas accrued to the farmers as compared to local check. Thetechnology dissemination model developed and utilized forscientific demonstrations of chickpea, played a great role forenhancing productivity and net return to the farmers alongwith creating a platform for interface with differentstakeholders.

REFERENCES

Chaturvedi SK, Nadarajan N, Singh SK and Mishra JP. 2010. Strategyfor enhancing pulses production in Bundelkhand tracts of UttarPradesh and Madhya Pradesh. Published in Extension Strategy forBundelkhand Region, published by Zonal Project Directorate,Kanpur.

N. Nadarajan. 2013. Prospects and strategies for increasing pulsesproduction in the potential states. In Training Manual ‘ModelTraining Course on Management of Pest and Diseases in PulseCrops’ organized at IIPR, Kanpur, pp 1-18.

Singh NP, Singh Atar and Singh Lakhan .2005. Yield gap analysis ofpulse crops under front line demonstrations in Uttar Pradesh. ZonalCoordination Unit, Zone-IV, Kanpur.

Singh AK, Singh Lakhan, Singh Atar and Singh RK. 2008. Inventory ofAgricultural Technologies for Uttar Pradesh. Zonal ProjectDirectorate, Zone-IV, Kanpur.

Fig. 6: Yield gap and technology index of chickpea inUttar Pradesh


Role of pulses in the food and nutritional security in IndiaSHALENDRA, K.C. GUMMAGOLMATH, PURUSHOTTAM SHARMA1 and S.M. PATIL2

CCS National Institute of Agricultural Marketing, Jaipur; Rajasthan, India; 1Directorate of Soybean Research, Indore,Madhya Pradesh, India; 2Univerisity of Agricultural Sciences, Bangalore, Karnataka, India;E-mail: [email protected]

ABSTRACT

In spite of impressive growth of Indian agriculture, ensuringhousehold food and nutritional security is still a challenge dueto imbalanced growth in agriculture biased towards wheat andrice. Though production of pulses in the recent decade hasincreased but is not in pace with the increase in population.Pulses for being a major source of protein in Indian diet andfor being resource conserving and environmental friendly, theincrease in pulse production will act as a panacea for problemslike nutritional security. Hence, an attempt has been made inthis paper to analyze the significance of pulses in foodconsumption and nutritional security vis-à-vis other food items.The analysis is based on the 55th and 66th rounds of NationalSample Survey pertaining to years 1999-2000 and 2009-10,respectively, using simple descriptive statistics. The dietarypattern has shifted away from cereals and pulses toward fruits,vegetables, processed food and food items of animal origin.The decline in the consumption of pulses has lead to increasein malnutrition and decline in protein intake. Need of thehour is to increase production and availability of pulses byadopting various innovative measures like institutional andpolicy support, development and wider adoption of HYV andlow cost technologies, proper extension services for productionand marketing of pulses, development of value chain, etc.

Key words: Consumption Pattern, Expenditure Pattern, Elasticity,Food and Nutritional Security, Production and Pulses

Food and nutritional security is said to be achievedwhen adequate food (quality, quantity, safety, socio-economicacceptability) is available and accessible for and satisfactorilyused and utilized by all individuals at all time to live a healthyand active life (UNICEF, 2008). The impressive growth of Indianagriculture no doubt has helped the country in achieving self-sufficiency with respect to availability of foodgrains at nationallevel. The estimates suggest that India is likely to be the mostpopulous country on the planet by 2020 with a population of1.39 billion. India is house for 445 million poor i.e. 35 percentof Indian are living on less than $1.25 a day. Half of thepregnant women are anemic in India while in the case ofchildren under the age of five years, 74 percent are reported tobe anemic and 43 percent underweight (World Bank, 2012).Hence, ensuring household food and nutritional security isstill a challenge for the country, particularly when a hugeproportion of 1.2 billion population is poor and malnourished.

The growth of agriculture in India may help immenselyin improving food and nutritional security as agriculture plays

a key role in increasing food availability and higher realizationof income, support livelihoods of major proportion ofpopulation and contribute to the overall growth of the economy(World Bank, 2008). However, imbalanced growth ofagriculture may also lead to continued malnutrition. The GreenRevolution of mid 1960s, regarded for revolutionizing Indianagriculture, has been biased towards wheat and rice. Pulsesand coarse grains, which are the source of staple food andprotein requirements for poor, have not been given adequateattention (Adiguru and Ramasamy, 2003; Reddy 2009). Thoughthe proportion of pulses have shown some sign of recoveryduring the last decade owing to various government policies,still much progress could not be made in terms of availabilityof pulses. Inefficient marketing and relatively higher prices ofpulses further aggravates the problem of poor availability ofpulses leading to malnutrition. Malnutrition is not the resultof a single cause but is multi faceted problem acting singly orin combination with other complex factors like poverty,purchasing power, health care, ignorance and policies (Singh,2009; Reddy, 2013).

Pulses for being a major source of protein in Indian dietand for its vital contribution in sustaining agricultural growthdue to its resource conserving nature and being environmentalfriendly, the increase in pulse production will act as a panaceafor problem like availability of food and nutritional security.Hence, an attempt has been made in this paper to analyze thesignificance of pulses in food consumption and nutritionalsecurity vis-à-vis other food items. The paper specificallyattempts to study the change in consumption pattern ofleading food items over time in rural and urban India and theirimpact on the nutrient intake in terms of energy, protein andfat; and to work out gap in consumption of different fooditems in comparison to the levels prescribed. An attempt hasalso been made to examine the composition of consumptionexpenditure and various other related aspects like availability,production growth, price movement and price elasticity ofpulses vis-à-vis other food items so as to suggest appropriatepolicy measures to enhance the production and availabilityof pulses.

METHODOLOGY

The study utilizes secondary information collected fromvarious reports of National Sample Survey Organization ondietary pattern, consumer expenditure and nutrient intake, etc.for fulfilling different objectives of the paper. The analysis is

Shalendra et al., : Role of Pulses in the food and nutritional security in India 125

based on the 55th and 66th rounds of National Sample Surveypertaining to years 1999-2000 and 2009-10, respectively. Thegap in nutrient intake was worked out as per the formula givenbelow:

Food Consumption Gap = AFi - RFi

Where, AFi = Actual consumption level of ith food itemRFi = Recommended level of ith food item


Consumption Pattern of Leading Food Items

The change in consumption of different food itemsduring 1999-2000 and 2009-10 is presented in the Table-1. Thetable reveals that per capita daily consumption of cerealsdeclined substantially from 424 gms in 1999-2000 to 378 gmsin 2009-10 in rural India i.e. a decrease of nearly 11 percent,whereas corresponding change in urban India was from 347gms to 312 gms, a decline of about 10 percent. The other twocommodities whose consumption has come down in both ruraland urban India are pulses and sugar. However, consumptionof pulses is a concern for nutritional security, as per capitadaily consumption of pulses was 28 gms in rural India during1999-2000 against a recommended level of 42 gms which furtherdecreased to 23 gms during 2009-10. In urban areas, the percapita daily pulses consumption decreased from 33 to 27 gmsduring the same period. However, a considerable positivechange is observed in the consumption of fruits andvegetables and edible oil. The consumption of fruits andvegetables registered an increase of about 73 percent and 31percent, respectively in rural India while the increase was tothe tune of 53 percent and 21 percent, respectively in urbanIndia. Considerable change in the consumption of food itemsof animal origin has also been observed. The per capita dailyconsumption of meat, fish and eggs showed an increasingtrend though still lower than recommended level. It increasedfrom 14 gms to 20 gms in rural India and from 19 gms to 24 gmsin Urban India during the reference period. The per capitaconsumption of milk has increased marginally from 127 ml to

138 ml in rural India and from 176 ml to 182 ml in urban India.Change has also been observed in favour of other food itemswhich mainly consist of processed and packaged food items.

In all, the consumption is moving away from foodgrainsand changing towards horticultural products like fruits andvegetables, food items of animal origin like milk, eggs, meat,fish, etc and processed products. This shift in consumptionpattern may be attributed to relative prices of cereals andpulses, diversification towards high value food and changein income and taste and preferences of consumers (Mittal,2007; Reddy, 2004; Reddy, 2009a and Kumar, et al. 2007).Unfavorable change in the consumption of pulses may bedue to factors like relatively higher prices, complex marketingdue to involvement of processing, slow growth in productionand inclination of population towards consumption of animalprotein.

Change in Dietary Pattern and Nutrient Intake

The previous section reveals the transition in dietarypattern from foodgrains to horticultural crops, food items ofanimal origin and processed food. The impact of this transitionin dietary pattern on the nutrition intake has been assessed interms of change in calories, protein and fat intake. The detailsof calorie, protein and fat intake from different food items inrural and urban India during 1999-2000 and 2009-10 arepresented in the Table-2 to Table-4.

Though, the contribution of cereals have come down inrural India by about 11 percent, still as much as 60 percent ofcalories intake has been contributed by cereals during 2009-10. Studies suggest that the decline in traditional stapleconsumption has been significant for coarse cereals likesorghum, pearl millet and Maize (Shalini, 2012; Reddy et al.2013). The downfall in the contribution of cereals in caloriesintake has been effectively compensated by the increased

Table 1. Change in food consumption in rural and urbanareas of India, 1999-2000 and 2009-2010

Rural Urban Food Items Unit

1999-00 2009-10 Change (%) 1999-00 2009-10 Change

(%) Cereals Grams 424 378 -10.77 347 312 -10.04 Pulses Grams 28 23 -18.21 33 27 -18.70 Vegetables Grams 180 235 30.84 198 239 20.64 Fruits Grams 28 48 72.80 53 81 53.25 Milk ml 127 138 8.56 176 182 3.38 Edible oil Grams 17 21 27.20 24 27 12.05 Sugar Grams 28 23 -16.19 33 27 -17.07 Egg Fish Meat Grams 14 20 39.39 19 24 24.65

Others Grams 55 80 45.93 104 120 14.59

Rural Urban Food Items 1999-00 2009-10 Change

(%) 1999-00 2009-10 Change (%)

Cereal 1449(68.00)

1296(60.20) -10.54 1184

(55.35)1069

(49.86) -9.66

Pulses 96(4.50)

77(3.58) -19.85 115

(5.38)92

(4.29) -19.72

F&V 114(5.35)

145(6.73) 26.98 134

(6.26)164

(7.65) 22.37

Milk 137(6.43)

142(6.60) 3.65 204

(9.54)197

(9.19) -3.50

Edible oil 150(7.04)

191(8.87) 27.20 219

(10.24)245

(11.43) 12.05

Sugar 111(5.21)

93(4.32) -15.85 131

(6.12)109

(5.08) -17.08

Egg Fish Meat

17(0.80)

23(1.07) 39.85 24

(1.12)30

(1.40) 24.58

Other 58(2.72)

185(8.59) 220.91 129

(6.03)238

(11.10) 84.78

Grand Total

2131(100.00)

2153(100.00) 1.00 2139

(100.00)2144

(100.00) 0.22

Table 2. Nutrient intake by source in India: Energy (Kcal )


intake of calories from other sources like edible oil, fruits andvegetables and milk (Reddy and Bantilan, 2012). Similar patternhas been observed in urban India also. The proportion ofcereals in total calorie intake is lower in urban areas ascompared to rural areas. All these observations clearly indicatethat consumption of cereals has come down due to shift awayfrom traditional staples. It has been observed that as incomerises, households generally diversify their food consumptionpattern by shifting towards high value and high quality fooditems (Kumar et al. 2007).

In the case of fat intake, the situation has improvedboth in urban and rural areas for period under considerationin all the food items except cereals, pulses and sugar. Thesame has been reflected by an increase in fat intake by nearly20 percent in rural India and more than 9 percent in urbanIndia. Only a small portion is being contribution by sugar andpulses.

In the case of protein, though there is a marginal declinein the protein intake in both rural and urban areas, it has beenin the range of recommended level of 60 gms per capita perday. Apart from providing calories, two third of total proteinintake in rural areas and more than half of the total proteinintake in urban areas is being contributed by cereals. Nextmajor source of protein is pulses with 8.5 percent contributionin rural areas and 10.4 percent contribution in urban areas(2009-10). It is revealed that during the period underconsideration, the proportion of protein from cereals andpulses has come down both in rural and urban areas. Thedecline in contribution from cereals is obvious due to shift inconsumption from traditional items to fruits, vegetables andanimal protein. The concern is the decline in the contributionmade by pulses as a source of protein. Mainly in ensuring abalanced diet to the poor who may not have that easy accessto high value protein alternatives of horticultural crops andanimal origin, pulses could be better alternative. The poormainly rely on cereals and pulses for their protein requirements.Under such circumstances, pulses can act as an importantsource of protein for poor in urban and rural India.

Gap in Consumption of different Food Items

The gap in the consumption of different food items incomparison to the level prescribed is presented in Table-5.The consumption of cereals in rural India in both the periodunder consideration is found to be above the recommendedlevel. However, the consumption in urban India declined belowrecommended level during 2009-10 with a gap of 18 gms.Cereals are an import source of energy in Indian diet and theirdeficiency may lead to fall in energy intake and also utilizationof other vital nutrients.

In addition to cereals, the consumption of all itemsexcept sugar and edible oils is found to be lower than theprescribed level in rural as well as urban India during both the

Table 3. Nutrient intake by source in India: Fat (Grams)

Rural Urban Food Items 1999-00 2009-10 Change

(%) 1999-00 2009-10 Change (%)

Cereal 5.1(14.26)

4.3(10.06) -15.77 3.9

(7.78)3.47

(6.35) -10.99

Pulses 0.52(1.45)

0.45(1.05) -13.7 0.63

(1.26)0.54

(0.99) -14.65

F&V 1.22(3.41)

1.57(3.67) 28.15 1.62

(3.23)2.02

(3.69) 24.83

Milk 9.93(27.76)

10.04(23.50) 1.06 15.18

(30.28)14.34

(26.23) -5.53

Edible oil 16.67(46.60)

21.2(49.61) 27.2 24.33

(48.53)27.27

(49.88) 12.05

Sugar 0.00(0.00)

0.00(0.00) -69.29 0.00

(0.00)0.00

(0.00) -22.00

Egg Fish Meat

0.56(1.57)

0.77(1.80) 37.79 0.9

(1.80)1.07

(1.96) 19.15

Other 1.76(4.92)

4.4(10.30) 149.87 3.57

(7.12)5.96

(10.90) 66.81

Grand Total

35.77(100.00)

42.73(100.00) 19.45 50.13

(100.00)54.67

(100.00) 9.05

Table 4. Nutrient intake by source in India: Protein (Grams)

Rural Urban Food Items

1999-00 2009-10 Change (%) 1999-00 2009-10 Change

(%)

Cereal 39.88(68.09)

35.67(61.48) -10.54 33.41

(57.16)30.11

(52.15) -9.86

Pulses 6.4(10.93)

4.94(8.51) -22.78 7.65

(13.09)5.98

(10.36) -21.82

F&V 3.02(5.16)

3.95(6.81) 30.89 3.55

(6.07)4.3

(7.45) 21.07

Milk 5.1(8.71)

5.55(9.57) 8.9 7.27

(12.44)7.36

(12.75) 1.21

Sugar 0.04(0.07)

0.03(0.05) -33.89 0.04

(0.07)0.03

(0.05) -17.54

Egg Fish Meat

2.42(4.13)

3.47(5.98) 43.72 3.41

(5.83)4.45

(7.71) 30.62

Other 1.72(2.94)

4.41(7.60) 156.15 3.13

(5.36)5.5

(9.53) 75.88

Grand Total 58.57(100.00)

58.02(100.00) -0.93 58.45

(100.00)57.74

(100.00) -1.22

Table-5: Gap in consumption and requirement of differentfood items in India

(-) indicates gap in consumption

Rural Urban Food Items Unit

1999-00 2009-10 Change in Gap

(%) 1999-00 2009-10

Change in Gap

(%) Cereals Grams 94 48 -- 17 -18 --

Pulses Grams -14 -19 -12.14 -9 -15 -14.84

Vegetables Grams -170 -115 15.84 -152 -111 11.68

Fruits Grams -72 -52 20.40 -47 -19 28.31

Milk ml -173 -162 3.63 -124 -118 1.98

Edible oil Grams 0 4 -- 7 10 --

Sugar Grams 5 0 -19.71 10 4 --Egg Fish Meat Grams -16 -10 18.62 -11 -6 15.98


periods. However, this gap has come down in all the fooditems other than pulses during 2009-10. The gap in the percapita daily consumption of pulses has increased from 14gms in 1999-2000 to 19 gms in 2009-10 in rural India and from9 gms to 15 gms in Urban India during the same period.

