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Journal of Plant Development Sciences (An International Monthly Refereed Research Journal)

Volume 12 Number 1 January 2020

Contents

REVIEW ARTICLE

Nutrients requirement in fenugreek for their growth and yield

—Surender Singh, V.P.S. Panghal and Raman Jangra ------------------------------------------------------------- 1-5

RESEARCH ARTICLES

Use of ethno medicinal plants by ethnic people for the treatment of dermatological problems

—Vineeta, Abha Manohar K., Gopal Shukla, Biplab C. Sarkar and Sumit Chakravarty ------------------7-15

Effect of water stress on pre-harvest characters of Iranian wheat landraces under irrigated, restricted irrigated

and rain-fed condition

—Amandeep Kaur and Rashpal Singh Sarlach -------------------------------------------------------------------- 17-24

Relationship between independent and dependent variables of recommended maize production technology

—P.K. Netam, Basanti Netam and A. Qureshi --------------------------------------------------------------------- 25-29

Morphological variation of Tendu (Diospyros melanoxylon) leaves in Dhamtri district of Chhattisgarh, India

—Pratap Toppo, R.K. Prajapati, M.L. Lakhera and Abhishek Raj ------------------------------------------- 31-34

Compatibility of entomopathogenic fungi with buprofezin for management of brown planthopper, Nilaparvata

lugens Stal (Delphacidae: Hemiptera) in rice

—B. Nagendra Reddy, V. Jhansi Lakshmi, G.S. Laha and T. Uma Maheswari ----------------------------- 35-38

Production, productivity and profitability of maize (Zea mays) as influenced by different agronomic practices

—Urmila Painkra, P.K. Bhagat, A.K. Paliwal, V.K. Singh and A. K. Sinha --------------------------------- 39-42

Varietal performance of high yielding variety and economics of radish (Raphanus sativus) through front line

demonstration (fld) in east Kameng district of Arunachal Pradesh

—Manoj Kumar Singh, Narendra Deo Singh, B.M. Singh and C.K. Singh ---------------------------------- 43-46

SHORT COMMUNICATIONS

Effect on production and profitability of hybrid rice (Oryza sativa L.) through nutrient management practices

—Kishan Singh, D.K. Gupta, V.K. Singh, A.K. Paliwal and N. Chouksey ----------------------------------- 47-49

Heritability and genetic advance studies for grain yield and related attributes in husked barley (Hordeum vulgare L.)

—Arun Kumar Singh and Javed Ahmed Siddiqui ---------------------------------------------------------------- 51-53

Effect of different varieties and planting methods on growth, yield and quality of sugarcane under northern hill

zone of Chhattisgarh

—Ramakant Singh Sidar, S.S. Tuteja and V.K. Singh ----------------------------------------------------------- 55-57

*Corresponding Author

________________________________________________ Journal of Plant Development Sciences Vol. 12(1) : 1-5. 2020

NUTRIENTS REQUIREMENT IN FENUGREEK FOR THEIR GROWTH AND

YIELD

Surender Singh*, V.P.S. Panghal2 and Raman Jangra

3

1Department of Biology G.S.S.S, Jahajpul, Hisar (Haryana)

2Department of Vegetable Science, CCS HAU, Hisar, Haryana (India)

3 Raman Jangra, JRF

Email: [email protected]

Received-01.01.2020, Revised-28.01.2020 Abstract: Fenugreek (Trigonella foenum-graecum L.) belongs to sub family papilionaceae of leguminous family. It is an

important multipurpose crop commonly used as spice, condiment, food, fodder, soil renovator and medicine for a wide range

of disease. It is a source of raw material for pharmaceutical and perfume industries. Increase in growth and quality throw

suitable management of farm practices could contribute to income of farm land industries. Plant growth depends upon

metabolic process, which is governed by genetic makeup, climatic and edephic factors. Therefore, appropriate farming

practice involving optimum level of nutrients through different sources under different growth condition can help in

widespread and economical cultivation of the crop. Studies indicate that the uses of appropriate fertilizers at right time are

necessary to maximize overall performance of crop. To achieve the objective of sustainable crop production, the study

undertaken by different workers on the effect of organic and inorganic nutrients on growth and yield of fenugreek is needs to

be reviewed.

Keywords: Fenugreek, Nitrogen, Phosphorus, Vermicompost, Biofertilizer, Yield

INTRODUCTION

enugreek belongs to Trigonella genus of

leguminous family.The two important species are

Trigonella foenum-graecum (common methi) and

Trigonella corniculata (kasurimethi). It is an annual,

self pollinating dry land crop widely cultivated in

India and other part of world ( Acharya et al., 2006).

It was cultivated in part of Europe, Northern Africa,

West and South Asia, North and South America,

Australia and India (Mehrafarin et al., 2011). In

India, fenugreek is mainly grown in Rajasthan,

Gujarat, Madhya Pradesh, Maharastra and Haryana

(Godara et al.,2012).

Fenugreek has been grown over 2500 years for its

medicinal properties (Nehra et al., 2006). It is used in

folk medicine for a wide range of disease including

diabetes (Tuncturk, 2011). Fenugreek seed contain

volatile oil, protein, sugar, mucilage and alkaloid. It

is effective in dysentery, diarrhea, dyspepsia, loss of

appetite, chronic cough, enlargement of spleen and

diabetes. It is a vegetable for human and forage for

cattle (Ahmed et al., 2010). Seeds of fenugreek are

used as a spice, condiment, artificial flavoring of

maple syrup and production of hormone (Jorgensen,

1988). Its leaves and seeds are used as anti-diabetic,

lowering blood pressure & cholesterol, anticancer,

roasted grain as coffee substitute, insect control in

stored grain and perfume industry (Mehrafarin et al.,

2011). As it is a multipurpose crop, so, it should be

cultivated on large scale.

Cultivation of crop needs information about its

response to nutrient sand farm practices. Proper use

of nutrients play important role in increasing yield,

quality and quantity of product (Sehatoleslami et al.,

2013).Nitrogen and phosphorus are major plant

nutrients. Nitrogen is essential constituent of amino

acid, protein, nucleic acid, flavin, pyridine, enzyme

and coenzyme which contribute to growth of plant

(Mehta et al., 2011). Nitrogen promotes increased

growth, good leaves, developed stem and dark green

colour plant (Zandi et al., 2011). Phosphorus is a

structural component of nucleic acid, coenzyme,

phosphoprotein and phospholipid. It play important

role in cellular energy transfer, respiration and

photosynthesis (Tuncturk, 2011).It also enhances

symbiotic nitrogen fixation (Mehta et al., 2011).