Composition of Consumption Expenditure

The figures presented in the Table-6 revealed that, theproportion of total expenditure on food items has come downover time in both rural and urban India. The expenditure ondifferent commodities except cereals has, in general, eitherincreased or remained same in terms of proportion ofexpenditure made on food items. In the case of pulses, evenwith the decline in quantity consumed, the proportion ofexpenditure towards pulses in the total household expenditureon food items has increased mainly on account of increase inprices of pulses in the recent past.

story. The probable reason for slow growth in production ofpulses is that major proportion of area under pulses iscultivated under rainfed conditions (Savadatti, 2007). Someprogress in pulses has been made during the last decade dueto various policy initiatives of the Government, the positivechange in pulse production does not seem to be enough tocater to the need of masses as has been reflected by the lowerper capita availability of pulses at national level. Per capitaavailability of various food items like milk, sugar and edible oilis found to have increased over a period of time and arecomparable to the prescribed level recommended by NIN, 2010(Table-7). In addition to availability, the distribution of foods,both within the community and the family, may be unfavorableto some vulnerable groups due to low income and lowpurchasing power. In view of the high cost of milk, a largeproportion of the Indian population subsists on dietsconsisting mostly of vegetarian foods with low nutrient bio-availability (NIN, 2010).

Rural Urban Food Items 1999-2000 2009-10 1999-2000 2009-10 Cereals 22.2

(37.4)15.6

(29.1)12.4

(25.8)9.1

(22.4)Gram 0.1

(0.2)0.2

(0.4)0.1

(0.2)0.1

(0.2)Cereals substitute 0.1

(0.2)0.1

(0.2)0.0

(0.0)0.0

(0.0)Pulse and pulse products

3.8(6.4)

3.7(6.9)

2.8(5.8)

2.7(6.6)

Milk and milk products

8.8(14.8)

8.6(16.0)

8.7(18.1)

7.8(19.2)

Edible oil 3.7(6.2)

3.7(6.9)

3.1(6.4)

2.6(6.4)

Egg, fish and meat 3.3(5.6)

3.5(6.5)

3.1(6.4)

2.7(6.6)

Vegetables 6.2(10.4)

6.2(11.6)

5.1(10.6)

4.3(10.6)

Fruits and nuts 1.7(2.9)

1.6(3.0)

2.4(5.0)

2.1(5.2)

Sugar 2.4(4.0)

2.4(4.5)

1.6(3.3)

1.5(3.7)

Others 7.1(12.0)

8.0(14.9)

8.8(17.9)

7.8(19.2)

Total Food 59.4(100)

53.6(100)

48.1(100)

40.7(100)

Total Non-food 40.6 46.4 51.9 59.3

Total Expenditure 100.0 100.0 100.0 100.0

Note: MRP estimates for 1999-2000, Figures in parentheses areproportion of expenditure made on food items

Table 6. Trends in percent composition of consumerexpenditure (MPCE)

Food Production and Availability

The foodgrains production has recorded impressivegrowth since independence. It has increased from about 50million tones at the time of independence to over 240 milliontones during 2010-11. The present level of foodgrainsproduction seems to be adequate at national level, but theproduction of pulses being a vital source of protein for poorand vegetarian society, could not emulate the same growth

Table 7. Availability of different food items in India

Food Items Unit 1990 2000 2005-

06 2006-

07 2007-

08 2008-

09 2009-

10 NIN

Cereals gm/day 432 423 413 407 394 407 407 330

Pulses gm/day 41 32 33 36 42 37 32 42

Milk ml/day 176 220 241 251 260 266 273 300

Vegetables gm/day 212 243 -- 210 -- -- -- 350

Edible Oils gm/day 18 26 29 30 31 35 36 17

Sugar gm/day 34 43 45 46 49 52 51 23

The growth in the production of some of the leadingcrops is presented in Table-8. The performance of pulses wasfound to be poor in comparison to wheat and rice except forthe last decade. During last decade, pulse productionregistered a growth of 3.47 percent, which does not seem tobe sufficient to take care of the individual requirement as theper capita consumption has declined. This decline inconsumption of pulses over years may possibly be attributedto factors like increase in population leading to supply gap,rise in price of pulses (as reflected in the Figure-1) and shift inconsumption towards fruits, vegetables and animal protein,etc.

Crops 1980-81 to 1989-90 1990-91 to 1999-2000

2000-01 to 2011-12

Rice 3.62 (17.06)

2.02 (13.31)

1.72 (5.30)

Wheat 3.57 (15.49)

3.57 (18.30)

2.37 (10.92)

Coarse Cereals

0.40 (2.05)

-0.02 (-2.29)

3.01 (6.97)

Pulses 1.52 (2.10)

0.59 (0.11)

3.47 (3.24)

Table 8. Growth in production of crops (Base TE1981-82=100)

Note: Figures in parentheses are the absolute change in production(million tonnes)Source: Economic Survey, 2011-12, GOI


Same has been reflected by the analysis of compensatedown-price elasticities (Mittal, 2006). The own-price elasticityof all the commodities has the expected negative signs(Table-9). The price elasticity is lowest for cereals and milkand highest for products of meat origin. The price elasticity ofpulses is comparatively higher than cereals and milk especiallyfor very poor, poor and non-poor section of the population.Pulse consumption by very poor household in rural areasdeclines by 0.72 per cent when the price of pulse rises by 1 percent and thus revealing that, pulse consumption is moresensitive to price changes than cereal and milk consumption.High value commodities are very sensitive to prices. MostIndian consumers have relatively low incomes, and tend to bevery price-sensitive buyers of most items, including pulses. Abreakthrough in pulses production technology is necessaryto keep pace with rising demand for this commodity.

down mainly due to decline in the consumption of pulseswhich is a major source of quality protein compared to otherfood items. The concern is reduction in consumption of pulsesfor predominantly vegetarian society and poor due to highprice and fluctuation in supply of pulses. Moreover, pulsesmay act as a low cost substitute during high prices ofvegetables and food items of animal origin. Though, theproduction of pulses has registered an impressive growth inthe recent decade but it is not in pace with the increase in thepopulation. Thus, need of the hour is to increase productionand availability of pulses by adopting various innovativemeasures. This will ensure food and nutritional security bybringing sustainability in agricultural production in thecountry. In order to increase the growth in production ofpulses, institutional and policy support is required forenhancing area under pulses, development of HYVs, supplyof quality inputs (Kumar et al. and Singh et al. 2012),intercropping (Sankaranarayanan et al. 2011), proper extensionof production technologies (Tomar et al. 2009), developmentof value chain, etc. The supply of pulses can be increased byhaving orderly marketing of pulses. The availability ofinformation being a vital component will make farmers torespond more effectively to the various initiatives of theGovernment. With the advent of technology, the informationflow could reach to the lowest level of farming community.Popularizing low cost technology of production, promotionof high yielding varieties and marketing related issues will bemore effective using ICT. The elasticity of the demand forhigh value commodities is highly price sensitive and hence,in the event in the rise in price of such commodities, pulseswill act a substitute for cheaper protein. Also, considering thefact that, wide spread malnutrition prevailing among childrenand women in India, there is need to promote consumption ofpulses by linking to programme like mid-day meal and ruralhealth mission by incorporating either free distribution ofpulses or by subsidizing the food.

REFERENCES

Adiguru, P. and Ramasamy, C. 2003. Agricultural Based Interventionsfor Sustainable Nutritional Security. Policy Paper 17, National Centrefor Agricultural Economics and Policy Research, New Delhi.

GOI. 2001. Consumption of Some Important Commodities in India1999-2000. NSS 55th Round, National Sample Survey Organization,Ministry of Statistics and Programme Implementation, Governmentof India, New Delhi.

GOI. 2012a. Nutritional Intake in India, NSS 66 th Round. NationalSample Survey Organization, Ministry of Statistics and ProgrammeImplementation, Government of India, New Delhi.

GOI. 2012b. Household Consumption of Various Goods and Services inIndia. NSS 66 th Round, National Sample Survey Organization,Ministry of Statistics and Programme Implementation, Governmentof India, New Delhi.

Kumar, P, Mruthyunjaya and M Dey Madan, 2007. Long-term Changesin Indian Food Basket and Nutrition. Economic and PoliticalWeekly September 1, pp 2637-3572.

Figure 1. Wholesale Price Index of major consumption items(Base 1993-94)

Table 9. Compensated Own-Price Elasticity of Pulses

Pulses Cereals Milk Fish, Meat and Chicken Class

Rural Urban Rural Urban Rural Urban Rural Urban Very Poor - 0.72 - 0.79 - 0.40 - 0.44 - 0.84 - 0.34 - 3.11 - 2.62

Poor - 0.74 - 0.78 - 0.43 - 0.44 - 0.01 - 0.52 - 2.78 - 2.41 Non-Poor - 0.75 - 0.77 - 0.45 - 0.44 - 0.46 - 0.64 - 2.47 - 2.24

Rich - 0.74 - 0.74 - 0.45 - 0.41 - 0.72 - 0.78 - 2.20 - 2.01 All - 0.74 - 0.75 - 0.46 - 0.43 - 0.62 - 0.74 - 2.33 - 2.09

In the recent past food consumption pattern has

undergone considerable change owing to various factors likeincrease in income, urbanization, change in consumer tasteand preferences, awareness about safe and healthy food, etc.As a result, the composition of diet and nutrition intake haschanged considerably. It is evident from the fact that the dietaryplan has shifted away from cereals and pulses toward fruits,vegetables, processed food and food items of animal origin.The consumption of pulses has come down for variouspossible reasons like poor availability, high prices andavailability of cheaper alternatives of animal origin. The shiftin consumption towards horticultural crops and food items ofanimal origin has no doubt contributed towards higher intakeof calories, but the intake of protein at the same time has come


Kumar Rajesh, Singh S K, Purushottam and Sah Uma. 2012.Dissemination of pulse production technologies in Uttar Pradesh:A micro-level analysis. Journal of Food Legumes. 25(4): 340-343.

Mittal, Surabhi. 2006. Structural Shift in Demand for Food: projectionsfor 2020. Working Paper No 184, ICRIER, New Delhi.

Mittal, Surabhi. 2007. What affect changes in cereal consumption?Economic and Political Weekly February 3, pp 444-47.

NIN. 2010. Dietary Guidelines for Indian – A Manual. National Instituteof Nutrition, Hyderabad, Andhra Pradesh

Purushottam, Singh S K, Chaudhary R G, Kumar Rajesh, Praharaj C Sand Krishna Bal. 2012. Assessment of technological inputs for majorpulses in Bundelkhand region. Journal of Food Legumes 25(1):61-65.

Reddy A A. 2004. Consumption pattern, trade and production potentialof pulses, Economic and Political Weekly 39(44): 4 854–60.

Reddy A A. 2009. Pulses production technology: Status and way forward.Economic and Political Weekly 44(52): 73–80.

Reddy A A. 2009a. Policy options for India’s edible oil complex.”Economic and Political Weekly 44(4): 22–4.

Reddy A A. 2013. Strategies for reducing mismatch between demandand supply of grain legumes, Indian Journal of Agricultural Sciences,83(3): 243–59

Reddy, A A and Yadav, O P and Malik, D P and Singh, I P and Ardeshna,N J and Kundu, K K and Gupta, S K and Sharma, R and Sawargaonkar,G and Shyam, D M and Reddy, K S. 2013. Utilization Pattern,Demand and Supply of Pearl Millet Grain and Fodder in WesternIndia. Working Paper Series No. 37. Working Paper. InternationalCrops Research Institute for the Semi-Arid Tropics, Patancheru,Andhra Pradesh, India.

Reddy, A A and Bantilan, M C S. 2012.Competitiveness and technicalefficiency: Determinants in the groundnut oil sector of India. FoodPolicy, 37 (3). pp. 255-263.

Sankaranarayanan K, Praharaj C S, Nalayini P and Gopalakrishnan N.2011. Grain legume as a doable remunerative intercrop in rainfedcotton. Journal of Food Legumes 24(1):18-22.

Savadatti, Puspa M. 2007. An Econometric Analysis of Demand andSupply Response of Pulses in India. Karnataka Journal of AgriculturalSciences 20 (3): 545-550.

Shalini, Gupta. 2012. Food Expenditure and Intake in the NSS 66 th

Round. Economic and Political Weekly January 14, pp. 23-26.

Sharma, V. K. 2011. An Economic Analysis of Food ConsumptionPattern in India. International Referred Research Journal 2 (24):71-74.

Singh, R. B. 2009. Towards a Food Secure India and South Asia: MakingHunger History. Asia-Pacific Association of Agricultural ResearchInstitute, Thailand.

Tomar R K S, Sahu B L, Singh Rupendra K and Prajapati R K. 2009.Productivity enhancement of blackgram (Vigna mungo L.) throughimproved production technologies in farmers’ Held. Journal of FoodLegumes. 22(3):202-204.

UNICEF. 2008. Food Prices Increases/ Nutrition Security: Action forChildren. United Nations International Children’s Emergency Fundhttp://www.unicef.org/eapro/Food_Prices_Technical_Note_-july_4th.pdf.

World Bank. 2008. World Development Report 2008: Agriculture forDevelopment. Washington, DC, World Bank.

World Bank. 2012. World Development Indicators 2012. Washington,DC, World Bank.


Short Communication

Genetic variability and character association analysis in french bean (phaseolusvulgaris L.)ANAND SINGH and DHIRENDRA KUMAR SINGH

Department of Vegetable Science, College of Agriculture, G. B. Pant University of Agriculture & Technology,Pantnagar-263 145, U.S.Nagar, Uttarakhand, India; E-mail: [email protected](Received : April 11, 2013 ; Accepted : July 30, 2013)

ABSTRACT

Forty two divergent genotypes of French bean (Phaseolusvulgaris L.) were evaluated for yield and yield attributes duringspring season of 2009-10. Genotypes differed significantly forall the characters. High genetic advance coupled with highheritability was observed for 100- seed weight, seed yield/plant,pod yield/plant and pod yield qt/ha, indicating there by thepreponderance of additive gene action for these characters.Correlation analysis indicated that pod yield/plant wassignificant and positively associated with days taken to Istflowering and Ist picking, pod length and seed yield/plant. Pathco-efficient analysis revealed that days taken to Ist flowering,days to Ist picking, pod length, 100- seed weight and seed yield/plant had positive direct effect on pod yield/ha. Hence, selectionon these traits could be improving seed yield in French bean.

Key words: Correlations, French bean, Genetic advance, Heritability

French bean (Phaseolus vulgaris L.) is a popular podlegume as well as important vegetable crop in many part ofthe world. In India, it is cultivated on an area of about 162thousand hectare with the production of 432 thousand metrictons and annual productivity of 2800kg/ha (FAO, 2009).Success of plant breeding programme depends mainly on thespectrum of genetic variability available in the population. Awide variability will provide the breeder a greater scope forselecting desired material. Yield is a complex and dependentcharacter, which is associated with number of componentcharacters that are interrelated. Thus, effective improvementin yield may be brought through selection in yield componentswhich show close association with yield. Correlation measuresmutual association without considering the causation while,path coefficient analysis provides an effective means ofdisclosure on direct and indirect cause of association andpermits a critical examination of specific forces acting toproduce a given correlation and measures the relativeimportance of each causal factor. Therefore, the present studywas undertaken to study the variability and association ofdifferent yield attributes in the selected genotypes of Frenchbean.