Potassium and zinc have important role in plant

protection under stress condition. Potassium is

required for maintenance of Co2 fixation, high pH in

stomata and oxidative damage to chloroplast. Zn

helps in root growth and drought tolerance by

increasing Auxin production (Sehatoleslami et al.,

2013). Sulphur play important role in plant

metabolism and has positive effect on root growth in

plant (Basu et al., 2008). An adequate supply of

nitrogen, phosphorus, organic manure and proper

seed rate will leads to higher productivity in

fenugreek (Deora et al., 2009).Heavy use of

chemical fertilizer has adverse effect, whereas

biofertilizers are eco-friendly (Mishra et al.,2011).

There is a gap between nutrient supply and removal

from soil. It can be bridged by combined use of

chemical fertilizers and biofertilizers (Mehta et

al.,2011). Combined use of organic and inorganic

nutrients supplies most of the nutrients to plant and

sustain soil health (Godara et al., 2011). Agricultural

waste are good source of organic nutrients which can

be converted into compost, vermicompost , farmyard

manure and dry leaf manure (Ghadge and Jadhar,

F

REVIEW ARTICLE

mailto:[email protected]

2 SURENDER SINGH, V.P.S. PANGHAL AND RAMAN JANGRA

2013). Plant growth depends on metabolic processes

which are governed by genetic makeup, climatic and

edephic factors. Therefore, growth and yield can be

regulated by improving environment through

agronomic treatments (Ahmed et al., 2010).

Although fenugreek is a multipurpose crop but it has

not obtained due importance in our cropping pattern

(Mehrafarin et al.,2011), therefore, present study

conducted with the objective of investigating the

cultivation aspect of fenugreek and to standardize

optimum nutrients management on growth and yield

parameters of fenugreek.

Effect on growth parameters:

Nitrogen and phosphorus-Application of 20 kg

nitrogen ha-1

and 40 kg P2O5 ha-1

significantly

enhanced plant height, dry matter and number of

branches per plant (Deora et al.,2009), whereas,

increased growth parameters were also reported with

application of 40 kg nitrogen ha-1

and 45 kg P2O5 ha-

1in fenugreek (Godara et al.,2012). These results are

in conformity with the other workers who reported

significant increase in growth character of fenugreek

with application of 46.5kg P2O5 ha-1

(Ahmed et al.,

2010). Mehta et al.(2010) have also reported higher

plant height, dry matter accumulation and leaf area

with application of 20kg nitrogen ha-1

. Significant

increase in growth parameter was observed with

application of nitrogen 40 kg ha-1

along

withvermicompost5 t ha_1

(Dubey et al.,2011).

Khiriya et al.(2001) also reported increase in growth

parameter of fenugreek with increasing level of

phosphorus up to 40 kg ha_1

.Mehta et al. (2010) and

Bhunia et al.(2006) were also in agreement with the

results of the other researchers who observed

increase in growth parameter i.e., plant height, dry

matter accumulation and leaf area, with the

application of 40 kg P2O5 ha-1

. But, according to

Gour et al. (2009) these growth parameters were

recorded maximum with application of 60 kg P2O5

ha-1

. Higher plant height in fenugreek were also

reported from 30 kg P2O5 ha-1

(Tuncturk, 2011),

whereas from 90kg P2O5 ha-1

by Mavai et al.(2000)

observed enhanced growth parameter from 60 kg

P2O5 ha-1

. Increasing level of phosphorus

significantly increase number of branches in

fenugreek (Khan et al., 2005). Number of branches

per plant significantly increased with increasing level

of phosphorus up to 60 kg ha-1

(Gour et al., 2009 and

Kumar et al., 2013). Most of the researchers were not

confirm the findings of Khan et al. (2005), they

reported that phosphorus application showed no

significant effect on growth parameter of fenugreek.

Majority of studies suggested that application of

approximately 40kg P2O5 ha-1

was sufficient for

fenugreek growth. The differences in result might be

due to differentials in environmental condition under

which these studies were carried out.

Vermicompost-Application of vermicompost had

significantly effect on growth parameters of

fenugreek (Jat et al., 2006). Application of 4 t ha-

1vermicompostsignificantly enhanced plant height

and number of branches per plant in fenugreek

(Deora et al., 2009). Growth parameters enhanced

with application of 5 t ha_1

vermicompost along with

40kg nitrogen per hectare (Dubey et al., 2011),

whereas, Karmegam (1999) reported that growth of

green gram increase with application of 3 t

vermicompost per hectare. Number of branches per

plant, number of pod per plant and pod length was

recorded maximum with the application of

vermicompost4 t ha-1

(Jat et al., 2006 and Kumar et

al., 2013).Integration of 50% RDF through poultry

manure + 50% RDF through inorganic source to

fenugreek recorded higher number of branches per

plant and biological yield in fenugreek (Chaudhary et

al., 2011).

Biofertilizers- Phosphorene dissolves the bound form

of phosphate and makes it available to plant which

leads to increase in plant growth and dry matter

(Ahmed et al., 2010). Application of Rhizobium or

PSB resulted in higher plant height but dry matter

and leaf area was significantly higher with

combination of Rhizobium spp. and PSB (Mehta et

al., 2010). These results are in harmony with findings

of Bhunia et al. (2006) in fenugreek, whereas,

Rammurti (1996) has not confirm the above findings.

He observed that before sowing if seed inoculated

with Rhizobium had no effect on different growth

parameters in fenugreek, but Panghal et al.

(2014)reported that plant height, number of branches

per plant, number of pod per plant and pod length

was increased significantly if seeds of fenugreek

treated with Rhizobium + PSB solution before

sowing when compared to without inoculation.

Effect on yield attributes and yield: Nitrogen and phosphorus–Application of nitrogen

has significant effect on yield and yield attributes in

fenugreek. Application of 25 kg N ha-1

produced

highest number of pod per plant but maximum seed

yield and biological yield was obtained from 75 kg N

ha-1

(Zandi et al., 2011). Mehta et al. (2011) reported

that number of seed per pod, number of seed per

plant, 1000 seed weight, seed and biological yield

increased with 20 kg N ha-1

and these findings were

also confirmed by Tuncturk et al. (2011) and Gowda

et al. (2006). Application of 40 kg N ha-1

+45 kg P2O5

ha1recorded higher pod length, pod per plant ,seed

per pod and 1000 seed weight ( Godara et al., 2012

and Mavai, 1997) Whereas Bhunia et al. (2006)

recorded significantly higher seed and straw yield

with20 kg N ha-1

+40 kg P2O5 ha-1

. The difference in

results might be due to difference in environmental

and soil conditions under which these studies were

carried out. Adequate supply of nitrogen may

increase photosynthesis and translocation of

photosynthate, which increases yield by increasing

flowering and fruiting.

Many researcher reported higher seed yield in

fenugreek with application of phosphorus

(Chaudhary, 1999; Khan et al., 200519 and Mavai et

JOURNAL OF PLANT DEVELOPMENT SCIENCES VOL. 12(1) 3

al., 2000). Maximum seed yield was obtained when

40 kg ha-1

phosphorus was applied (Basu et al., 2008

and Bhunia et al., 2006). Whereas, other researchers

are in agreement that mineral fertilizer applied at a

rate of 60 kg P2O5 ha-1

resulted in maximum number

of seed per pod,1000 seed weight, number of seed

per plant, seed yield, biological yield and harvest

index (Gour et al., 2009 and Khan et al., 2005).

Application of 60 kg P2O5 ha-1

resulted in higher

number of pod plant-1

,1000seed weight, whereas,

highest seed yield was obtained with the application

of 60 and 90 kg P2O5ha-1

(Tuncturk ,2011).Whereas,

Khan et al. (2005) reported that number of pod per

plant was not affected by phosphorus application but

phosphorus application improved performance in

term of 1000 seed weight. Some researchers reported

that application of 60 kg P ha-1

significantly

increased number of pod per plant, but 40 kg P ha-1

significantly increased number of seed per pod and

seed yield (Basu et al., 2008; Bhunia et al., 2006;

Kumar et al., 2013; Mehta, Kumar et al., 2011 and

Mehta et al., 2010). Applied phosphorus might have

enhanced nitrogenase activity which increase root

nodulation and various physiological process in plant

.It increase translocation of photosynthate which

results in increased seed yield.

Vermicompost - Number of pod per plant, seed yield

and straw yield significantly increased with

application of 4tha-1

vermicompost in fenugreek

(Kumar, 2013). Whereas, other researchers suggested

that application of 5t ha-1

vermicompostand 40 kg N

ha-1

along with Rhizobiumgave maximum seed and

straw yield (Bhunia, 2006). Significantly higher

number of pod per plant, seed and straw yield

recorded with combined application of FYM 10t ha-1

+vermicompost5t ha-1

+ Rhizobium+PSB[Kumawat

et al., 2013 and Fathi et al., 2012). Combined

application of 50% RDF through vermicompost +

50% through inorganic source increased seed yield,

straw yield and biological yield (Godara et al., 2012).

Integration of 50% RDF through poultry manure +

50% RDF through inorganic source to fenugreek

recorded higher numberof pod per plant, seed per

pod, seed yield and biological yield (Chaudhary et

al., 2011).Vermicompost supply additional nutrients

and increase solubility of soil nutrientsit increase

yield by increasing flowering and fruiting.

Biofertilizers- Inoculation of seed with PSB and

Rhizobium increased seed and straw yield in

fenugreek (Kumar et al., 2000 and Mehta et al.,

2011).These results are in accordance with findings

of Bhunia at el.(2006), Chaudhary (1999) and

Panghal et al. (2014). Application of bio-phosphate

fertilizer significantly increase pod per plant, weight

of pod plant-1,

,seed and straw yield (Ahmed et al.,

2010).Application of Rhizobium increase root growth

and PSB increase phosphate solubilizaion it increase

growth and yield.

CONCLUSION

Fenugreek is a commercial and multipurpose crop. It

is used as medicine for wide range of disease, spices,

condiments, food, forage, soil renovator, insect

control in stored grain. It is a dryland legume crop

which responds to application of irrigation. Studies

related to agronomic practices which could produce

high growth of fenugreek under different

environmental conditions are uncommon. Efficient

agronomic practice for Indian growing conditions

needs to be developed. There is a need to standardize

the optimum level of nutrient under different growth

conditions for assured and high quality as well as

quantity of fenugreek. Appropriate farming for wide

range of growth condition can help in widespread

cultivation to meet increasing demand of this crop.It

can be inferred from the present review that higher

growth, development and yield of fenugreek can be

obtained with application of 20 kg N and 40kg P2O5

ha-1

with inoculation of seed by PSB and Rhizobium.

The differences in result might be due to different

environmental conditions under which these studies

were conducted. Researcher conducted their

experiment under different condition and did not

combine the level of nutrient with different spatial

arrangements. Wide range of environmental

conditions prevails in India and world which affect

plant growth. Requirements of plant change with

change in climatic and edephic factors.

Standardization of optimum nutrient level needs

verification by more studies under different

conditions. Therefore, confirmation of trends seen in

studies needs to be obtained before providing more

specific recommendation of nutrients level can be

made.

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USE OF ETHNO MEDICINAL PLANTS BY ETHNIC PEOPLE FOR THE

TREATMENT OF DERMATOLOGICAL PROBLEMS

Vineeta*, Abha Manohar K., Gopal Shukla, Biplab C. Sarkar and Sumit Chakravarty

Department of Forestry, Uttar Banga Krishi Viswavidyalaya

Pundibari-736165, Cooch Behar (West Bengal)


Received-05.01.2020, Revised-26.01.2020 Abstract: Medicinal plants are a rich source of active ingredients of secondary metabolites which provide a safer and cost effective way to treat diseases. The present article reviewed the published paper on ethno botanical plants used to treat the dermatological problems which are common in the West Bengal state of India and ethnic people of the state used locally available plant resources. A total of 74 plants belonging 69 genera and 36 families have been extracted for their therapeutic use against different skin related problems such as cuts, burns, infection, leucoderma, boils etc. Among all the plant parts, leaves were the most frequently utilized part of plant and most herbal remedies are prepared as paste, extract or juice and applied externally and were found to possess good healing property over a short period of time. The present study concluded that further clinical and phytochemical experimentation is needed.

Keywords: Medicinal plants, Ethnobotanical, Skin, Leucoderma, Juice, Ethnic

INTRODUCTION

lants are always being important and used as

traditional medicine, since the dawn of human

civilization. Many studies have shown that over 80%

of people in developing countries depend on the

traditional medicines for their basic primary health

care system (Bannerman, 1982). India which is

known for its rich and diverse flora and fauna and

considered as 12 mega diverse countries of the world

with 16 agro climatic zones, 12 vegetative zones, 15

biotic provinces and 426 biomes with 15,000

medicinal plants, out of which 7,000 are used in

Ayurveda, 700 in Unani and 600 in Siddha systems of medicine (Hoota and Chatterjee, 2016). In India

there are many ethnic groups with rich cultural

heritage which still using traditional herbal medicine

for treating various skin diseases (Oyedemi et al.,

2018; Newman and Cragg, 2007;Rahman et al.,

2008). Skin disease is seldom deadly and has been

estimated that it account for 34% of all occupational

diseases and only plants have been the principal form

of medicine throughout the world, as people strive to

stay healthy in the face of chronic stress and

pollution, and to treat illness with medicines that work in count with the body’s own defense (Kohen,

1999). From the ancient times various types of skin

diseases like boils, sores, leprosy, eczema, acne,

leucoderma, ringworm etc. are treated completely

with plant origin medicines but now a days clinical

medicine takes some of its charm, but herbal

treatmentsare still on its existence among the ethinic

communities and gaining more attention around the

world perhaps due to the long term use of western

medicine induce severe complications.Medicinal

plants are generally has a rich source of vitamins,

antioxidants, essential oils and oils, hydrocolloids, proteins, terpenoids and other bioactive compounds

(Dubey, 2004) which help in the treatment of various

bacterial, fungal and viral skin diseases. Elaborate studies around the world have demonstrated that skin

diseases are treated by herbal remedies from a

variety of plant parts such as leaves, bark, stem, root,

or fruit and these medicinal preparations are

administered topically and may be applied in the

form of cream, lotion, gel, soap, sap, solvent extract

or ointment, and have also been established to

possess antimicrobial properties (Smon et al., 2009).