The present study was carried out at VegetableResearch Centre, Department of Vegetable Science, Collegeof Agriculture, G. B. Pant University of Agriculture &

Technology, Pantnagar, U. S. Nagar, Uttarakhand during thespring season of 2009-10. The experimental material consistedof 42 genotypes. The genotypes were sown in a randomizedblock design with three replications. Seeds were sown atspacing of 15 cm within row and 30cm between the rows. Torecording the observation, 10 plants were randomly selectedfrom each genotype and each replication. Data were obtainedon 10 quantitative characters viz,. days to 50% seedgermination, plant height at 30 days after seed sowing, daystaken to Ist flowering, days to Ist picking, pod length, weightof single pod, 100-seed weight, seed yield per plant, pod yieldper plant and pod yield per hectare (q/ha). Analysis ofvariances for all the characters was carried out by the methodof Panse and Sukhatme (1967). Phenotypic, genotypic andcoefficients of variation were calculated as per the method ofBurton and De vane (1953). Genotypic and phenotypiccorrelations were calculated to find out the associationbetween different traits as mentioned by Searle (1961). Thesignificance of correlation coefficients was tested bycomparing with‘t’ value at (n-2) d.f. as discussed by Snedecorand Cochran (1967).

The analysis of variance revealed that the differencesamong the genotypes were significant for all the characterswhich confirm that the material involved in the study hashigher magnitude of variation. Estimates of components ofvariance, heritability in broad sense and genetic advance often characters are presented in Table 1. The results indicatedthat in general the relative magnitude of phenotypic coefficientof variation was higher than the corresponding genotypiccoefficient of variation for all the characters, which indicatedthat these characters had interaction with the environment.Seed yield/plant recorded the highest genotypic coefficientof variation, followed by 100- seed weight, pod yield/plant,pod yield, weight of single pod, days to 50% seed germination,pod length, plant height at 30 days after seed sowing, daystaken to Ist flowering and days to Ist picking. The efficiencyof selection procedure is more appropriate only when theparents having a high variability for the desirable characters,which are heritable in nature. It was suggested by Burton(1952), that genotypic coefficient of variation together withheritability estimates would give the best scope for gettingdesirable characters through selection of parents for

Singh & Singh : Genetic variability and character association analysis in french bean (Phaseolus vulgaris L.) 131

hybridization. Heritability (broad sense) was also found higherfor all the characters except days to Ist picking and weight ofsingle pod. Such high level of heritability may be due to thecontrol of additive gene action in expression of thesecharacters.

Heritability alone does not give any clear picture aboutthe nature of inheritance of a trait. Heritability estimates inconjunction with genetic advance over mean gives the natureof inheritance of a trait. In the present study, high geneticadvance coupled with high heritability was observed in thecharacters namely 100-seed weight, seed yield/plant, pod yield/plant and pod yield qt/ha. This suggested the preponderance

of additive gene action with low environmental influence forthe determination of these characters and could be effectivein phenotypic selection. Raffi and Nath (2004) reported theadditive gene effect for pod yield per plant, 100- seed weightand seed yield /plant. The characters, plant height at 30 daysafter sowing and pod length exhibited high heritability withlow genetic advance may be due to non additive gene action.High heritability coupled with moderate genetic advance wasobserved for days to 50% seed germination and days taken tofirst flowering, implies equal importance of additive and nonadditive gene actions. Similar observations were reported ingreen gram by Parameswarappa and Salimath (2007),Parameswarappa (2005) and Kumar et al., (2003).

Coefficient of Variation Character Mean Genotypic Phenotypic

Heritability (Broad sense) (%)

Genetic advance (GA)

Genetic advance as per cent of mean (%)

Days to 50% seed germination 15.19 15.80 16.26 94.34 4.80 31.59 Plant height at 30 days after seed sowing (cm)

12.90 11.05 12.01 84.70 2.70 20.93

Days taken to 1st flowering 40.74 7.53 7.69 95.80 6.19 15.20 Days to 1st picking 61.71 1.72 1.94 79.27 1.95 3.15 Pod length (cm) 8.89 14.69 15.94 84.94 2.47 27.28 Weight of single pod (g) 4.39 23.01 26.33 76.34 1.78 41.29 100 seed weight (g) 23.84 37.36 37.41 99.69 18.32 76.48 Seed yield per plant (g) 26.61 48.82 48.86 99.81 26.74 100.48 Pod yield per plant (g) 25.19 27.75 27.90 98.94 14.33 56.88 Pod yield (qt/ha) 75.67 27.75 27.90 98.92 42.98 56.85

Table: 1. Genetic parameters for 10 characters in French bean

Table: 2. Correlation coefficient between different characters in French beanCharacter Level Days to 50%

seed germination

Plant height at 30 days after seed

sowing (cm)

Days taken to 1st

flowering

Days to 1st picking

Pod length (cm)

Weight of single pod

(g)

100 seed weight (g)

Seed yield per plant

(g)

Pod yield per plant (g)

Pod yield (qt/ha)

P 1 -0.4540** 0.1699 -0.1365 0.1470 0.1576 0.0270 0.1709 0.0235 0.0235 Days to 50% seed germination G 1 -0.5055** 0.1805 -0.1408 0.1665 0.1699 0.2154 0.1772 0.0219 0.0219

P 1 0.0378 0.0505 -0.0682 -0.1094 -0.1007 0.1119 0.0850 0.0847 Plant height at 30 days after sowing (cm)

G 1 0.0420 0.0645 -0.0761 -0.1143 -0.1090 0.1212 0.0864 0.0866

P 1 -0.1237 0.2565 0.4117** 0.1946 -0.0377 0.3087 0.3092 Days taken to 1st flowering

G 1 -0.1578 0.2845 0.4688** 0.1999 -0.0376 0.3189* 0.3187*

P 1 -0.0650 0.0913 -0.0615 0.2242 0.2940 0.2959 Days to 1st picking

G 1 -0.0709 0.1099 -0.0696 0.2563 0.3412* 0.3401

P 1 0.3361* -0.0766 0.3118* 0.4226* 0.4226* Pod length (cm)

G 1 0.3816* -0.0835 0.3370* 0.4678** 0.4678**

P 1 0.3624* 0.0083 0.1657 0.1648 Weight of single pod (g) G 1 0.4192** 0.0081 0.1973 0.1978

P 1 -0.1671 -0.1510 -0.1508 100 seed weight (g)

G 1 -0.1678 -0.1524 -0.1525

P 1 0.3718* 0.3713* Seed yield per plant (g) G 1 0.3737* 0.3737*

P 1 0.9998 Pod yield per plant (g) G 1 0.1000

P 1 Pod yield (qt/ha)

G 1


The data in respect of correlation coefficient analysisbetween important characters both phenotypic and genotypiclevel are presented in Table 2. In general, the genotypiccorrelation coefficients were higher than phenotypiccorrelations. This indicated that low phenotypic correlationmight be due to the masking effect of environment in geneticassociation between the characters (Johnson et.al.1955). Thecorrelation of the yield and yield contributing charactersindicated that pod yield/ plant was significant and positivelyassociated with days taken to Ist flowering, days to Ist picking,pod length and seed yield per plant. Vasic et.al. (1997),Berrocal et.al. (2002), Upadhyay, (2001) and Chaubey et.al.(2012) reported similar types of findings in French bean.Interestingly, these characters were also positive andsignificantly correlated with each other. Therefore, thepositively correlated yield attributes, days taken to Istflowering, days to first picking, pod length, seed yield/plantshould be considered as crucial parameters for selection inbreeding programme targeted for high yield in French bean.Similar results were observed by Singh (1993) and Vasicet.al.(1997). This association indicating that increase anddecrease in pod yield/ plant directly reflected in the length ofpod. The path analysis (Table3) revealed that days taken toIst flowering, days to Ist picking, pod length, 100- seed weightand seed yield/plant had positive direct effects on pod yield/ha. Whereas negative direct effect was registered for days to50% seed germination, plant height at 30 days after seedsowing, weight of single pod and pod yield/plant. Pod length,days to Ist flowering, seed yield/plant, 100 seed weight, anddays to Ist picking had the highest direct positive effects onpod yield/hectare. These findings are in congruity withPrakash and Ram (1981), Joshi and Mehra (1984) and Nathand Korla (2004).

Table: 3. Phenotypic and genotypic Path coefficient for yield in French bean Level Correlatio

n with pod yield/ ha

Direct effect

Days to 50% seed germination

Plant height at 30 days after seed sowing (cm)

Days taken to 1st flowering

Days to 1st picking

Pod length (cm)

Weight of single pod (g)

100 seed weight (g)

Seed yield per plant (g)

Pod yield per plant (g)

P 0.023 -0.000 - 0.0009 0.0002 -0.0007 0.001 -0.0006 -0.0001 -0.0001 0.2346 Days to 50% seed germination G 0.021 -1.680 - 0.753 0.538 -0.016 0.554 -0.242 .339 .524 -0.133

P 0.084 -0.002 0.0001 - 0.000 0.0002 -0.0001 0.0004 .0000 -0.0000 0.0848 Plant height at 30 days after seed sowing (cm)

G 0.086 -1.490 0.0849 - 0.125 .007 -0.253 0.163 -0.171 0.358 -0.527

P 0.309 0.001 -0.0036 -0.0001 - -0.0006 0.000 -0.0016 -0.0000 0.0000 0.3082 Days taken to 1st flowering G 0.318 2.981 -0.303 -0.062 - -0.018 0.948 -0.669 .314 -0.111 -1.946

P 0.295 .005 0.0001 -0.0001 -0.0002 - -0.000 -0.0003 0.0000 -0.0001 0.2935 Days to 1st picking G 0.340 0.117 .236 -0.096 -0.470 - -0.236 -0.157 -109 0.758 -2.083 P 0.422 0.000 0.000 .0001 0.0010 -0.0003 - -0.0013 0.0000 -0.0002 0.4219 Pod length (cm) G 0.467 3.332 -0.279 0.113 0.848 -0.008 - -0.545 -0.131 0.997 -2.855 P 0.164 -0.003 0.000 .0002 0.0006 0.0004 0.0001 - -0.0001 -0.0000 0.1650 Weight of single

pod (g) G 0.197 -1.428 -0.285 0.170 1.397 0.012 1.271 - .660 0.023 -1.204 P -0.150 -0.000 -0.0004 .0002 0.0003 -0.0003 -0.0001 -0.0014 - 0.0001 -0.1507 100 seed weight (g) G -0.152 1.575 -0.361 0.162 0.596 -0.008 -0.278 -0.598 - -0.496 0.930 P 0.371 0.000 -0.0001 -0.0002 -0.000 0.0011 0.0001 -0.000 0.0000 - 0.3708 Seed yield/ plant (g) G 0.373 2.960 -0.297 -0.0180 -0.112 0.0030 1.123 -0.011 -0264 - -2.281 P 0.999 -0.998 -0.000 -0.0001 0.0005 0.0015 0.0001 -0.0006 0.0001 -0.0003 - Pod yield/ plant (g) G 0.100 -6.105 -0.036 -0.128 0.950 0.040 1.559 -0.281 -0.240 1.106 -

On the basis of the present investigation it was revealed

that days to Ist flowering, days to Ist picking, pod length 100-seed weight, seed yield/plant and pod yield/ plant wereimportant traits in French bean. Therefore, direct selection forthese traits might bring an improvement in green pod andseed yield.

REFERENCES

Berrocal Ibarra S, Ortiz Cereceres J. and Pana VCB. 2002. Yieldcomponents, harvest index and leaf area efficiency of a sample ofa wild population and a domesticated variant of the common bean(Phaseolus vulgaris).South African Journal of Botany. 68: 205-211.

Burton GW. 1952. Quantitative Inheritance in Grasses. Proc. 6th Inst.Grassland. Cong., 1: 277-283.

Burton GW and De Vane EH.1953.Estamating variability in tall Fescue(Festuca arundinacea) from replicated clonal material. Agron.J.45:478-81.

Chaubey BK, Yadav CB, Kumar K and Srivastava RK. 2012. Geneticvariability, character association and path coefficient analysis infaba bean. Journal of Food Legumes 25(4): 348-350.

FAO. 2009. Production year book, Italy, Rome, United Nations.

Johnson HW, Robinson HF and Comstock RE. 1955. Estimates ofvariance and environmental variability in soybean. Agron. Journal47: 314- 318.

Joshi BD.and Mehra KL. 1984. Path analysis of productivity in frenchbean. Prog. Hort.16:78-84

Kumar Kamleshwar, Prasad KD and Verma AK . 2003. Geneticvariability, correlation and path coefficient analysis in greengram.J. Agric. Res. Birsa Agric. Univ. 15: 1 97-101.

Nath S and Korla BN. 2004. Path analysis of some quantitativecharacters in dwarf French bean (Phaseolus vulgaris L) in relationto pod yield. Legume Research, 27(3):228-230.

Singh & Singh : Genetic variability and character association analysis in french bean (Phaseolus vulgaris L.) 133

Panse VG and Sukhatme PV. 1967. Statical Method for AgriculturalWorks.ICAR, New Delhi.

Parameswarappa SG. 2005. Genetic variability, combining ability andpath coefficient analysis in greengram. Karnataka J. Agric. Sci., 18(4): 1090-1092.

Parameswarappa SG. and Salimath KD. 2007. Studies on geneticvariability, combining ability and path coefficient analysis ingreengram. Crop Res. 34 (113): 195- 197.

Prakash KS and Ram HH. 1981. Path coefficient analysis ofmorphological traits and development stages in french bean. Indianj.Agric. Sci. 51:76-80.

Raffi SA and Nath UK. 2004. Variability, heritability, and genetic advanceand relationships of yield and yield contributing characters in drybean (Phaseolus vulgaris L.). Journal of Biological Science4(2):157-159.

Searle SR. 1961. Phenotypic, genotypic and environmental correlations.Biometrics 17: 474-480.

Singh AK. 1993 .Genetic variability and correlation studies in frenchbean.Haryana J.Hort. Sci., 22(3): 125-128.

Snedecor,GW and Cochran WG .1967. Statistical methods. Oxford andIBH Publishing Co. Pvt. Ltd., Calcutta.

Upadhyay P . 2001. Genetic diversity and path coefficient analysis inFrench bean (Phaseolus vulgaris L.) M.Sc. (Ag) thesis submitted toG.B.P.U.A.&T.Pantnagar, India.

Vasic M, Gvozdanovic Varga J, Cervenski J, Jevtic S and Lazic B. 1997.The interdependence of morphological characters in Yugoslavianbean varieties (Phaseolus vulgaris L.). In: Proceedings of the firstBalkan symposium on vegetables and Potatoes, Belgrade, Yugoslavia.Acta Horti., 462: 235-241.


Short Communication

Assessment of heritable components in chickpea (Cicer arietinum L.)SUDHANSHU JAIN, S.C. SRIVASTAVA, Y. M. INDAPURKAR and H.S. YADAVA

Directorate of Research Services, Rajmata Vijayaraje Scindia Krishi Vishwa Vidyalaya, Gwalior 474 002,Madhya Pradesh, India; E-mail: [email protected](Received : August 20, 2013 ; Accepted : November 27, 2013 )

ABSTRACT

Thirty newly bred and diverse genotypes were tested to assessthe heritable variation and yield factors in chickpea. Highlysignificant differences among the genotypes were noted for allcharacters studied. Seed yield/ plant, harvest index, and 100seed weight exhibited high heritability and moderate to highestimates of genetic advance as percentage of mean. Plantheight, pods/ plant, seeds/ pod, 100 seed weight and harvestindex showed positive and significant correlation with seedyield/ plant. The correlation between days to 50% floweringand seed yield/ plant was negative and significant. Path analysisshowed that plant height, days to maturity, primary branches/plant pods/ plant, seeds/ pod, 100 seed weight and harvest indexwere major yield factors in chickpea. Genotypes BG 3012 {(BGD72 x BG 362) (SBD 377)} and AKG 04-11 {(ICC 14 x JG 23) (BG1032) appeared as promising genotypes for use in breedingprogramme aimed at genetic improvement in seed yield ofchickpea.

Key words: Chickpea, Correlation coefficient, Path analysis

Chickpea (Cicer arietinum L.) an important winter pulsecrop of semi-arid tropics. India is a major producer of chickpeain the world which contributes about 8.22 million tons to totalchickpea bosket from an area of around 9.19 million ha. Thegenetic manipulation have been successfully made for shortercrop duration (<100 days), high yield (>2.0 ton/ha) and durableresistance against Fusaroum wilt but, its average productivityis low (895kg/ha during 2010-11) which need improvement.Selection of genotypes based on yield per se is not mucheffective due to existence genotypes x environment interactionhence, breeders concentrate on the selection based yieldattributes which are known to be least influenced by theenvironmental fluctuations. The knowledge on heritablevariation and relative merits of yield factors helps in achievingthe selection gain during the process of section. Someinformation on these aspects is available in chickpea but thisinformation is lacking for newly bred Indian chickpeagenotypes. An attempt was therefore made in this study todetermine the extent of heritable variation and to judge relativemerit of yield factors for genetic amelioration of seed yield inchickpea.

Thirty newly bred genotypes of chickpea, collected fromdifferent AICRP centers of the country were tested inrandomized block design with three replications at Rajmata

Vijayaraje Scindia Krishi Vishwa Vidyalaya, College ofAgriculture, Gwalior, India during Rabi 2010-2011. Eachgenotype was grown in three row plots of 5.0m length havingrow-to-row and plant-to-plant spacing at 30cm and 10cm,respectively. Five competitive plants were randomly selectedfrom each genotypes in each replication for recordingobservation on days to 50 % flowering, days to maturity,plant height (cm), primary branches/plant, pods/ plant, seeds/pod, 100 seed weight (g), harvest index, and seed yield/ plant(g). Statistical software SPAR 1, developed at Indian StatisticalResearch Institute, New Delhi was used for the estimation ofall the genetic parameters of the present study.

Mean sum of squares due to genotypes were highlysignificant for all characters studied indicating the existenceof sufficient variability hence, offer good scope for theselection of desirable genotype from present material (Aroraand Jeena, 1999). The understanding of genetic variabilityprovides many avenues for genetic amelioration of the crophowever; very limited information is available on the extent ofgenetic variation in newly bred genotypes developed throughrecombinant breeding in chickpea. The present study showedthe existence of medium to high magnitude of phenotypiccoefficient of variation (PCV) for pods/ plant, seeds/ pod, 100seed weight and seed yield/ plant . Low to medium estimatesof variability was noted for days to maturity, days to 50%flowering, primary branches/ plant and harvest index. Ingeneral, the estimate of heritability was high for all thecharacters studies except primary branches/ plant and seed/pod. The magnitude of genetic advance as percentage of meanwas high for seed yield/ plant, harvest index, and 100 seedweight. Thus, seed yield/ plant, harvest index, plant heightand 100 seed weight exhibited high heritability coupled withhigh genetic advance hence; direct selection based onphenotypic performance may be effective as these traits areunder control of additive genetic system (Yadava et al., 2003).

In general, the direction of genotypic and phenotypiccorrelations was mostly same but the magnitude of genotypiccorrelation was higher than the phenotypic correlations. Itrevealed the masking influence of environmental factors onphenotypic expression of the characters. A critical perusal ofall possible phenotypic correlation coefficients among seedyield and its attributing characters revealed that plant height,pods/ plant, seeds/ pod, 100 seed weight and harvest indexshowed positive and significant correlation with seed yield/

Jain et al., : Assessment of heritable components in chickpea (Cicer arietinum L.) 135

plant (Table 1) but, the correlation between days to 50%flowering and seed yield/ plant was negative and significant(Jeena and Arora, 2001 and Kumar et. al., 2001). Pods/ plantexhibited positive and significant correlation with primarybranches/ plant, seeds/ pod and harvest index. Similarly, pods/plant recorded positive and significant correlated with harvestindex in chickpea as also observed by Rao and Kumar (2000),Sidramappa (2008), Yadav et al.(2003) and Kumar et.al. (2012).

Path coefficient analysis revealed that directcontribution of plant height, days to maturity, pods/ plant,seeds/ pod, 100 seed weight and harvest index at phenotypiclevel was positive towards seed yield per plant indicatingthem as major yield attributes. The direct bearing of primarybranches/ plant was though negative but it contributedindirectly via pods/ plant, seeds/ pod and harvest indextowards seed yield/ plant as also noted by Yadava and Singh

(2008) and Vaghela et al., (2009) in chickpea. The residualeffect recorded in this study was mainly due to the characterswhich were not taken under observation or due toenvironmental factors which were beyond the control of thisstudy.

In the present study, plant height, days to maturity,primary branches/ plant pods/ plant, seeds/ pod, 100 seedweight and harvest index appeared as major yield componentin the present genetic population of chickpea. Among them,were found to be governed by additive genes hence, top fivegenotypes were selected on the basis of phenotypicperformance of these traits. Among selected genotypes, BG3012 and AKG 04-11 were common genotypes thus, appearedpromising for genetic amelioration of seed yield in chickpea.Both the genotypes were developed by three way crosseshaving parentage as BG 3012 {(BGD 72 x BG 362) (SBD 377)}and AKG 04-11 {(ICC 14 x JG 23) (BG 1032)}.

Characters Plant height (cm)

Days to maturity

Primary branch/ plant

Pods/ Plant

Seeds/ Pod

100 seed weight (g)

Harvest index Seed yield/ plant (g)

Days to 50 % flowering

P G

0.246* 0.260

0.160 0.195

-0.023 -0.028

0.045 0.049

0.020 0.026

0.319** -0.349

0.015 -0.103

-0.246* -0.272

Plant height (cm) P G

0.020 -0.16

0.068 0.164

0.229* 0.670

0.306** 0.380

-0.022 -0.400

0.133 0.010

0.237* 0.257

Days to maturity P G

-0.034 0.071

0.091 0.014

-0.228* -0.418

0.198 0.240

0.058 0.030

0.034 0.031

Primary branch/ plant P G

0.291** 0.670

0.103 0.380

-0.181 -0.400

0.081 0.131

0.030 0.153

Pods/ plant

P G

0.243* 0.897

0.045 0.113

0.386** 0.410

0.554** 0.578

Seeds/ pod

P G

-0.105 -0.183

0.214* 0.236

0.245* 0.500

100 seed weight (g) P G

0.057 0.114

0.304** 0.361

Harvest index P G

0.804** 0.850

Table 1: Phenotypic and genotypic correlations between seed yield / plant and yield factors in chickpea

Table 2: Direct and indirect effects of yield factors on seed yield/ plant in chickpea

*and **Significant at 5 and 1% probability, respectively.

Bold figures denote the direct effects. Residual effects: P = 0.527, G = 0.459

Characters Days to 50 %

flowering

Plant height (cm)

Days to maturity

Primary branch/

plant

Pods/ plant

Seeds/ pod

100 seed weight (g)

Harvest index

Correlation with seed

yield Days to 50 % flowering

P G

-0.256 -0.079

0.029 -0.170

0.001 0.104

0.003 0.002

0.024 -0.016

0.002 0.041

-0.060 -0.167

0.011 0.013

-0.246* -0.272

Plant height (cm) P G

-0.063 -0.021

0.157 -0.656

0.001 -0.009

-0.008 -0.013

0.121 -0.096

0.030 0.905

-0.004 -0.010

0.003 0.157

0.237* 0.257

Days to maturity P G

-0.041 -0.016

0.003 0.010

0.007 0.469

0.004 -0.006

0.008 -0.005

-0.024 -0.669

0.037 0.115

0.040 0.133

0.034 0.031

Primary branch/ plant

P G

0.006 0.002

0.011 -0.108

0.001 0.042

-0.109 -0.080

0.154 -0.220

0.011 0.403

-0.034 -0.092

-0.010 0.206

0.030 0.153

Pods/ plant

P G

-0.011 -0.004

0.036 -0.191

0.001 0.008

-0.035 -0.054

0.528 0.329

0.022 0.206

0.009 0.054

0.004 0.230

0.554** 0.578

Seeds/ pod

P G

-0.005 -0.002

0.048 -0.134

-0.002 -0.251

-0.012 -0.030

0.009 -0.295

0.107 1.601

-0.020 -0.088

0.120 -0.301

0.245* 0.500

100 seed weight (g)

P G

0.002 0.028

-0.003 0.013

0.001 0.100

0.022 0.032

0.024 -0.037

-0.011 -0.294

0.189 0.479

0.080 0.040

0.304** 0.361

Harvest index P G

0.218 0.266

-0.196 -0.194

-0.113 -0.147

-0.118 -0.105

0.239 0.279

0.240 0.211

0.218 0.227

0.316 0.313

0.804* 0.850


It can be concluded from present study thatconsiderable genetic variability was exist in the presentmaterial. Seed yield/ plant, harvest index, and 100 seed weightwere governed by additive genetic system. Plant height, daysto maturity, primary branches/ plant pods/ plant, seeds/ pod,100 seed weight and harvest index appeared as main yieldfactors in chickpea. Selection based on phenotypicperformance of yield factors indicates that BG 3012 and AKG04-11 having diverse genetic base were promising for utilizationin breeding programmes for genetic improvement in chickpea.

REFERENCES

Arora PP and Jeena AS 1999. Association analysis for yield and otherquantitative traits in chickpea. Agriculture Science Digest 19: 183–186.

Jeena AS and Arora PP. 2001. Role of variability for improvement inchickpea. Legume Research 24:135-136

Kumar Abhishek, Suresh Babu G and Lavanya G Roopa 2012. Characterassociation and path analysis in early segregating population inchickpea (Cicer arietinum L.). Legume Research 35: 337- 340

Kumar S, Arora PP and Jeena AS. 2001. Correlation analysis in chickpea.Agriculture Science Digest 22:134-135

Rao SK and Kumar KS. 2000. Analysis of yield factors in short durationchickpeas (Cicer arietinum L). Agriculture Science Digest 20:65-67.

Sidramappa SA, Patil PM and Kajjidoni ST. 2008. Direct and indirecteffects of phenological traits on productivity in recombinant inbredlines population of chickpea. Karnataka Journal of AgricultureScience 21:491- 493

Vaghela MD, Poshiya VK, Savaliy JJ, Davada BK and Mungra KD.2009.Studies on character association and path analysis for seedyield and its components in chickpea. (Cicer arietinum L) LegumeResearch 32: 245-249.

Yadava HS, Singh OP and Agrawal SC. 2003. Assessment of heritablevariation and selection of genotypes for consumer quality traits inchickpea. Indian Journal of Pulses Research 16: 14-16.

Yadava HS and Singh RP. 2008. Assessment of traits determined droughtand temperature tolerance in chickpea. Journal of Food Legumes21: 99-106.

Yadav KS, Naik ML and Yadava H S. 2003. Correlation and pathanalysis in early generation of cowpea. Indian Journal of PulsesResearch 16: 101-103.


Short Communication

Genetic variability and character association for yield and its components in blackgram (Vigna mungo (L.) Hepper)A. NARASIMHAN, B. R. PATIL and B. M. KHADI

Department of Genetics and Plant Breeding, University of Agricultural Sciences, Dharwad-58005, Karnataka, India;E-mail: [email protected](Received : February 27, 2012; Accepted : July 22, 2013)

ABSTRACT

A pooled analysis was carried out in order to estimate the geneticparameters and to study the association in urdbean. Analysisof variance indicated highly significant difference among allthe genotypes studied for all the characters. The phenotypiccoefficient of variation was higher than the genotypic coefficientof variation among all the characters studied. Higher phenotypicand genotypic coefficients of variation were observed for totalseed yield, number of pods per plant and number of bunch.Very high heritability estimates were recorded for all thecharacters recorded viz., plant height, number of branches,number of bunches, number of pods per plant, pod length,number of seeds per pod, test weight and total seed yield. Highgenetic advance expressed as percentage of mean, were recordedfor plant height, number of branches, number of bunches,number of pods per plant and total seed yield. The higher ‘r’values concomitant to the use of very less number of genotypesattributed the maximum towards the least number of charactersbeing significantly correlated. Hence, selection for genotypeswith higher plant height, more number of branches, bunchesand number of pods could facilitate augmentation of seed yieldin urdbean.

Key words: Correlation, Genetic parameters, Selection, Urdbean,Variability.

Yield and most of the yield contributing characters arequantitative in nature showing continuous variation withnormal distribution. The distribution is specified by the twoparameters: mean and variance. They can be effectivelyemployed to estimate genotypic and phenotypic correlationswhich are of immense help in formulating selection strategiesto develop suitable genotypes for different agro climaticregions. The correlation co-efficient gives the measure ofrelationships between traits and provides the degree to whichvarious characters of a crops are associated with productivity.Selection based on yield components is advantageous, ifdifferent yield related traits are well documented. Correlationstudies will establish the extent of such associations betweenyield and yield components giving an idea about thecontribution of different characters to seed yield. In the presentinvestigation an attempt was therefore made to study theseaspects. This information could facilitate formulation ofeffective selection strategies for augmentation of seed yieldin urdbean.

The material comprised of twelve genotypes of urdbeanevaluated for two seasons i.e., Rabi 2009 and summer monthsof 2010 grown in simple RBD with three replications. Seedswere sown with a spacing of 30 cm between the rows and 10cm between the plants in beds of 4 meters. In order to ensurebetter germination and uniform crop stand two seeds per hillwas sown. All the recommended agronomic practices as perthe package of practices were followed. Observations of eightquantitative characters viz., plant height, number of branches,number of bunches, number of pods per plant, pod length,number of seeds per pod, test weight and total seed yield wasrecorded. Five plants were selected randomly and data onindividual mean from each replication was subjected tostatistical analysis. The data was analyzed using a simpleRBD and SPAR programme. For the analysis of the data theANOVA was first calculated. The significance of “f” valuewas tested by comparing the computed value with the tablevalues . The genetic parameters like mean, range, variance,GCV, PCV, heritability and genetic advance over mean werecalculated. Association studies was also carried out with anobjective to determine the degree of association of thecharacters with yield components.

A highly significant variation in the mean performancesof all the genotypes, for eight quantitative characters ofurdbean was revealed by the pooled analysis of variation.Total seed yield exhibited the highest variation among allcharacters studied followed by number of pods per plant. T9(928.81 kg per ha) recorded the highest seed yield while DU3(23.87) had the highest number of pods. In all the charactersstudied the phenotypic coefficient of variation was higherthan the genotypic coefficient of variation. In the presentstudy higher phenotypic and genotypic coefficients ofvariation were observed for total seed yield (42.90 and 42.38respectively), number of pods per plant (26.11 and 25.41respectively) and number of bunch (25.64 and 24.85respectively). Very high heritability estimates were recordedfor all the characters recorded viz., plant height (90%), numberof branches (93%), number of bunches (94%), number of podsper plant (95%), pod length (46%), number of seeds per pod(71%), test weight (70%) and total seed yield (98%). Thisindicated the preponderance of additive gene action in theexpression of all these traits. High genetic advance valueswere recorded for plant height (34.37), number of branches


(38.83), number of bunches (49.58), number of pods per plant(50.94) and total seed yield (86.29). High genetic advancecoupled with high heritability indicated the preponderance ofadditive gene action. The moderate genetic advance observedfor number of seeds per pod (14.31). High heritability withmoderate genetic advance observed for this character whichimplied the action of both additive and non additive geneticcomponents in the expression of this character. Low geneticadvance values were observed for test weight (9.02) and podlength (7.03) which was a consequence of high influence ofenvironment variance indicated the action of non additivegene action. Hence selection based on the above charactersis less effective.

The present investigation revealed that the genotypiccorrelation coefficients, in general, were higher than thephenotypic correlation coefficients indicating masking ofmodifying effects of environment and also the presence ofstrong association between the two corresponding characterswhich also indicated that the selection for the charactersmight be rewarding. The higher ‘r’ values concomitant to theuse of very less number of genotypes attributed the maximumtowards the least number of characters being significantlycorrelated. In the present investigation majority of thecharacters like pod length, number of seeds per pod, hundredseed weight and total seed yield exhibited a non-significantassociation with all the characters.

Among the urdbean genotypes, the variety DU2performed well for two characters viz., number of bunchesand hundred seed weight and it was found resistant toCercospora leaf spot, but it showed a highly susceptible

reaction to MYMV and powdery mildew. Although varietyDU3 performed well for two important characters viz., numberof branches and number of pods per plant, it was foundsusceptible to all the three diseases and it yielded the least,rendering it unsuitable for further utilization in breedingprograms. Despite having the least plant height, number ofbranches, number of pods per plant, pod length and beingsusceptible to MYMV, the green seeded variety Barabankilocal produced an above average yield and was foundmoderately resistant to powdery mildew and Cercospora leafspot. Thus, based on the breeder’s requirement, this genotypecan be used in the further breeding programs.