The state West Bengal has varied climatic conditions

and occupies rich biodiversity. The state has large no

of ethinic communitywhich follow their own culture.

Due to temperature, high rain fall and high humidity, skin disease is an issue among the poor communities

which is somehow responsible for dermatological

problems and presence of ethnic community with

their traditional knowledge preferred mainly

ethanomedicinal plants for their skin treatment.Many

studies were already done in this area of research but

in a scattered way and there is no such collective

information of different plants used in the

dematological problem across the state, Therefore,

the present review article is extracted from different

scientific literature of ethano medicinal plants used in dermatological problem in different regions of West

Bengal. Only valid information of plants, plant part

used, different ailments, its mode of application were

considered in this study. So, the present study

focused on the endangered use of ethanomedicinal

plants by ethinic people for the treatment of

dermatological problems

MATERIALS AND METHODS

The State of West Bengal is situated in the eastern

part of the country between 21o20' and 27o32' N latitude and 85o50' and 89o52' E longitude with the

P

RESEARCH ARTICLE


8 VINEETA, ABHA MANOHAR K., GOPAL SHUKLA, BIPLAB C. SARKAR AND SUMIT CHAKRAVARTY

Tropic of Cancer running across it. The total area of

the state is 88,752 sq. km which is 2.7% of the total

area in the country. The estimated population of

West Bengal in 2009 was 87.8 million and has

become 91.3 million as per the latest Census of India

carried out in 2011 (WBSAP, 2011).The climate of

the State is tropical and humid except in the northern

hilly region which is close to the Himalayas. The

temperature in the mainland normally varies between

24°C to 40°C during summer and 7°C to 26°C during

the winter. The average rainfall in the State is

about 1750 mm with considerable variation among

the districts ranging between 1234 mm in

Birbhum to 4136 mm in Jalpaiguri(WBSAP, 2011).

Due to varied climatic conditions variation in

biodiversity is vast. The state has highly dependent

communities such as Gonds, Kol, Santal, Oraon,

Munda, Lodha, Mech, Bedia, Bhumij, Mahali etc. on

these valuable biodiversity resources and they

commonly acquired a high value ethno-medicinal

knowledge owing to their close affinity with the

surrounding plant cover.

RESULT AND DISCUSSION

Composition of plants

There are number of plants are identified by

researchers in different region of West Bengal and

used by tribal people in their traditional way to treat

different disordersuch as in Bankura it was 43 plant

species, respectively (Sinhababu and Banerjee 2013),

115 plant species in Jalpaiguri (Bose et al., 2015) and

35 plant species in Naxalbari (Biswakarma et al.,

2015). In this study we observed atotal of 74

speciesbelonging to 43 species and 69 genera. The

species are arranged in alphabetical order with their

botanical name, local name, family, habitat, plant

part used and mode of application were given in table

1. After exploring the data it is observed that the

collected literature consists of 29 tree species

(Woodfordiafruticosa, Melastomamalabatricum,

Azadirachta indica, Toonaciliataetc), 26 herb species

(Hemidesmusindicus, Ecliptaprostrata, Bidenspilosa,

Paederiafoetidaetc), 11 shrub species (Calotropis

gigantean, Buddleja asiatica, Glycosmisarborea,

Jatrophacurcasetc), while least was observed in

climber,creeper and grassin fig 1.

Dominating family recorded was Fabaceae (5

species, 4 genera), Asteraceae (4 species, 4 genera),

Euphorbiaceae (4 species, 4 genera), Malvaceae (3

species, 3 genera), Moraceae (3 species, 3 genera)

and so on in fig 2. Genera with maximum species

recorded in Terminalia represented 3 species and

Cassia, Solanum and Trichosanthus was represented

by 2 species while Abutilon, Aloe,Alstonia,

Artocarpusetcwere represented by one species in fig

3. Family with most dominant genera was recorded

in Asteraceae, Euphorbiaceae, Fabaceae with 4 no of

genera each while others species represent only 1

genera each. Similarly many studies revealed the use

of diverse species in their skin problems (Kumar et

al., 2010; Ghosh et al., 2013). Hota and Chatterjee

(2016) observed 37 plants belonging to 26 families

were documented for their skin therapeutic use in

PaschimMedinipur region.

Nagariyaet al., 2010 reported the use of medicinal

plants for healing of skin diseases in different regions

of India. The plant parts used for medicinal purpose

are leaves, root, stem, fruits, the complete aerial parts

the whole plants barks and flower. However, leaves

were found most requently used parts (Jatavet al.,

2013). After reviewing the collected literature it is

observed that based on their traditional knowledge,

people used different plant parts with different modes

of preparation for curing their no. of ailments related

to skin. The most dominating plant part used by

different tribal communities for different species

were leaves (Psidiumguajava,

Pterocarpusmarsupium, Alstoniascholaris, Cassia

alataetc) followed by all above ground parts

(Peperomia pellucid, Solanumamericanum,

Bidenspilosa, Elephantopusscaberetc) and seeds

(Madhuca indica, Entadarheedii, Caesalpinia crista,

Millettiapinnataetc)in fig 4.Other plant parts like

bark, stem, latex, rhizome, twigs, flower, fruits etc

are also used but only few plants fall under these

groups. Most of the ethnobotanical studies confirmed

that the leaves are the major portion of the plant used

in the treatment of diseases (Ignacimuthuet al., 2008;

Choudhuryet al., 2012).

Ethano medicinal plants are used by ethinic

communities as per their cultural belief for the

treatment of different dermatological problem by

using different mode of preparation as well as

administration of recipe used in the treatments of the

Skin Diseases.It was observed that recipes are

prepared from combination of different parts from

two or more plant species including leaves, seeds and

stem (bark). Preparations mostly preferred are by

grinding, infusion and paste.Several studies have

enumerated the plants used for wound healing and

skin diseases in various parts of the world (Chahet

al., 2006; Harshaet al., 2003).

CONCLUSION AND RECOMMENDATION

Ethnobotany and Ethnopharmacology are

interdisciplinary fields of research that look in

particular at the pragmatic information of indigenous

peoples pertaining to medicinal substances, their

possible health benefits and their health risks

associated with such remedies.This extracted

material belongs to a number of plants of this region

used to cure dermatological problem and probably it

could be of considerable interest in the development

of new drugs.But these plant species remain

unevaluated for pharmacological values.Once its

validated community benefit sharing approach will

be beneficial for tribals. Financially.Although local

efforts to conserve medicinal plant resources are still


inadequate, the long held traditional beliefs of the

population regarding folk medicine has its own

unintentional role in conservation, management and

sustainable utilization.