REFERENCES

Fisher RA and Yates F. 1963. Statistical tables for Biological, Agriculturaland Medical Research. Oliver and Boyd, Edinburgh.

Johnson. HW, Robinson HF and Comstock RE. 1955. Estimation ofgenetic and environmental variability in soybean. Agronomy Journal47: 477-483.

Konda CR, Salimath PM and Mishra MN. 2009. Genetic VariabilityStudies for Productivity and Its Components in Blackgram [Vignamunga (L.) Hepper]. Legume Research 32(1): 59-61.

Krishnan Gopi, Reddy A, Shekar M, Raja Reddy K and SubramaniaReddy K. 2002. Chapter association and path analysis in Urdbean[Vigna munga (L.) Hepper]. Madras Agricultural Journal 89(4-6): 315-318.

Srividhya A, Sekhar M and Reddy GLK. 2005. Correlation and pathanalysis in F2 generation of urdbean {Vigna mungo (L.) Hepper}.Legume Research 28(4).

Venkatesan M, Veeramani N, Anbuselvam Y and Ganesan J. 2004.Correlation and path analysis in blackgram (Vigna mungo L.).Legume Research 27(3):197-200.

Table 1: The genotypic and phenotypic correlation among eight quantitative characters studied in urdbean (Vigna mungo.) inrabi and summer 2009-2010

** Significant at 0.01 level; * Significant at 0.05 level,X1 = Plant height (cm) X2 = Number of branches X3 = Number of bunchesX4 =Pods per plant X5 =Pod length (cm) X6 =No of seeds per podX7 =100 seed weight (g) X8 = Total seed yield (kg per ha)

rp

rg 1 2 3 4 5 6 7 8

1 1 0.18 0.48 0.54 0.31 0.25 0.39 -0.12

2 0.17 1 0.62 0.39 0.26 -0.23 0.3 0.01

3 0.65* 0.45 1 0.70* 0.13 -0.27 0.52 0.19

4 0.71* 0.84** 0.57 1 0.31 -0.17 0.48 -0.10

5 0.24 0.43 0.17 0.38 1 0.12 0.11 0.07

6 0.14 -0.02 -0.23 -0.34 0.22 1 -0.08 -0.16

7 0.61 0.61 0.35 0.47 0.4 -0.3 1 -0.30

8 -0.2 0.08 -0.36 -0.1 0.01 -0.13 0.21 1


Short Communication

Studies on genetic variability, heritability and genetic advance in chickpea (Cicerarietinum L)SHWETA, A.K.YADAV and R.K. YADAV

C.S. Azad University of Agriculture and Technology, Kanpur, Uttar Pradesh, India; E-mail : [email protected](Received : August 10, 2013 ; Accepted : December 04, 2013)

ABSTRACT

Thirty genotypes of chickpea were evaluated to study themagnitude of genetic variability, heritability and geneticadvance in yield and yield contributing characters. A high degreeof significant variation was observed for all the charactersstudied except seeds per pod. The phenotypic and genotypiccoefficients of variation were found maximum for seed yieldper plant followed by pods per plant and seeds per pod whereasminimum for days to maturity. High heritability estimates withhigh genetic advance as percent of mean were observed forsecondary branches per plant, seed yield per plant, 100-seedweight, pods per plant and plant height that could be improvedby simple selection.

Key words: Chickpea, Genetic advance , Heritability, Variability

Chickpea (Cicer arietinum L.) is a major food legumecultivated mainly in Algeria, Ethiopia, Iran, India, Mexico,Morocco, Myanmar, Pakistan, Spain, Syria, Tanzania, Tunisiaand Turkey. It is fourth most important grain legume crop inthe world with a total production of 11.62 million tones (Mt)from an area of about 13.20 million hectare (Mha) .About 8.49Mt of chickpea was produced from 8.94 Mha areas during2012-13 with 949 kg ha-1 an average yield in India. Theinformation on nature of total phenotypic variability togetherwith the magnitude of heritability for any given quantitativecharacter under improvement is of utmost importance to thebreeder to proceed towards fruitful hybridization programme.Yield improvement would be facilitated only when geneticdiversity exists in the material chosen for an improvement.The genotypic and phenotypic coefficients of variation areuseful in detecting the amount of variability present in the setof available genotypes. Heritability and genetic advance helpin determining the influence of environment in the expressionof the characters and the extent to which improvement ispossible after selection. Hence, the study was conducted toquantify the variability in chickpea genotypes for yield andits related characters.

The experimental material consisted of 30 diversegenotypes of chickpea which were laid out in RandomizedBlock Design (RBD) with 3 replications at the RegionalResearch Station, Saini, Kaushambi of C.S. Azad Universityof Agriculture and Technology, Kanpur during rabi 2008-09

and 2009-10. Each plot comprised of four rows of 4 m lengthspaced 30 cm apart with plant to plant spacing of 10 cm. Dataon the basis of five randomly taken competitive plants wererecorded on nine quantitative characters viz., days to 50%flowering, days to maturity, plant height (cm), pods per plant,seeds per pod, primary branches per plant, secondarybranches per plant, 100-seed weight (g) and seed yield perplant (g). Analysis of variance was done based on RBD foreach of the characters separately. The phenotypic andgenotypic coefficients of variation and heritability in broadsense was estimated. Analysis of variance (ANOVA) revealedhighly significant differences among the genotypes for all thecharacters under study except seeds per pod suggestingpresence of substantial amount of variability for all thecharacters in 30 genotypes .

A considerable amount of variation was observed inmost of the characters. The range of mean values wasobserved for days to maturity (116.00 to 144.00), day to 50%flowering (77.00 to 93.00), plant height (29.67 to 63.00), podsper plant (20.33 to 100.01), seed yield per plant (5.41 to 32.62),100 seed weight (14.50 to 25.90), secondary branches per plant(8.67 to 20.00), primary branches per plant (3.00 to 5.67) andseeds per pod (1.00 to 2.33). The characters showing widerange of variation provide an ample scope for selecting thedesirable genotypes. Genetic variability for many of thesecharacters had also been reported earlier by Jeena et al. (2005),Khan et al. (2006) and Durga et al. (2007).

In the study, estimates of phenotypic coefficients ofvariation (PCV) were comparable with respective genotypiccoefficients of variation (GCV) for all the characters. However,the estimates of PCV were, in general, higher than thecorresponding estimates of GCV for all the characters . Thismay result due to the involvement of environment andgenotype x environment effect in the expression of characters.The respective phenotypic and genotypic coefficient ofvariation were found maximum for seed yield per plant (45.98and 45.18) followed by pods per plant (42.60 and 42.07) andseeds per pod (35.96 and 21.31) whereas minimum being fordays to maturity (4.53 and 4.45). Other characters have low tomoderate estimates of PCV and GCV. These observations werein conformity with the findings of some earlier workers likePratap et al. (2004), Jeena et al. (2005) and Tomar et al. (2009).


Mean Range S. No. Characters Min. Max.

PCV GCV Heritability Genetic advance

Genetic advance % of mean

1. Days to 50% flowering 82.65 77.00 93.00 4.82 4.28 78.9 6.48 7.84 2. Days to maturity 137.41 116.00 144.00 4.53 4.45 96.6 12.39 9.01 3. Plant height (cm) 51.51 29.67 63.00 15.04 14.30 90.5 14.44 28.03 4. Pods per plant 47.31 20.33 100.01 42.60 42.07 97.5 14.49 30.62 5. Seeds per pod 1.46 1.00 2.33 35.96 21.31 35.1 0.38 26.02 6. Primary branches per plant 4.13 3.00 5.67 24.76 16.82 46.1 0.97 23.48 7. Secondary branches per plant 12.67 8.67 20.00 29.06 26.05 80.4 6.10 48.14 8. 100 seed weight (g) 18.70 14.50 25.90 18.19 17.23 89.8 6.29 36.63 9. Seed yield per plant (g) 19.86 5.41 32.62 45.98 45.18 96.6 8.58 43.20

These findings suggest that selection can be effective

based on phenotypic along with equal probability of genotypicvalues. With the help of GCV alone, it is not possible todetermine the extent of variation that is heritable. Hence, theknowledge of heritability helps the plant breeders in prediction.The genetic advance for quantitative characters aids inexercising necessary selection procedure.

The high heritability in broad sense was recorded for allthe characters except seeds per pod (35.1) and primarybranches per plant (46.1). These observations are in conformitywith the finding of Pratap et al. (2004), Jeena et al. (2005),Sharma et al. (2005) and Tomar et al. (2009). The highheritability denotes high proportion of genetic effects in thedetermination of these traits and can be adopted for improvinggrain yield in chickpea.

Genetic advance as per cent of mean was maximum forsecondary branches per plant (48.14) followed by seed yieldper plant (43.20), 100 seed weight (33.63), pods per plant(30.62), plant height (28.03), seeds per pod (26.02) and primarybranches per plant (23.40) whereas it was minimum for days tomaturity (9.01) and days to 50% flowering (7.84). In the presentinvestigation, high heritability estimates coupled with highgenetic advance observed for pods per plant, plant height,days to maturity and seed yield per plant might be due tolarge additive gene effects, which revealed that the selectioncriteria based on these traits would improve the seed yield.The results are confirming the findings of Pratap et al. (2004),Burli et al. (2004), Jeena et al. (2005), Tadele et al. (2005) andTomar et al. (2009).

On the basis of heritability and expected geneticadvance as percent of mean for different characters studied inthe present investigation, selection criteria based onsecondary branches per plant, seed yield per plant, 100 seedweight, pods per plant and plant height may be useful forfurther development of high yielding genotypes.

REFERENCES

Burli AV, More SM, Gare BN and Dodake SS. 2004. Studies on geneticvariability and heritability in chickpea under residual soilmoisture condition. Journal of Maharashtra Agricultural Universities29(3) : 353-354.

Durga KK, Murty SSN, Rao YK and Reddy MV. 2007. Genetic studieson yield and yield components of chickpea. Agricultural ScienceDigest 27(3) : 2001-03.

Jeena AS, Arora PP and Utpreti MC. 2005. Divergence analysis inchickpea. Agricultural Science Digest 22(2) : 132-3.

Khan H, Ahmed SQ, Ahamad F, Khan MS and Iqbal N. 2006. Geneticvariability and correlation among quantitative traits in gram. SarhadJournal of Agriculture 22(1) : 55.-9.

Pratap A, Basandra D and Sood BC. 2004. Variability and heritabilitystudies in early maturity chickpea genotypes. Indian Journal ofPulses Research 17(2) : 177-8.

Sharma LK, Saini DP, Kaushik SK and Vaid B. 2005. Genetic variabilityand correlation studies in chickpea (Cicer arietinum L.). Journal ofArid Legumes 2(2): 415-6.

Tadele A, Haddad NI, Malhotra R and Samarah N. 2005. Inducedpolygenic variability in Kabuli chickpea (Cicer arietinum L.) lines.Crop Research, Hisar 29(1): 118-28.

Tomar OK, Singh Dhirendra and Singh D. 2009. Genetic analysis inchickpea (Cicer arietinum L.). Indian Journal of Agricultural Science79(12) : 1041-5.

Table 1: Estimates of mean, range, variance components and genetic parameters for different characters


Short Communication

Effect of zinc, molybdenum and Rhizobium on yield and nutrient uptake in summerurdbean (Vigna mungo L.)KHALIL KHAN and VED PRAKASH

N.D. University of Agriculture and Technology, Narendranagar, Kumarganj, Faizabad, India; [email protected](Received : August 26, 2013 ; Accepted : December 1, 2013)ABSTRACT

A field experiment was conducted for two consecutive Zaidseasons during 2011 and 2012 at Student Instructional Farm ofN.D. University of Agriculture and Technology, Narendra Nagar(Kumarganj), Faizabad to study the effect of zinc, molybdenumand Rhizobium on yield and nutrients dynamics of summerurdbean (Vigna mungo L.). Application of 5.0 kg Zn/ha, 0.5 kgMo/ha and inoculation of seeds with Rhizobium significantlyincreased seed and stover yield during both the years. Besidesbuild up of available N, Zn and Mo in soil after harvested of thecrop, nitrogen uptake significantly increased followingapplication of 5.0 kg zinc, 0.5 kg Mo/ha and Rhizobiuminoculation. Zinc and molybdenum uptake were alsosignificantly increased by the supply of 2.5 kg zinc and 0.5 kgMo/ha.

Key words: Molybdenum application, Nutrient uptake, Seedinoculation, Seed yield, Zn application.

Pulses are an essential item in the daily diet of people inIndia. A large section of the people in the country is vegetarianrequiring a good supplement of protein in their diet. Pulsesare richest source of protein among the vegetarian food.Among the micronutrients, zinc plays a vital role in thesynthesis of protein and nucleic acid and helps in the utilizationof nitrogen and phosphorus in the plant. It promotesnodulation and nitrogen fixation in leguminous crops(Dorosinsky and Rao 1975) and also plays an important rolein starch formation. Usually the pulse seeds are inoculatedwith Rhizobium for symbiotic N fixation and the role of Znand Mo in biological N fixation (BNF) is known. However,location specific fertilizer dose for Zn and Mo needs to bequantified to ascertain their role in yield formation and BNF.Therefore, the present investigation was carried out to studythe effect of zinc, molybdenum and Rhizobium inoculation onyield and nutrient uptake in urdbean (Vigna mungo L.) duringsummer season.

A field experiment was carried out at StudentInstructional Farm of N.D. University of Agriculture andTechnology, Narendranagar (Kumarganj), Faizabad (U.P.)during two consecutive summer season of 2011 and 2012.Treatment combinations (24) comprised of four levels of zinc(0, 2.5, 5.0 and 7.5 kg/ha), three levels of molybdenum (0, 0.5and 1.0 kg/ha) and two levels of Rhizobium (with and withoutinoculation of seeds) were laid out a factorial randomized

complete block design with three replications. Silty loam soilof the experimental field was slightly alkaline in reaction (pH8.21), low to medium fertility (0.58% soil organic carbon, 291.0kg/ha available N, 12.85 kg/ha available P and 217.00 kg/ha K)with good drainage. Soil available micronutrients viz., zinc(0.57 ppm) and molybdenum (0.28 ppm) were in the range oflow and adequate respectively. Periodical and quantitativeobservations related to seed yield and yield components andnutrient content were taken following application of zinc,molybdenum and Rhizobium inoculation on urdbean crop.Total and available N were analyzed by the standardprocedures (Subbiah and Asija 1956 and Jackson 1973). Thedata collected during both the years were subjected tostatistical analysis to draw valid conclusions.

There was a significant influence of zinc, molybdenumand Rhizobium inoculation on grain and stover yield andprotein content in urdbean seed during both the years (Table1). Application of 5.0 kg zinc and 0.5 kg molybdenum/hasignificantly increased both seed and stover yield of urdbeanduring both the years. It is due to essentiality of these twonutrients in plant growth. Similar findings were also reportedelsewhere (Singh and Yadav1997, Jat and rathore 1994). As aresult of inoculation with Rhizobium for promotion of bothplant growth and grain yield, the said inoculation producedsignificantly higher seed and stover yield as evident duringboth the years. Protein content in seed also increased withthe increasing doses of zinc and molybdenum and Rhizobiuminoculation (Krishna 1995, Raju and Verma 1984).

Nitrogen uptake significantly increased with applicationof 5.0 kg zinc and 0.5 kg molybdenum/ha and Rhizobiuminoculation (Table 2). Significantly increased in nitrogenuptake due to zinc and molybdenum was due to increasedseed yield as a result of zinc and molybdenum application.

Similarly Rhizobium inoculation also significantlyincreased nitrogen uptake in both seed and stover. Rhizobiuminoculation promoted crop growth and its yield by increasingN content in biomass; and as a result its total uptake by cropwas also increased. This is in agreement with the finding ofSharma and Minhas 1982 and Singh and Bhadauriya 1984.Besides N uptake, application of 2.5 kg zinc and 0.5 kgmolybdenum/ha significantly increased zinc and molybdenumuptake in both urdbean seed and stover. Rhizoium inoculationalso significantly increased both zinc and molybdenum uptake.