Table 1. Documented list of plant species along with family, part used, diseases, mode of application and

habitat

S.N.

Species

Name Family Local Name

Part

Used

IUCN

status Disease

Mode of

application Habitat References

1 Abutilon

indicum Malvaceae Petari

Root

and seeds

CL

Scabies, boils

and abscess

Root paste applied on boils and

abscess. Seed oil

used for scabies

Shrub Ghoshet al.,

2013

2 Achyranthes

bidentata Amaranthaceae Chorkanta

Roots and

leaves

CL Boils and acne

Applied root-paste and leaf juice on

affected area

Herb Ghoshet al.,2013

3 Aloe vera Liliaceae Ghritkumari Leaves CL

Rough skin Fresh leaf juice

smear on skin Herb Ghosh., 2008

4 Alstoniascho

laris Apocynaceae Chhatim Leaves

LC Skin disease

Crushed leaves applied on

affected area.

Tree Sahaet al., 2013

5 Andrographi

s paniculata Acanthaceae Kalmegh

Whole

plant

CL Boils

Leaf paste cure

boils. Herb

Rahaman et al.,

2015

6 Artocarpush

eterophyllus Moraceae Kathal Leaves

CL

Boil and skin

diseases.

Leaf used in boil, wound and skin

diseases.

Tree Ghosh ., 2008;

Bose.,2011

7 Azadirachta

indica. Meliaceae Nim Leaves

LC

Boils and skin

disorders

Leaf-paste applied

on affected area Tree

Ghoshet al.,

2013;

Sinhababuet al., 2013;

8 Bidenspilosa Asteraceae Murti Whole plant

CL Skin disease

and check

bleeding

Whole plant paste used in treatments.

Herb Sahaet al., 2013

9 Brassica campestris

Brassicaceae White sarisha

Seeds

CL

Acne and alopecia

Seeds of white sarisha and til (1:1

ratio) are made

into paste and externally applied

on head in

alopecia and face for acne

Herb Ghosh ., 2008

10 Buddleja asiatica

Buddlejaceae Gorumara Leaves LC

Skin disease Leaf juice used in skin complaints

Shrub Sahaet al., 2013

11 Buteamonos

perma Fabaceae Palash Leaves

LC Boils,

pimples, skin diseases

Leaf-paste are

used for the treatment

Tree Ghoshet al.,

2013

12 Caesalpinia

crista

Caesalpiniacea

e Karanj Seed

CL Alopecia,

boils and wounds

Seed oil used in

affected area. Tree Ghosh ., 2008

13 Calotropisgi

gantea Asclepiadaceae Akana

Leaves and

latex

CL

Sores and

skin disease

Leaves and latex is directly applied on

affected area


14 Sennaalata Fabaceae Chakora Leaves

LC

Skin disease

Leaf pest is used

to treat skin disease.

Tree Bose et al.,2015

15 Cassia

fistula

Caesalpiniacea

e

Bandar lathi,

Amaltus Root

LC

Skin disease Root pastes are used for skin

disease

Tree Sahaet al., 2013; Sinhababuet al.,

2013

16 Clerodendrumviscosum

Verbenaceae Ghentu

Root

and

stem

CL

Skin disease

Leaf paste is used

against skin

disease

Shrub Bose et al.,2015

17 Colebrookea

oppositifolia Lamiaceae Dhursuli Leaves

CL Skin infection

Leaves and root extract used in

skin infection



18 Curcuma

longa Zingiberaceae Halud

Rhizom

e

CL

Skin diseases

and boil

Rhizome paste applied to treat

skin diseases

Herb

Bose et

al.,2015;

Rahaman et al., 2015

19 Daturametel Solanaceae Datura Leaves

CL

Boils and

abscess

Leaf paste are

warmed and

applied on affected area

Herb Ghosh.,2008

20 Ecliptaprost

rata Asteraceae Keshute

Whole

plant

LC

Skin diseases

Whole plant

extraction used for skin diseases

Herb

Sahaet al., 2013;

Bose et

al.,2015; Sinhababuet al.,

2013;

21 Elephantopu

sscaber Asteraceae Mejurjhuti

Whole

plant

CL

Boil

Half-burnt plant is made into powder

and mixed with

coconut oil and applied on the

boil.

Herb Rahaman et al.,

2015

22 Eleusinecor

acana Poaceae Marwa Grains

LC Small pox

Grains are used for

treatment Cereal Sahaet al., 2013

23 Entadarheed

ii Fabaceae Gila Seeds

CL Astringent

Seeds used in

treatment Herb Sahaet al., 2013

24 Equisetum

debile Equisetaceae Ashalj

Whole

plant

LC

Astringent

Aerial parts of

plant used as astringent

Creeper Sahaet al., 2013

25 Euphorbia pulcherrima

Euphorbiaceae Lalpata

Leaves

and

flowers

LC

Skin disease

Leaves and

flowers used for

treatment


26 Evolvulusalsinoides

Convolvulaceae

Shankhyapuspi

Whole plant

CL

Leucoderma

Whole plant

extraction used to

treat leucoderma.

Herb Sinhababuet al., 2013

27 Ficusreligiosa

Moraceae Aswatha Bark

CL Skin disease

and

leucoderma

Bark is used as antiseptic and

astringent. Bark

used in leucoderma.

Tree Sinhababuet al., 2013

28 Glycosmisarborea

Rutaceae Ashshewra Root CL

Skin diseases Root powder used for treatment


29 Gynocardia

odorata Achariaceae Chalmogra

Fruits and

seeds

CL Skin diseases

Fruits and seeds

used for treatment Tree Sahaet al., 2013

30 Hedyotissca

ndens Rubiaceae Dhupjhora Root

CL

Boils

Root extract

applied on affected area

Climber Sahaet al., 2013

31 Hemidesmusindicus

Asclepiadacaea Anantmul Root CL

Miliariarubra Root juice rubbed on the body.

Herb Ghosh.,2008

32 Hibiscus rosa-sinesis

Malvaceae Jaba Leaves

CL

Boils and skin diseases

Leaves used to

treat mild burns, boils and skin

diseases.

Shrub

Ghoshet al.,

2013; Bose et al.,2015

33 Holarrhena

pubescens Apocynaceae Kurchi Bark

LC Skin eruption

Bark used to treat skin eruption,

irritation.