Table 1: Effect of Zinc, Molybdenum and Rhizobium on seed and stover yield (kg/ha) and protein content (%) in urdbeanSeed yield (kg/ha) Stover yield (kg/ha) Protein content (%) Treatments 2011 2012 2011 2012 2011 2012

Zinc levels (kg/ha) 0.0 1050 1067 1906 1993 21.5 21.8 2.5 1106 1120 2000 2099 21.6 21.9 5.0 1151 1169 2089 2184 21.9 22.3 7.5 1162 1180 2109 2205 22.1 22.4 SEm(+) 19 21 36 32 - - CD (P=0.05) 43 48 82 83 - - Molybdenum levels (kg/ha) 0.0 1061 1078 1927 2014 21.6 22.1 0.5 1123 1141 2038 2137 21.7 22.1 1.0 1167 1186 2119 2215 21.8 22.2 SEm(+) 17 18 31 28 - - CD (P=0.05) 43 48 80 83 - - Rhizobium levels Uninoculated 1063 1081 1931 2018 21.6 22.1 Inoculated 1171 1189 2125 2222 22.0 22.6 SEm(+) 14 15 25 23 - - CD (P=0.05) 39 42 72 65 - -

Table 2: Effect of Zinc, Molybdenum and Rhizobium on nitrogen uptake (kg/ha) in urdbean

Seed Stover Total Treatments 2011 2012 2011 2012 2011 2012

Zinc levels (kg/ha) 0.0 36.1 37.2 29.5 30.9 65.7 68.1 2.5 38.4 39.6 31.6 32.7 70.0 72.9 5.0 40.7 41.9 33.8 34.7 74.5 76.7 7.5 41.0 42.2 33.5 35.3 74.6 77.5 SEm(+) 0.8 0.8 0.6 0.5 1.0 1.0 CD (P=0.05) 2.2 2.3 1.7 1.5 2.7 2.8 Molybdenum levels (kg/ha) 0.0 36.7 38.1 29.7 31.4 66.4 69.5 0.5 39.0 40.4 32.0 33.8 71.0 74.2 1.0 40.6 42.1 33.5 35.2 74.1 77.3 SEm(+) 0.7 0.7 0.5 0.5 0.8 0.9 CD (P=0.05) 1.9 2.0 1.5 1.3 2.4 2.4 Rhizobium levels Uninoculated 36.8 38.2 30.1 31.1 66.9 69.2 Inoculated 41.2 42.8 33.4 36.0 74.6 78.8 SEm(+) 0.5 0.6 0.4 0.4 0.7 0.7 CD (P=0.05) 1.5 1.6 1.2 1.1 1.9 2.0

Table 3: Effect of Zinc, Molybdenum and Rhizobium on zinc uptake (g/ha) in urdbean

Seeds Stover Total Treatments 2011 2012 2011 2012 2011 2012

Zinc levels (kg/ha) 0.0 352 362 144 152 496 514 2.5 372 382 152 160 523 542 5.0 387 398 158 167 545 564 7.5 392 402 160 169 551 571 SEm(+) 6.5 6.8 2.7 2.5 6.9 8.1 CD (P=0.05) 18.6 19.3 7.7 7.2 19.8 23.3 Molybdenum levels (kg/ha) 0.0 356 365 145 153 501 518 0.5 378 388 154 163 532 551 1.0 394 405 161 170 554 574 SEm(+) 5.6 6.4 2.3 2.5 7.0 7.7 CD (P=0.05) 16.1 18.4 6.6 7.2 22.5 23.9 Rhizobium levels Uninoculated 358 367 146 154 504 521 Inoculated 394 405 161 170 555 574 SEm(+) 4.6 5.3 1.9 1.8 4.9 5.8 CD (P=0.05) 13.1 15.0 5.4 5.1 14.0 16.5

Khan & Prakash : Effect of zinc, molybdenum and Rhizobium on yield and nutrient uptake in summer urdbean 143

Table 4: Effect of Zinc, Molybdenum and Rhizobium on Mo uptake (g/ha) in urdbean

Table 5: Effect of Zinc, Molybdenum and Rhizobium on available nitrogen, zinc and molybdenum (kg/ha) in soil at after harvestin urdbean

Seed Stover Total Treatments 2011 2012 2011 2012 2011 2012

Zinc levels (kg/ha) 0.0 128 132 77.8 82.1 206 214 2.5 136 139 82.2 86.8 218 226 5.0 142 145 85.7 90.5 227 236 7.5 144 147 86.9 91.7 230 239 SEm(+) 2.5 2.5 1.5 1.4 2.9 3.1 CD (P=0.05) 7.1 7.2 4.2 3.9 8.3 8.9 Molybdenum levels (kg/ha) 0.0 130 133 79 83 208 216 0.5 138 142 84 88 222 230 1.0 144 148 87 92 231 240 SEm(+) 2.2 2.2 1.3 1.3 3.5 3.7 CD (P=0.05) 6.2 6.3 3.6 3.9 9.8 10.3 Rhizobium levels Uninoculated 130 134 79 83 209 217 Inoculated 144 148 87 92 232 240 SEm(+) 1.8 1.8 1.0 1.0 2.1 2.2 CD (P=0.05) 5.0 5.1 3.0 2.7 5.9 6.3

Available N Available Zn Available Mo Treatments 2011 2012 2011 2012 2011 2012

Zinc levels (kg/ha) 0.0 294 299 0.595 0.605 0.289 0.291 2.5 296 300 0.601 0.610 0.292 0.293 5.0 299 303 0.607 0.616 0.295 0.296 7.5 301 305 0.613 0.621 0.299 0.297 SEm(+) 2.1 2.1 0.003 0.003 0.002 0.002 CD (P=0.05) 6.0 6.1 0.008 0.008 NS NS Molybdenum levels (kg/ha) 0.0 296 301 0.602 0.611 0.291 0.290 0.5 297 302 0.604 0.613 0.293 0.295 1.0 299 303 0.606 0.616 0.321 0.324 SEm(+) 1.8 1.8 0.002 0.002 0.001 0.001 CD (P=0.05) NS NS NS NS 0.003 0.003 Rhizobium levels Uninoculated 297 301 0.602 0.611 0.293 0.293 Inoculated 298 303 0.606 0.615 0.299 0.295 SEm(+) 1.5 1.5 0.002 0.002 0.001 0.001 CD (P=0.05) NS NS NS NS NS NS

Besides nutrient content and uptake, application ofgraded doses of zinc did positively influence available N, Zn,Mo in the soil after harvest of urdbean. However, significantincrease in available nitrogen in soil was observed only at 7.5kg of zinc/ha compared to control (no zinc). Similarly,application of graded doses of zinc up to 7.5 kg/ha significantlyincreased available zinc in the soil. Effect of zinc on soilavailable Mo was similar following varying dose of Moapplication. Contrarily, application of 1.0 kg molybdenum/haalso significantly increased available Mo in the soil althoughsoil build up of N and Zn was not evident. Rhizobiuminoculation also positively influenced soil available N, Zn andMo although these were not up to the level of significance.

From the foregoing, it was concluded that in summerurdbean, Rhizobium inoculation along with application of 5.0kg Zn and 0.5 kg Mo could be recommended for realization ofhigher seed yield and enhancing soil fertility.

REFERENCES

Dorosinsky LM and Kady Rao AA. 1975. Effect of inoculation onnitrogen fixation by chickpea, its crop growth and content ofprotein. Microbiology All unic. s.w. res. Instt. Agric. MicrobialHenningrad U.S.S.R. 44: 1103-1106.

Jackson ML.1973. Soil Chemical Analysis. Prentice Hall of India Pvt.Ltd, New Delhi.


Jat RL and Rathore PS. 1994. Effect of S, Mo and Rhizobium inoculationon green gram (Phaseolus radiatus). Indian Journal of Agronomy39: 651-654.

Krishna 1995. Effect of sulphur and zinc application on yield, S and Znuptake and protein content of mung. Legume Research 8: 89-92.

Raju MS and Verma SC 1984. Response of green gram (Vigna radiata)to Rhizobial inoculation in relation to fertilizers nitrogen. LegumeResearch 7 : 73-76.

Sharma EM and Minhas RS. 1982. Effect of molybdenum applicationon the yield and uptake by soybean grain in an alfisol. Journal of

Indian Society of Soil Science 34: 314-17.

Singh U and Yadav DS. 1997. Study on sulphur and zinc nutrition ofgreen gram (Phaseolus radiatus L) in relation to growth attributes,seed protein, yield and S and Zn uptake. Legume Research 20: 224-226.

Singh B and Badhoria BS. 1984. Response of green gram to potassiumand zinc application. Journal of Agriculture Science (U.K.) 102:253.

Subbiah BV and Asija GL. 1956. A rapid procedure for the determinationof available nitrogen in soils. Current Science 25:259–260.


Short Communication

Effect of seed dressers against root rot of cowpeaD. B. PATEL, S. M. CHAUDHARI, R.G. PARMAR and Y. RAVINDRABABU

Centre of Excellence for Research on Pulses, S. D. Agricultural University, Sardarkrushinagar 385 506, Gujarat,India; E-mail: [email protected](Received: December 12, 2012 ; Accepted : November 20, 2013)

ABSTRACT

Studies were conducted to manage the root rot disease of cowpeathrough seed treatment with different seed dressers duringkharif 2009-10, 2010-11 and 2011-12. The minimum root rotdisease incidence was recorded in the seed treatment with Cosco@3gm/kg (11.3%) followed by Thiram @ 2gm/kg (12.9%) andCaptan @ 2gm/kg (13.4 %). The yield data revealed that thehighest grain yield was recorded in seed treatment with Cosco@ 3gm/kg (718 kg/ha) followed by Vitavax @ 2gm/kg (700 kg/ha), Thiram @ 2gm/kg ( 698 kg/ha) and Captan @ 2gm/kg (675kg/ha).

Key words: Rhizoctonia solani, Disease management

Cowpea (Vigna unguiculata) is one of the mostimportant leguminous crops throughout the world, amongvarious diseases, root rot caused by Rhizoctonia solani Kuhninflict substantial yield losses. It is a soil borne disease andmanagement of such soil borne pathogens with fungicidescause hazards to the human health and environment. In thiscontext, soil amendment and seed treatments are gainingimportance for managing such plant pathogens as anotherviable alternative to fungicides. Hence, the study wasconducted to ascertain efficacy of different fungicides, bio-agent and cow dung against the disease.

The field experiments were conducted at PulsesResearch Station, S.D. Agricultural University,Sardarkrushinagar during the cropping season 2009-10, 2010-11 and 2011-12. A most popular cowpea cultivar “GC 4” was

sown by drilling method keeping seed rate 15 kg/ha withspacing 45 × 10 cm. Pre-sowing seed treatment was done withcarbendazim 50 % WP @ 3 g/kg seeds, mancozeb 75% @2gm/kg seeds, combination of carbendazim and mancozeb @3gm/kg, thiram 75% WP @ 2 gm/kg, cosco 75% WP @ 3gm/kg, Trichoderma harzianum @ 4gm/kg and cow dung(farmyard manure) @ 20 gm/kg along with untreated control.The experiment was laid out in randomized block design (RBD)with three replications The data collected were recorded fordisease incidence and yield and were subjected to statisticalanalysis following ‘Analysis of variance’ techniques (Panseand Sukhatme1967). The data recorded on root rot diseaseincidence (%) and yield.

Data analysis revealed that all the treatments resultedsignificantly less incidence of root rot over untreated control(25.7%) during all the cropping seasons and as pooled. Seedtreatment with cosco @ 3gm/kg resulted in the least meandisease incidence (11.3%) followed by thiram @ 2gm/kg (12.9%)and captan @ 2gm/kg (13.4%).

Seed treatment with vitavax @ 2 gm/kg seed (962 kg/ha)resulted in the highest grain yield during 2009 whereas, duringthe year 2010 and 2011 the highest yield was recorded in seedtreatment with cosco @ 3gm/kg (632 and 637 kg/ha,respectively)). In pooled results, the maximum grain yieldwas observed in seed treatment with cosco (718 kg/ha)followed by vitavax (700 kg/ha), thiram ( 698 kg/ha) and captan(675 kg/ha). The present results are supported by the earlierstudies (Monga and Grover, 1991).

Root rot (% incidence) Grain yield (kg/ha) Sr. No

Treatment 2009-10 2010-11 2011-12 Pooled 2009-10 2010-11 2011-12 Pooled

1 Carbendazim 3gm/kg 16.6 17.4 16.4 16.8 890 537 539 655 2 Mancozeb 2gm/kg 20.9 20.3 18.8 20.0 707 497 497 567 3 Sixer 3gm/kg 12.1 14.7 15.0 13.9 914 591 592 699 4 Thiram 2gm/kg 11.3 13.9 13.4 12.9 852 620 622 698 5 Captan 2kg/mg 11.6 14.3 14.3 13.4 822 601 603 675 6 Cosco 3gm/kg 9.7 12.6 11.6 11.3 884 632 637 718 7 Vitavax 2gm/kg 17.1 16.2 15.8 16.4 962 570 569 700 8 T. harzianum 4gm/kg 17.9 18.6 17.5 18.0 784 511 517 604 9 Cow dung 20kg/kg 22.9 21.8 20.7 21.8 706 438 474 551

10 Untreated Control 25.7 26.4 25.1 25.7 677 407 399 494 S. Em. + 1.1 0.9 0.6 0.5 61.6 34.7 34.1 24.8

C.D. at 5% 3.2 2.7 1.7 1.5 183.0 103.1 101.4 69.9 C.V. % 11.4 9.0 5.8 9.0 13.0 11.1 10.8 12.3

Table 1 Effect of seed dressers for the control of root rot of cowpea


The computed economics of different treatments (Table2) revealed that the highest net return (Rs. 8385) was obtainedin seed treatment with cosco followed by thiram (Rs. 7776),vitavax (Rs. 7646) and sixer (carbendazim + mancozeb) (Rs.7430). The highest Incremental Cost Benefit Ratio (ICBR) wasobtained in the seed treatment of T. harzianum (ICBR 1: 3.56)followed by thiram (ICBR 1: 3.24) and cosco (ICBR 1: 3.02).This is also indicative that bio-agent might be acceleratingthe crop growth along with management of soil bornepathogens.

Table 2 Economics of different treatmentsTreatment

No Yield Kg/ha

Yield increased after control (kg/ha)

Gross extra income (Rs.)

Cost of treatment Net return ICBR

1 655.32 160.98 8049.00 2780.00 5269.00 1: 1.89 2 567.21 72.87 3644.00 2400.00 1244.00 1: 0.52 3 698.54 204.20 10210.00 2780.00 7430.00 1: 2.67 4 697.86 203.52 10176.00 2400.00 7776.00 1: 3.24 5 675.21 180.87 9044.00 2590.00 6454.00 1: 2.49 6 717.63 223.29 11165.00 2780.00 8385.00 1: 3.02 7 700.26 205.92 10296.00 2650.00 7646.00 1: 2.89 8 603.83 109.49 5475.00 1200.00 4275.00 1: 3.56 9 551.39 57.05 2853.00 2040.00 813.00 1: 0.40

10 494.34 -- -- -- -- -- Cowpea Price Rs. 50 /kg Captan Rs. 425 /kgCarbendazim Rs. 580 /kg Cosco Rs. 580 /kgMancozeb Rs.300 /kg Vitavax Rs. 540 /kgSixer Rs.580 /kg T. harzianum Rs.150 /kgThiram Rs.300 /kg

REFERENCES

Panse, V.G. and Sukhatme, P.V. (1967). Statistical methods for agriculturalworkers. 2nd ed., IARI Publ. New Delhi pp.146-153.

Monga D. and Grover R. K. (1991).Chemical control of root rot ofcowpea in relation to altered pathogenicity of Fusarium solani.Indian Phytopathology 44:191.


Short Communication

Development of tempeh a value added product from soyabeans and other underutilisedcereals/millets using Rhizophus Oryzae PGJ-1G. GAYATHRY1, K. JOTHILAKSHMI, G. SINDUMATHI and S. PARVATHI

Home Science College and Research Institute, TNAU, Madurai, TamilNadu, India;1Department of Agricultural Microbiology, TamilNadu Agricultural University (TNAU), Coimbatore - 641 003,TamilNadu, India. E-mail: [email protected](Received : September 18, 2012 ; Accepted : November 01, 2013)

ABSTRACT

The present investigation was carried out to develop soyabeanincorporated cereal/ millet tempeh. Rhizophus oryzae wasisolated from finger millet porridge and was used as inoculumfor developing tempeh. Soyabean alone (control) and soyabeanswith other cereals and millets at different incorporation levelswere used to develop tempeh. Among different incorporationlevels, 1:1 blending of the grains was highly accepted with anorganoleptic score of about 98 per cent for the control (soyabeanalone) and 97 per cent for maize + soyabean respectively. Thebiochemical properties of tempeh from various treatments hasrevealed that the protein content of the control was found to besignificantly higher of 48.00g/100g followed by maize +soyabean tempeh of about 38.0g/100g. The highestconcentration of calcium, phosphorous, iron, vitamins namelythiamine and riboflavin was found in maize + soyabean tempeh.The study has very well proved that fermentation of soyabeans,cereals and millets by R. oryzae PGJ-1 yielded a well developedtempeh with enhanced nutritional value compared to thetraditional starters. This highly nutritious protein food can bepopularised among rural folks and the processing technologycan be adopted by small and medium scale legume based foodindustries.

Key words: cereals, fermentation, millets, Rhizophus oryzae PGJ-1,soyabeans, Tempeh

Tempeh is a mold fermented compact cake like soyabeanproduct. It was originated in Indonesia and it is the traditionalcuisine of Indonesians for more than 2000 years. It is producedwith different strains of Rhizopus spp. such as Rhizopusoligosporus, R.oryzae, R. stolonifer and R. arrhizus onsoyabeans (Steinkraus et al. 1983). The mycelium of this moldknit the cotyledons into a compact cake that can be sliced, cutinto cubes and is consumed by people after cooking ortoasting. Rodriguez et al. (2004) has reported that Solid statefermentation (SSF) process represents a technologicalalternative for a great variety of legumes and cereals, orcombination of them, to improve their nutritional quality andto obtain edible products with palatable sensorialcharacteristics. During fermentation of cooked solidsubstrates (grains) enzymes like proteases, lipases,carbohydrases and phytases are produced and because ofthe enzymatic degradation of macromolecules into lower

molecular weight compounds, the cell walls and intracellularmaterial are partly solubilised contributing to a desirabletexture, flavour and aroma of the product. In addition adecrease of anti-nutritional factors (ANF) is associated withthe action of the molds and their enzymes (Blakeman et al.1988). The other substrates that can be used are commonbean, chick pea, rapeseed, lupin, horsebean, groundnut, wheat,corn and soymilk residues (Feng et al. 2005; Johnson et al.,2006).

Tempeh is extremely rich in fiber, vitamins and possessa nutty taste with nougat like texture that odours like a freshmushroom. It can be popularised among the rural folks easilyand go on par with the consumption pattern of ediblemushroom. Further the processing of the substrate usedduring fermentation requires a simpler and easier methodologywhich can produce profound biochemical changes of thesubstrate. Moreover, it is best suited for small and mediumscale processing of locally available cereals and legumes intoa wholesome product of high nutritional value in developingcountries.

The rationale of the present research was to exploitfermentation in the processing of underutilized substrates andutilization of these grains in value-addition. Owing to theimportance of the protein richness and nutritive value of millets/cereals and soyabean tempeh, an experiment was conductedto investigate the suitability of locally available underutilizedmillets/cereals and soyabean incorporations in the productionof tempeh-like product using pure cultures of Rhizophusoryzae.

Screening of suitable mold for tempeh fermentation

Naturally fermented finger millet porridge samples werecollected from the local villages of Madurai district, Tamilnadu,India. From this several mold were isolated using PotatoDextrose Agar (PDA) medium by dilution-plate method. Afterincubation, Rhizophus strains were selected, isolated andcultured separately in Petri plates at room temperature for 3 to4 days. The isolates were further purified by fungal hyphal tipmethod and maintained in PDA slants at 4oC. All the isolateswere used to prepare tempeh using soyabean respectivelyaccording to the laboratory method described by Yeoh and


Merican (1977). Fresh tempeh fermented by each strain wasevaluated for its acceptability using its criteria such as colour- white, surface-covered entirely by mold mycelium, physicalcharacteristics namely compactness, texture, elastic andrubbery for white beans, softer for bean fraction, flavor specificto soyabean tempeh with no residual or beany flavour (Sutardiand Buckle 1985). Preliminary studies such as colonycharacteristics, morphology of the mold was carried out. Thebest strain was identified, screened and selected fordeveloping tempeh using different grains at variousincorporation levels. 1.0 per cent of this inoculum was usedfor fermenting the different treatment combinations fordeveloping tempeh.

Preparation of substrates and production of tempeh

Soyabean (Glycine max), Sorghum (Sorghum vulgare),Maize (Zea mays), Italian millet (Setaria italica), Little millet(Panicum miliare) and Kodo millet (Paspalum scrobiculatum)were obtained from local grocery market in Madurai, Tamilnaduand used for the study. The different incorporation levels andtreatments of grains are presented in Table 1. The raw materialswere sorted, sieved, cleaned of moldy, discoloured grain andother extraneous matter. Tempeh was produced by followingthe traditional Indonesian technology. The cleaned grains weredehulled using dehuller. They were washed thrice and soakedseparately in excess of water for 12 to 16 h. Then the waterwas drained and washed thoroughly with water. Soyabeanwas cooked in a closed pan for one h and for other milletscooking was done for 30 min to soften. After cooking theexcess water was drained off and cooled by spreading themon a clean cloth for 15 min or until the moisture content isretained to 65 per cent. Then it was mixed with 1.0 per centRhizopus oryzae rice flour based spore inoculum with 106

Colony Forming Units per gram of the inoculum base (CFU/g). Traditional tempeh inoculum obtained from the local marketof Malaysia was used for comparing the quality attributes ofthe isolated inoculum in the development of tempeh. It wasthen packed asceptically in polypropylene bags with holes of1 mm size and 2 cm apart and made into a compact packing.Then it was sealed, flattened and kept on a wire mesh tray andfermented at 38ÚC for 36 h. The fresh tempeh was cut intosmall pieces, steamed for 10 min and blanched in 2 per centSodium Chloride solution. Then the slices were dipped in mixof corn flour, Bengal gram flour, chilly powder, asafoetida andsalt of required amount. Then it was deep fat fried in an oilpan. The finished product was subjected to organolepticevaluation.

Fresh tempeh prepared from above incorporation levelwas evaluated for its acceptability and quality using criteriasuch as colour: white, surface: covered entirely by moldmycelium, physical characteristics such as compactness,texture, elasticity, firmness. The fried tempeh developed wasorganoleptically evaluated by 20 trained judges using 9 pointhedonic scale. The judges assessed colour, appearance,

flavour, texture, taste and overall acceptability. Organolepticevaluation was done using a score card, a score of “1” indicatedthat the recipe was “disliked extremely” and a score of “9”denoted the recipe was “liked extremely well” by the panel ofjudges (Amerine et al. 1965).

Biochemical characterisation of tempeh

Fresh tempeh developed using 1:1 blending of cereals/millets and soyabean was tested for moisture content, pH,protein, calcium, phosphorus, iron, vitamins such as thiamineand riboflavin content were done using standard proceduresof AOAC (2002).

Culture inoculum for tempeh developement

The selected fungal strain PGJ-1 was morphologicallycharacterised as Rhizophus sp. It was further identified byMicrobial Type Culture Collection (MTCC), Institute ofMicrobial Technology (IMTECH), Chandigarh, India.According to MTCC the isolated culture was identified asRhizophus oryzae and is deposited at MTCC with accessionnumber 6584. The colonies on the potato dextrose agar mediumwas at first milky white, became greyish black in age, hyalineor brown sporangia were formed on short sporangiophoreswith unbranched rhizoids. The optimum condition for growthof PGJ-1 was 34ÚC and pH was 2.8 to 4.5. R.oryzae has longbeen used in the tempeh solid state fermentation and isconsidered as food grade fungus and Generally Regarded AsSafe (GRAS) for human consumption. (Hachmeister and Fung1993). The zygomycete Rhizopus oligosporus is traditionallyused to ferment soybean tempeh, but it is also possible toferment other legumes and cereals to tempeh. The traditionallymade tempeh harbours a multitude of microorganisms withpotentially beneficial or detrimental effects on quality. Fenget al. (2005) has indicated that pure culture fermentation oftempeh using barley grains yielded rich and quality tempehwith rubbery texture, good flavour and aroma at the end ofincubation period. In the present study the screened isolatePGJ-1 developed quality tempeh with highest organolepticscore of 8 compared to the traditional inoculum which scoredonly 7.

Selection of Soyabean and cereal/ millet incorporationlevels

At the end of fermentation the product developed afresh meaty odour and it was sliced and used for culinarypreparation. From the organoleptic evaluation it was evidentthat 50:50 blending of cereals/ millets and soyabeans werehighly accepted than the 75:25 incorporation levels. Theorganoleptic scores were comparatively higher only whensoyabeans was mixed with other grains at equal proportions.Hence only 1:1 blending treatments alone were selected forbiochemical analysis. They selected treatments for biochemicalcharacterisation were sorghum + soyabean (1:1), maize +

Gayathry et al. : Development of tempeh a value added product from soyabeans and other underutilised cereals 149

soyabean (1:1), Italian millet + soyabean (1:1), little millet +soyabean (1:1), kodo millet + soyabean (1:1), soyabean alone(Control) (100%). Vaidehi et al. (1996) has reported that maize+ soyabean tempeh flour incorporated chapathi, ladoo, soup,porridge mixes recorded protein content of 13.2 g/100g. Butin the present study, the fresh tempeh showed relatively highernutrient content. The soyatempeh was highly accepted withthe overall acceptability score of 98 per cent followed by T7with an organoleptic score of 97 per cent.

The moisture and pH of the tempeh obtained fromselected treatments were found to be constant without anysignificant difference among them (Table 2). The proteincontent of the control was found to be significantly higher of48.00g/100g followed by maize + soyabean tempeh of 38.0 g/100g. The lowest protein content of 16.70 g/100g was recordedby little millet +soyabean incorporation. The protein contentof maize + soyabean tempeh, maize + cow pea tempehdeveloped using their flour by Osundahunsi and Aworh (2003)were 19.7 and 19.2 g/100g respectively. But the protein contentof tempeh prepared in this study using maize + soyabean,Italian millet + soyabean, kodo millet + soyabean as wholegrains showed significantly higher protein content of 38.00,31.00, 30.00 g/100g respectively. The highest concentrationof calcium, phosphorous and iron as well as vitamins namelythiamine and r iboflavin was found in T7 treatment.Fermentation of various treatments by mold might haveenhanced nutritional value and wholesomeness over thestarting material. The results obtained in the present studyare in concurrence with that of Van Veen et al. (1968) who has

Treatments Incorporation levels (75% + 25%) T1 Sorghum + soyabean T2 Maize + soyabean T3 Italian millet+ soyabean T4 Little millet + soyabean T5 Kodo millet + soyabean Incorporation levels (50% + 50%) T6 Sorghum + soyabean T7 Maize + soyabean T8 Italian millet+ soyabean T9 Little millet + soyabean T10 Kodo millet + soyabean T0 (control) Soyabean alone (100%)

Table 2. Biochemical composition of fresh tempeh

Table 1. Standardisation of various incorporation levels ofsoyabeans and cereals/ millets

S. No Treatment Moisture (%) pH Protein

(g) Calcium

(mg) Phosphorus

(mg) Iron (mg)

Thiamine (mg)

Riboflavin (mg)

1. Sorghum + soyabean (T6) 65.70 6.30 24.50 145.30 459.00 7.90 0.56 0.25 2. Maize + soyabean (T7) 64.10 6.02 38.00 272.50 507.40 8.40 0.67 0.29 3. Italian millet + soyabean (T8

) 66.90 6.50 31.00 141.50 494.30 7.60 0.51 0.27 4. Little millet + soyabean (T9) 65.30 6.60 16.70 159.50 272.60 8.40 0.48 0.26 5. Kodo millet + soyabean (T10) 67.90 6.30 30.00 152.00 437.10 6.10 0.46 0.24 6. Soyabean alone (T0) 64.31 6.60 48.00 410.0 450.00 11.2 0.70 0.37 SED 0.4209 0.0448 0.3605 0.0816 0.3362 0.0657 0.0125 0.0037 CD 0.9170 0.0976 0.7854 0.3956 0.7326 0.1432 0.0272 0.0080

stated that during fermentation of the legumes by mold, theprotein content and other nutritional properties are enhanced.Vitamin content such as thiamine and riboflavin also increaseddue to fermentation and it may be attributed by fermentingmicroorganisms which might have increased the bio-availability of vitamins and minerals in millets and pulses bydecreasing the activity of anti-nutritional factors and theresults are similar to the findings of Shrestha and Rati (2003)who has reported that thiamine and riboflavin content of pokoa tempeh like food fermented by R.chinensis increased duringfermentation. Tempeh was developed by Bhavanishanker etal. (1987) using R. oligosporus to increase the nutritive valueof partially defatted groundnut for human consumption. Bau

(1994) has illustrated that solid-state fermentation of rapeseedusing Rhizopus oligosporus would result in the improvementof biological, nutritional value and elimination of antinutritionalsubstances. A 24 h fermentation induced a degradation of 57per cent of á-galactosides, an important flatulence generatorof rapeseed meal. The fermented meal had a high proteincontent (348 g kg”1) and a net increase in aromatic amino acidsand ammonia content.

The present study has very well demonstrated thefeasibility of processing a 1:1 blend of cereals/millets andsoyabean into tempeh like product using Rhizophus oryzaePGJ-1 isolated from a naturally fermented food. Based on theresults of biochemical characteristics and sensory evaluationthe product could very well serve as a protein, mineral andvitamin rich diet. Further soyabeans and other grains aredehulled in a wet process, having the advantage that no majorequipment is required and the grains suffer very littlemechanical damage. It can be concluded that tempeh can bedeveloped with a little bit of processing using selected pureculture of mold strain at relatively cheaper rate usingsoyabeans and other less utilized millets/cereals.

REFERENCES

Amerine MA, Pangbom RM and Rosseler EB. 1965. Principle of sensoryevaluation of food. Academic Press, London.

Bau HM., Villaume C., Lin CF., Evrard J., Quemener B., Nicolas JP andMejean L. 1994. Effect of a solid-state fermentation using Rhizopusoligosporus sp.T-3 on elimination of antinutritional substancesand modification of biochemical constituents of defatted rapeseedmeal. Journal of Science of Food and Agriculture 65: 315–322.


Bhavanishankar TN, Rajashekaran T and Sreenivasamurthy V. 1987.Tempeh-like product by groundnut fermentation. FoodMicrobiology 4(2):121-125

Blakeman JP, McCracken AR and Seaby DA. 1988. Changes broughtabout in solid substrates after fermentations of mixtures of cerealsand pulses with Rhizopus oryzae. Journal of Science of Food andAgriculture 45: 109–118.

Feng XM, Eriksson ARB and Schnurer J. 2005. Growth of lactic acidbacteria and Rhizopus oligosporus during barley tempehfermentation. International Journal of Food Microbiology 104:249–256.

Hachmeister KA and Fung DY. 1993. Tempeh: A mold modifiedindigenous fermented food made from soyabeans and /or cerealgrains. Critical Reviews in Microbiology 19 (3): 137 -188

Jonsson CE., Sandberg AS and Alminger ML. 2006. Reduction ofphytate content while preserving minerals during whole grain cerealtempe fermentation. Journal of Cereal Science 44 (2): 154–160

Osundahunsi OF and Aworh OC. 2003. Nutritional evaluation, withemphasis on protein quality of maize-based complementaryfoods enriched with soyabean and cowpea tempeh. InternationalJournal of Food Science and Technology 38: 809-813.