Tree Sahaet al., 2013;

34 Jatrophacurcas

Euphorbiaceae Bherenda

Fresh

latex and

seed

EN

Skin diseases

Seeds and smeared

latex are used for

treatment

Shrub Ghosh.,2008

35 Leucasplukenetii

Labiatae Parbolaphang

Leaves

and flowers

CL

Chronic skin eruptions

Leaves and

flowers used to treat chronic skin

eruptions

Herb Bose.,2011

36 Lippia alba Verbenaceae YuetoryGac

h Leaves

CL Skin diseases

Leaves are used against skin

disease.

Herb Bose et al.,2015


37 Madhuca indica

Sapotaceae Mahua Seed CL

skin diseases Barks are used Tree Sinhababuet al., 2013

38 Mallotusphil

ippensis Euphorbiaceae Sindure

Leaves and

fruits

CL Skin diseases

Leaves and fruit are used for

treatment

Tree Sahaet al.,2013

39

Melastomam

alabathricu

m

Melastomataceae

Futki Leaves

CL

Boils and skin trouble

Leaf paste used

against boils and

skin trouble.

Tree

Bose et

al.,2015; Sahaet

al., 2013

40 Pongamispinnata

Fabaceae Karajdare Seeds

LC

Boil, heel

crack and

itching

Seed oil is applied

for itching and boil on affected

area, seed oil is

warmed and massaged on the

heel crack

Tree Rahaman et al.,2015

41 Mimosa pudica

Mimosaceae Swetlajjabati Leaves,

LC Inflammation,

leucoderma

and small pox

Applied and drink juice of leaf

Herb Ghosh.,2008;

Sahaet al., 2013

42 Morusaustra

lis Moraceae . Leaves

CL Burning

sensation

Paste of plant part

are used for treatment


43 Ocimum tenuiflorum

Lamiaceae Tulsi

Leaves,

seeds and

roots

CL

Skin disease

Paste and extract

of plant part used

for treatment


44 Oroxylum indicum

Bignoniaceae Sona

Fruits,

seed and

bark

CL Leucoderma

and

inflammation

Paste of hydrated

fruits or seed or

bark applied


45 Oxalis

corniculata Oxalidaceae Amarul

Whole

plant

CL

Skin disease

Whole plant extraction used as

antiseptic agent

and skin disease.

Creeper Sahaet al., 2013

46 Paederiafoet

ida Rubiaceae Gondhopata

Leaves and

stem

CL Inflammation Leaves used Herb Sahaet al., 2013

47 Peperomiap

ellucida Piperaceae Luchipata

Whole

plant

CL Boils

Whole plant paste

used against boils Herb Bose et al.,2015

48

Phlogacanth

usthyrsifloru

s

Acanthaceae Rambhang Leaves

CL

Astringent Leaves extract and its paste


49 Phoenix

sylvestris Arecaceae Khajuur Seed

CL

Inflammation

Seed paste for

inflammation and wounds.

Tree Sinhababuet al.,

2013

50 Portulacaol

eracea Portulacaceae Nona Sak Leaves

LC Inflammation

Leaf extraction used in

inflammation

Herb Sinhababuet al.,

2013

51 Psidiumguaj

ava Myrtaceae Peyara Leaves

LC Skin diseases

Leaf paste applied

on affected area. Tree Sahaet al., 2013;

52 Pterocarpus

marsupium Papilionaceae Murga Leaves

NT Skin diseases

Leaf juice is useful

for skin diseases. Tree

Sinhababuet al.,

2013

53 Rhus chinensis

Anacardiaceae Bhalay Fruits LC Swelling and

wounds Fruits are used for treatment


54 Ricinus communis

Euphorbiaceae Eradom Bark

CL

Skin inflammation

Bark is used to

treat skin inflammations and

rashes.

Tree

Sahaet al.,

2013;Rahaman et al.,2015

55 Scopariadulcis

Scrophulariaceae

Ban dhane Leaves

CL

Boil

Leaf extraction

used in burning

sensation in pulmonary artery

and veins. Leaf is

used against boils

Herb

Bose et

al.,2015; Sahaet

al., 2013


56 Semecarpus

anacardium Anacardiaceae Bhallataka

Bark

and fruits

CL Skin disease

and inflamation

Bark and fruits are

used for the treatment.


57 Sesamum

indicum Pedaliaceae Til Seeds

CL

Acne

Seed of both til and white sarisha

(1:1) crushed and

applied on acne, til along with white

mustard seeds are

also applied

Herb

Ghosh.,2008;

Ghoshet al., 2013

58 Shorearobus

ta

Dipterocarpace

ae Sal Leaves

LC Astringent

Leaves used as

astringent Tree Sahaet al., 2013

59 Sidaacuta Malvaceae Sweat barela,

Leaves

and

roots

CL

Boil Leaf prevents boils


60 Solanumamericanum

Solanaceae Kalabegun Whole plant

CL Skin diseases and wounds

The whole plant

and tender shoot

is useful


61 Solanumver

ginianum Solanaceae Gorupbegun Root

CL

Small pox

Root paste dry tablet act as

antidote in small

pox

Herb Ghosh.,2008

62 Sonchusaspe

r Asteraceae

Whole

plant

CL

Boil

Whole plant

extract used to

treat wounds and boils.

Herb Bose et al.,2015

63 Stephania

japonica

Menispermace

ae Akundi

Rhizom

e

CL Skin diseases

Rhizome used as

astringent Vine Bose., 2011

64 Terminalia arjuna

Combretaceae Arjun Bark

CL

Skin diseases

and

leucoderma

Bark of young

stem paste is applied externally

in skin diseases.

Tree

Ghoshet al.,

2013; Sinhababuet al.,

2013

65 Terminalia

bellirica Combretaceae Bahera Seed

CL Skin diseases

and leucoderma

Seed oil is used

for skin disease and leucoderma

Tree Sinhababuet al.,

2013

66 Terminalia

chebula Combretaceae Haritaki Fruit

CL Skin diseases

Fruits used as

astringent Tree Sahaet al., 2013

67 Thysanolaena maxima

Poaceae Jharu Stem and root

CL Boils Paste used in boils Grass Sahaet al., 2013

68 Tinosporaco

rdifolia

Menispermace

ae Guduchi Leaves

CL Skin disease

Leaf paste applied

on affected area. Herb Sahaet al., 2013

69 Toonaciliata Meliaceae Toon Bark LC

Astringent Bark used as

astringent. Tree Sahaet al.,2013

70 Trichosanth

escordata Cucurbitaceae Vitechhara

Young

twig

CL

Skin diseases

The young twig is

used in the treatment


71 Trichosanth

esdioica Cucurbitaceae Patol Fruit

CL

Chicken pox

Juice extracted

from the roasted fruits is used as oil

to the chicken pox

scar.

Climber Ghosh.,2003

72 Vitexnegund

o Verbenaceae Nishinda Leaves

LC Inflammation

Leaf juice is useful

for inflammation Shrub Sahaet al., 2013

73 Woodfordiaf

ruticosa Lythraceae Dhai

Flowers

and bark

LC

Boils

Flowers and bark

paste used for the treatment


74 Ziziphusmauritiana

Rhamnaceae Kul Leaves LC

Boils Leaf paste applied on affected area


IUCN Category:EN- Endangered; LC- Least Concerned; NT- Near Threatened; CL-Catalogue of Life


Fig 1. Life form of reported flora

Fig 2. Recorded families, their species and No. of genera

Fig 3. Genus with their no. of species

0

5

10

15

20

25

30

35

Tree Herb Shrub Climber Creeper Cereal Grass Vine

00.5

11.5

22.5

33.5

44.5

5

Aca

nth

acea

e

An

acar

dia

ceae

Asc

lep

iad

acae

a

Bra

ssic

acea

e

Co

nvo

lvu

lace

ae

Equ

iset

acea

e

Lab

iata

e

Lyth

race

ae

Mel

iace

ae

Mo

race

ae

Pap

ilio

nac

eae

Po

acea

e

Ru

bia

ceae

Scro

ph

ula

riac

eae

Zin

gib

erac

eae

No of species

No of genera

00.5

11.5

22.5

33.5

Ab

uti

lon

An

dro

grap

his

Bra

ssic

a

Cal

otr

op

is

Cu

rcu

ma

lon

ga

Eleu

sin

e co

raca

na

Evo

lvu

lus

alsi

no

ides

Hed

yoti

s sc

and

ens

Jatr

op

ha

curc

as

Mo

rus

aust

ralis

Pae

der

ia f

oet

ida

Po

rtu

laca

ole

race

a

Ric

inu

s co

mm

un

is

Sho

rea

rob

ust

a

Step

han

ia ja

po

nic

a

Too

na

cilia

ta

Zizi

ph

us

mau

riti

ana

No. of species


Fig 4. Plant part used of different flora

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EFFECT OF WATER STRESS ON PRE-HARVEST CHARACTERS OF IRANIAN

WHEAT LANDRACES UNDER IRRIGATED, RESTRICTED IRRIGATED AND

RAIN-FED CONDITION

Amandeep Kaur* and Rashpal Singh Sarlach2

1Department of Botany, Punjab Agricultural University, Ludhiana 141004

2 Department of Plant Breeding & Genetics, Punjab Agricultural University, Ludhiana ,141004


Received-02.01.2020, Revised-28.01.2020 Abstract: Water stress is one of the most important abiotic stresses which severely affect plant growth and yield. With a

view to understand the effects of drought stress on pre harvest components of wheat cultivars under field conditions, the

present investigation was carried in the Department of Plant Breeding and Genetics with three replications under

Randomized Block Design. Set of selected Iranian landraces from the preliminary screening experiment with the help of

Polyethylene glycol (6000). Landraces were selected on the basis of vigor index and planted in the field along with

commercial relevant checks in three environments Irrigated, Restricted irrigated and Rain-fed. Data of days to

germination, flowering, maturity, plant height and tillers per meter row length were recorded. On the basis of

performance,IWA 8600796,IWA 8600179, IWA 8606333 and IWA 8606258 considered as water stress tolerant

.Identified landraces can be included in future breeding programmes for the wheat improvement for drought prone areas.

Keywords : Water stress, Iranian wheat landraces , Pre-harvest characters

INTRODUCTION

heat is important cereal crop which contributes

more calories and protein than any other

cereal crop(Abd- EL- Haleem et al., 2009). Abiotic

stresses such as drought, excessive watering, extreme

temperature and salinity affect growth and

development processes in plants.Drought stress is

more challenging than any other abiotic stress.Water

stress leads due to lack of proper moisture which is

necessary for the development of plant (Zhu 2002).In

extreme drought situations wilting point in plants

reached at point which results in desiccation and

ultimately death of the plant. Drought stress affects

the plant almost at all stages like tillering, booting,

anthesis,grain formation and grain filling. During

reproductive stage, drought stress cause 70-80% loss

in yield of crop (Kulkarni et al.,2008).Drought stress

affects the growth of plant from seedling to full

maturity stage which results in reduction of yield

(Bilal et al., 2015).In plant life, most critical and

vulnerable stage to environment stress is the seed

germination.Water stress acts by decreasing the

percentage and rate of germination and seedling

growth (Delachiave and De Pinho 2003). Water

stress is known to increase the mean germination

time in crop plants (Willenborb et al., 2004).Plant

height decreasesd due to reduction in cell division

which is due to loss in turgidity anddehydration of

protoplasm.Tillering is the most important yield

contributing component. Generally, crop stand better

and ultimately greater the yield as greater the number

of tillers. Limited supply of water at booting stage

reduced the formation of tillers in wheat which

ultimately decreased the yield of crop (Ranaet

al.,1999) and Kimurtoet al.,2003). Under irrigated

condition 95% of tillers produced ears as compared

to the stress where only 79% of tillers produced ears

(Karim et al., 2000). The main objective of this work

is to investigate pre-harvest morphological

traitswhich are associated with drought tolerance and

that could be used for yield improvement in wheat

breeding programmes.


In order to evaluate effect of water stress on pre-

harvest characters of wheat cultivars, 27 lines were

selected on the basis of vigor index from preliminary

screening experiment.

Selected Iranian landraces on the basis of minimum reduction of vigor index under stress as compared to

control

Sr.No. Landraces Minimum reduction as compared control

1 PETTERSON ML68-10 302

2 Cltr 15395 100

3 IWA 8600064 399

4 IWA 8600091 473

W

RESEARCH ARTICLE

18 AMANDEEP KAUR AND RASHPAL SINGH SARLACH

5 IWA 8600179 180

6 IWA 8600191 439

7 IWA 8600232 136

8 IWA 8600397 261

9 IWA 8600435 320

10 IWA 8600440 179

11 IWA 8600542 298

12 IWA 8600567 215

13 IWA 8600596 185

14 IWA 8600715 185

15 IWA 8600795 274

16 IWA 8600796 239

17 IWA 8600841 79

18 IWA 8600846 174

19 IWA 8600883 24

20 IWA 8606258 279

21 IWA 8606633 296

22 IWA 8606661 292

23 IWA 8606739 200

24 IWA 8606753 200

25 IWA 8606741 264

26

27

IWA 86067576 IWA

8607572

275

200

These lines showed minimum reduction as compared

to control in all seedling parameters (germination

percentage, coleoptile length, root length, shoot

length, root and shoot fresh and dry weight at 14%

Polyethylene glycol (6000 ) treatment. 27 Iranian

landraces were grown under irrigated, restricted

irrigated and rain-fed conditions.