Rodrýìguez EO., MiIan CJ., Mora ER., Cárdenas VOG and Moreno RC.2004. Quality protein maize (Zea mays L.) tempeh flour throughsolid state fermentation process. Food Science and technology 37(1): 59-67

Shrestha HN and Rati ER. 2003. Microbiological profile of murchastarters and physico-chemical charecteristics of poko, a rice basedfood product of Nepal. Food Biotechnology 16: 1-15

Steinkraus KH, Cullen RE, Pederson CS, Nellis LF and Gavitt BK.1983. Indonesian tempeh and related fermentations. In: Handbookof Indigenous Fermented Foods ed. Steinkraus, K.H., Cullen, R.E.,Pederson, C.S., Nellis, L.F. and Gavitt, B.K. pp. 1–94. New York:Marcel Dekker.

Sutardi S and Buckle KA. 1985. Phytic acid changes in soyabeansfermented by traditional inoculum and six strains of Rhizophusoligosporus. Journal of Applied Bacteriology 58: 539 – 543

Vaidehi MP, Sumangala SG and Vijayakumari J. 1996. Tempeh basedready to prepare food mixes of high nutritional value. Journal ofFood science and Technology 33(6): 506-509

Van Veen AG, Graham DCW and Steinkraus KH. 1968. Fermentedpeanut presscake. Cereal Science today. 13: 96 -99

Gayathry et al. : Development of tempeh a value added product from soyabeans and other underutilised cereals 151

Dr. K.S.Reddy, BARC, Mumbai

Dr. E.V.D. Sastry, Durgapura, Jaipur

Dr. K. B. Saxena, ICRISAT, Hyderabad

Dr. D. Packiaraj, TNAU, Coimbatore

Dr. Jagdish Singh, IIPR, Kanpur

Dr. P.S.Singh, BHU, Varanasi

Dr. Mohan Singh, IIPR, Kanpur

Dr. Ramesh Chandra, Pantnagar

Dr. P.S.Deshmukh, New Delhi

Dr. G. Gopalaswamy, TNAU, Coimbatore

Dr. P. Jayamani, TNAU, Coimbatore

Dr. Livinder Kaur, PAU, Ludhiana

Dr. Ashwini Kumar, Dhaulakuan

Dr. Subhojit Datta, IIPR, Kanpur

List of Refrees for Vol. 26 (3 & 4)

Dr. Dibendu Datta, IIPR, Kanpur

Dr. A. Amarendra Reddy, ICRISAT, Hydearbad

Dr. A. Bhattacharya, Kanpur

Dr. R.K.Gupta, CIPHET, Ludhiana

Dr. Maharaj Singh, IGFRI,Ghansi

Dr. Inderjeet Singh, PAU, Ludhiana

Dr. R.K.Panwar,Pantnagar

Dr. Rahul Wadaskar, Akola

Dr. D.D.Tiwari, Kanpur

Dr. S.K.Singh, IIPR, Kanpur

Dr. J. Souframanian, BARC, Mumbai

Dr. M.N.Singh, BHU, Varanasi

Dr. Anju Pathania, CSK HPKV, Sangla

Dr. Sarvjeet, PAU, Ludhiana

To encourage pulses research and development, ISPRD admits its members asFellows. Applications in the prescribed proforma are invited from eligible ISPRDmembers for the award of ISPRD Fellowship for the year 2013. Any member iseligible if he/she has been the member of the Society continuously precedinglast 5 years and has at least 3 research papers related to food legumes (out ofwhich, one must have been published in the Journal of Food Legumes). Onlythose 2 research papers, which were published in other Journals having NAASrating at or above par with Journal of Food Legumes, will be considered. Filled-in applications along with necessary enclosures should be submitted to the Secretary,Indian Society of Pulses Research and Development, IIPR, Kanpur 208 024(U.P.) by 31 March, 2014. Those who are already Fellows of the Society neednot apply.

Indian Society of Pulses Research and DevelopmentIndian Institute of Pulses Research, Kanpur – 208 024

ISPRD Fellowship Awards 2013

Secretary, [email protected]

Indian Society of Pulses Research and DevelopmentIndian Institute of Pulses Research, Kanpur 208 024

ISPRD Fellowship Awards 2013

1. Name in Full :

2. Father’s Name :

3. Date of Birth :

4. Designation :

5. Field of specialization :

6. Address (with Telephone No., E-mail and Fax)

Office : ________________________________________________________________________________________

Residence : ____________________________________________________________________________________

7. Academic career

Passport Size Photo

Degree University/Institution Year Distinction, if any

Designation Organization Period

8. Employment Record and Experience

9. Enlist only three best publications indicating (a) Name of author(s), (b) year, (c) title, (d) name of journal, volume no. andpage nos.

10. Date/year of life/ordinary membership of ISPRD.

11. Special services rendered to ISPRD.

Signature of applicant with date

Head of Institute/Organization(Optional)

PROFORMA

Journal of Food Legumes (formerly Indian Journal of PulsesResearch) publishes original papers, short communicationsand review articles by renowned scientists, covering all areasof food legumes research. The paper should not have beenpublished or communicated elsewhere. Authors will be solelyresponsible for the factual accuracy of their contribution.Language of publication is English (British).Please send your manuscript to following address:SecretaryISPRDIndian Institute of Pulses ResearchKalyanpur, Kanpur 208 024, IndiaEmail: [email protected] must be submitted through e-mail. You shouldalso submit a hard copy of your manuscript for our officialrecord. Besides author(s) is required to submit a certificatethat the paper is exclusive for Journal of Food Legumes.Manuscripts must conform to the Journal style (see the latestissue). Correct language is the responsibility of the author.After having received your contribution (date of submission),there will be a review process before the editorial board takesdecision regarding acceptance for publication. One copy ofthe revision together with the original manuscript must bereturned to the subject editor or Secretary. The submittedpaper must be one complete word document file comprising atitle page, abstract, text, references, tables, figure legends andfigures. When preparing your text file, please use only TimesNew Roman for text (12 point, double spacing) and Symbolfont for Greek letters to avoid inadvertent charactersubstitutions.FormatEvery original paper should be divided into the following fivesections: ABSTRACT, Key words, INTRODUCTION,MATERIALS AND METHODS, RESULTS ANDDISCUSSION, and REFERENCES. The manuscript should betyped on one side of the paper only, double spaced, and with4-cm margins with page and line numbers. The main title mustbe capital bold. Subheading must be bold italic and Sub-subheading normal italic.At the head of the manuscript, the following informationshould be given: the title of the paper, the name(s) of theauthor(s), the institute where the research was carried out,the present addresses of the authors (foot note) and of thecorresponding author (if different from above Institute).Authors are required to provide running title of the paper.You must supply an E-mail address for the correspondingauthor.The abstract should contain at least one sentence on each ofthe following: objective of investigation (hypothesis, purpose,aim), experimental material, method of investigation, datacollection, result and conclusions. Maximum length of abstractis 175 words. Up to 10 key words should be added at the endof the abstract and separated by comma. Key words must bearranged alphabatically (e.g., EMS, Gamma ray, Mungbean,Mutations, Path coefficient, ......).Each figure, table, and bibliographic entry must have areference in the text. Any correction requested by the reviewershould also be integrated into the file.Manuscript file including tables must be in MS Word andWindows-compatible and must not contain any files otherthan those for the current manuscript. Please do not importthe figures into the text file. The text should be prepared usingstandard software (Microsoft Word); do not use automatedor manual hyphenation.

LengthManuscripts should not exceed a final length of 15 printedpages, i.e., 5,000 words, including spaces required for figures,tables and list of references. Manuscripts for shortcommunications should not exceed 3000 words (3 printedpages, with not more than a total of 2 figures or tables).Units, abbreviations and nomenclatureFor physical units, unit names and symbols, the SI-systemshould be employed. Biological names should be givenaccording to the latest international nomenclature. Botanicaland zoological names, gene designations and gene symbolsare italicised. Yield data should be reported in kg/ha. The nameof varieties or genotypes must start and end with singleinverted comma (e.g., ‘Priya’, ‘IPA 204’, ......).Tables and FiguresTables and figures should be limited to the necessary minimum.Please submit reproducible artwork. For printing of colouredphotograph, authors will be charged Rs. 4000/- perphotograph. It is essential that figures are submitted as high-resolution scans.ReferencesThe list of references should only include publications citedin the text. They should be cited in alphabetical order underthe first author’s name, listing all authors, the year ofpublication and the complete title, according to the followingexamples:Becker HC, Lin SC and Leon J. 1988. Stability analysis in plantbreeding. Plant Breeding 101: 1-23.Sokal RR and Rholf FJ. 1981. Biometry, 2nd Ed. Freeman, SanFrancisco.Tandon HLS. 1993. Methods of Analysis of Soils, Plants, Waterand Fertilizers (ed). Fertilizer Development and ConsultationOrganization, New Delhi, India. 143 pp.Singh DP. 1989. Mutation breeding in blackgram. In: SA Farookand IA Khan (Eds), Breeding Food Legumes. PremierPublishing House, Hyderabad, India. Pp 103-109.Takkar PN and Randhawa NS. 1980. Zinc deficiency in Indiansoils and plants. In: Proceedings of Seminar on Zinc Wastesand their Utilization, 15-16 October 1980, Indian Lead-ZincInformation Centre, Fertilizer Association of India, New Delhi,India. Pp 13-15.Satyanarayan Y. 1953. Photosociological studies on calcariousplants of Bombay. Ph.D. Thesis, Bombay University, Mumbai,India.In the text, the bibliographical reference is made by giving thename of the author(s) with the year of publication. If there aretwo references, then it should be separated by placing ‘comma’(e.g., Becker et al. 1988, Tandon 1993). If references are of thesame year, arrange them in alphabatic order, otherwise arrangethem in ascending order of the years.While preparing manuscripts, authors are requested to gothrough the latest issue of the journal. Authors are alsorequired to send the names & E-mail address of least 3-4reviewers appropriate to their articles.

Instructions to Authors

14. Beneficial traits of endophytic bacteria from field pea nodules and plant growth promotion of field pea 73

S. Narula, R.C. Anand and S.S. Dudeja

15. Effect of temperature-tolerant rhizobial isolates as PGPR on nodulation, growth and yield of 80

Pigeonpea [Cajanus cajan (L) Milsp.]

Simranjit Kaur and Veena Khanna

16. Phenotypic characterization of rhizobacteria associated with mungbean rhizosphere 84

Navprabhjot Kaur and Poonam Sharma

17. Root morphology and architecture (CRIDA indigenous root chamber-pin board method) of two 90

morphologically contrasting genotypes of mungbean under varied water conditions

V. Maruthi, K. Srinivas, K.S. Reddy, B.M.Kk. Reddy, B.M.K. Raju, M. Purushotham Reddy,

D.G.M. Saroja and K. Surender Rao

18. Selection parameters for pigeonpea (Cajanus cajan L. Millsp.) genotypes at early growth stages 97

against soil moisture stress

Anuj Kumar Singh, J.P. Srivastava, R.M. Singh, M.N. Singh and Manoj Kumar

19. Optimization of extrusion process variables for development of pulse-carrot pomace 103

incorporated rice based snacks

Md. Shafiq Alam, Baljit Singh, Harjot Khaira, Jasmeen Kaur and Sunil Kumar Singh

20. Area expansion under improved varieties of lentil through participatory seed production programme 115

in Ballia District of Uttar Pradesh

S. K. Singh, Riyajuddeen, Vinay Shankar Ojha and Sanjay Yadav

21. Performance of chickpea in varied conditions of Uttar Pradesh 120

Lakhan Singh and A.K. Singh

22. Role of pulses in the food and nutritional security in India 124

Shalendra, K. C. Gummagolmath, Purushottam Sharma and S. M. Patil

SHORT COMMUNICATIONS

23. Genetic variability and character association analysis in french bean (Phaseolus vulgaris L.) 130

Anand Singh and Dhirendra Kumar Singh

24. Assessment of heritable components in chickpea (Cicer arietinum L.) 134

Sudhanshu Jain, S. C. Srivastava, Y. M. Indapurkar and H.S. Yadava

25. Genetic variability and character association for yield and its components in black gram 137

(Vigna mungo (L.) Hepper)

A. Narasimhan, B. R. Patil and B. M. Khadi

26. Studies on genetic variability, heritability and genetic advance in chickpea (Cicer arietinum L.) 139

Shweta, A.K. Yadav and R.K. Yadav

27. Effect of zinc, molybdenum and Rhizobium on yield and nutrient uptake in summer 141

urdbean (Vigna mungo L.)

Khalil Khan and Ved Prakash

28. Effect of seed dressers against root rot of cowpea 145

D. B. Patel, S. M. Chaudhari, R.G. Parmar and Y. Ravindrababu

29. Development of tempeh a value added product from soyabeans and other underutilised 147

cereals/millets using Rhizophus Oryzae PGJ-1

G. Gayathry, K. Jothilakshmi, G. Sindumathi and S. Parvathi

List of Referees for Vol. 26 (3 & 4) i

Journal of Food LegumesISSN

0970-6380

Online ISSN0976-2434

Volume 26 Number 3 & 4 September - December 2013

Contents

I SPR D1987

Published by Secretary on behalf of The Indian Society of Pulses Research and Development from

Indian Institute of Pulses Research, Kanpur-208 024E-mail: [email protected]

at Army Printing Press, 33, Nehru Road, Sadar Cantt. Lucknow-2 Ph.: 0522-2481164

(www.isprd.in)

RESEARCH PAPERS

1. Heavy metal toxicity to food legumes: effects, antioxidative defense and tolerance mechanisms 1

Navneet Kaur and Harsh Nayyar

2. Assessment of genetic diversity at molecular level in mungbean (Vigna radiata (L.) Wilczek) 19

S. K. Gupta, R. Bansal, U. J. Vaidya and T. Gopalakrishna

3. Effectiveness and efficiency of gamma rays and Ethyl Methane sulphonate (EMS) in mungbean 25

Kuldeep Singh and M.N. Singh

4. Combining ability analysis in medium duration CGMS based hybrid pigeonpea 29

(Cajanus cajan (L.) Millsp.,)

M. P. Meshram, A.N. Patil and Abhilasha Kharkar

5. Genetic variability, character association and path analysis in clusterbean (Cyamopsis tetragonoloba (L.) Taub) 34

A. Manivannan and C. R. Anandakumar

6. Genetic analysis for quantitative traits in pigeonpea (Cajanus Cajan L. Millsp.) 38

C. K. Chethana, P. S. Dharmaraj, R. Lokesha, G. Girisha, S, Muniswamy, Yamanura,

Niranjana Kumar and D. H. Vinayaka

7. Genetic variabilty and association studies in cowpea (Vigna unguiculata L. walp.) 42

Hasan Khan, K. P. Vishwanatha and H.C. Sowmya

8. Yield and yield attributes of hybrid pigeonpea (ICPH 2671) grown for seed purpose as influenced by 46

plant density and irrigation

M.G. Mula, KB Saxena, A. Rathore and R.V. Kumar

9. Influence of organic nutrient sources on growth, seed yield and economics of cowpea under 51

mid hills of Arunachal Pradesh

V.K. Choudhary, P. Suresh Kumar and R. Bhagawati

10. Pathogenic variation and compatibility groups in Sclerotium rolfsii isolates causing collar rot on 55

chickpea (Cicer arietinum L.)

O.M. Gupta, Sachin Padole and Madhuri Mishra

11. Efficacy of bioinoculants in combination with insecticides against insect pests of 59

blackgram Vigna Mungo (L.) Hepper

P.S. Singh and V. Chourasiya

12. Studies on insecticide efficacy and application schedule for management of blister beetles on greengram 63

K.S. Pawar, Sarika P. Shende, R.M. Wadaskar and A.Y. Thakare

13. Ovipositional preference of bruchid (Callosobruchus Maculatus Fabricius) on pod character and pod 70

maturity

S. Nandini and G. Asokan

Date post:	26-Feb-2021
Category:	Documents
Upload:	others
View:	2 times
Download:	0 times

ISSN 0970-6380 Online ISSN 0976-2434 Journal of Food ...isprd.in/journal_31052014.pdf26. Studies on...

Documents