Control treatment (Irrigated) was well watered

throughout the growing period (five

irrigations).Drought environment was created by

withholding irrigation ( two irrigations) and created

temporary rain shelter from water during rain. The

experiment was carriedout in RBD design with three

treatments with three replications. Sowing was done

in last week of November 2016.Plant height was

measured in centimeters from base of the plant to the

tip of the spike (excluding awns) at the maturity

time. When 50% of the spikes anther has extruded,

date of flowering was recorded for each line for each

plot and number of days were recorded starting from

the date of sowing.Date of maturity was recorded

from each line and number of days were counted

starting from sowing date

Total number of tillers per meter row length was

recorded by using a scale of 1 meter from each line at

maturity recounted starting from sowing date.

RESULTS AND DISCUSSIONS

Analysis of variance for all the morpho-physiological

traits was conducted. The mean square under drought

stress were highly significant for all the characters

under irrigated conditionexcept days to flowering

(Table1), restricted irrigation(Table 2) and rain-fed

conditions (Table 3)viz; days to germination, days to

flowering, days to maturity, plant height and tillers

per meter row length.

Days to germination

In plant life, most critical and vulnerable stage to

environment stress is the seed germination.Water

stress acts by decreasing the percentage and rate of

germination and seedling growth (Delachiave and De

Pinho, 2003). Water stress is known to increase the

mean germination time in crop plants (Willenborb et

al 2004).

IWA 8600796, IWA 8600841, IWA 8600846 and

IWA 8606258 took minimum days to germinate

under restricted irrigated and rain-fed conditions as

compared to irrigated condition (Table 8 and 9).

Days to flowering

Under Irrigated conditions, range of 74.0to 84.0 days

to flowering was observed with a mean of 79.0 days

to flowering (Table 4). Among checks C-591 and C-

273 took minimum days (75.0) while PBW 660 took

maximum (82.0) days to flowering (Table 4). Among


Iranian lines minimum days were taken by Cltr

15395 and IWA 8600179 and (74) days and

maximum by IWA 8600542 (84.0) days (Table 7).

Under restricted-irrigated condition most of lines

flowered in the range of 60.0 to 78.0 days with an

average of days 69.0 (Table 5). Among checks C-591

took minimum 70.0 days to flowering. Maximum

days were taken by Gladius (77.0) days to flowering

(Table 5). In Iranian lines, maximum (78.0) days

were recorded in IWA 8600796 IWA 8606661 IWA

8607576 and IWA 8600883 and minimum days

(60.0) was recorded in IWA 8600091 (Table 8).

Under rain-fed condition most of lines flowered in

the range of 54.0 to 74.0 days with an average of

64.0 days (Table 6). Among checks C-591 took

minimum days (68.0) whereas maximum days (72.0)

by BWL 5233 (Table 6). In Iranian landraces

maximum days (74.0) were taken by IWA 8607576

and minimum by IWA 8600091 (54.0) days (Table

9).These Iranian landraces IWA 8600397, IWA

8600796, IWA 8600883, IWA 860661 and IWA

860674 took minimum days to flowering under

restricted and rain-fed conditions as compared to

irrigated conditions (Table 8 and 9).

Days to maturity

Under irrigated condition, most of lines matured in


137.0 days (Table 4). Among commercial checks

days of maturity was 135.0 to 136.0 with an average

of 135.5 days (Table 4).Under restricted-irrigated

most of lines matured in the range of days 129.0 to

134.0 with an average of 131.5 days (Table 5).

Among commercial checks days of maturity were

130.0 to 134.0 with an average of 132.0 days (Table

5).

Most of lines under rain-fed condition matured in


130.0 days (Table 6). Among checks days of

maturity was 130.0 to 132.0 days with an average of

131.0 days (Table 6).These lines IWA 8600179,

IWA 8600232, IWA 8600841, IWA 8600567 and

IWA 8606633 took minimum days to mature as

compared to irrigated conditions under restricted

irrigated and rain-fed conditions (Table 8 and 9).

Plant height (cm)

In irrigated condition, plant height among Iranian

landraces varied between 90.5 to 106.5 cm with an

average 98.7cm( Table4). Among commercial

relevant checks C-306 had highest (114.5cm) while

Gladius had lowest (100.5cm) plant height (Table4).

Among Iranian lines, IWA 8606741 had maximum

(106.5.5cm) whereas minimum (90.5cm) plant height

was recorded in IWA 8600397 and IWA 8607576

(Table 7).

Under restricted-irrigated plant height varied

between82.2 to102.5cm with an average 92.3cm

(Table 5). Among commercial relevant checks C-306

had highest (112.5cm) while Gladius had lowest

(98.5cm) height (Table 5). Among Iranian lines,

IWA 8600064 had maximum (102.5cm) whereas

minimum (82.2cm) plant height was recorded in Cltr

15395 (Table 8).

Plant height under rain-fed condition varied among

genotypes between 65.5 to 90.5cm with an average

of 78.0 cm (6). Among commercial relevant checks

C-518 had maximum (107.5cm) whereas lowest

height was recorded in Gladius (84.5 cm) (Table 6).

In Iranian lines, IWA 8600084 had highest (90.5 cm)

and IWA 8600191 (65.5cm) had lowest plant height

(Table 9).Khan and Naqvi (2011) reported in wheat

that there was reduction in plant height under water

stress which strengthens our findings. Similar result

was found by (Qadir et al 1999 and Saleem 2003)

and Khan et al (2001) in maize.The reduction in

plant heightdue to loss of turgidity and dehydrationof

protoplasm.

Tillers per meter row length (cm): In irrigated condition, tillers / meter row length

among genotypes showed variation between 60.5 to

98.7 with a mean of 79.6 (Table 4). Among checks

C-306 and C-591 had maximum (108.5) while

Gladius had minimum (100.00) tillers / meter row

length (Table 4.). In Iranian lines, IWA 8600715 had

more (98.7) whereas IWA 8600796 (60.5) had least

number of tillers / meter row length (Table 7).In case

of restricted irrigated tillers/meter row length among

genotypes ranged between 50.0 to 89.0 with a mean

of 69.5 (Table 5). Among checks C-306 had

maximum (90.4) whereas BWL 5233 had minimum

(70.7) tillers per meter row length (Table 5). Among

Iranian lines IWA 8606633 had maximum (89.0)

followed by IWA 8600542 (88.7) whereas IWA

8600841 (50.0) had minimum tillers/meter row

length (Table 8).

Tillers per meter rowlength among the genotypes

varied between 32.0 to73.0 with an average of 52.5

under rain-fed condition (Tale 6). In commercial

relevant checks, PBW 175 had maximum (81.4)

while C-518 had minimum (59.8) tillers/ meter row

length (Table 6). In Iranian lines 8600841 had lowest

number of tillers (32.0) whereas maximum was

recorded in IWA 8606258 (73.0) (Table 9).Number

of tillers were more affected under restricted and

rain-fed conditions as compared to irrigated

condition.Similar result were found by Quadiret al

(1999) and Kabiret al (2009). Ranaet al (1999) and

Kimutroet al (2003) found that water stress at

tillering or at booting stage significantly affected the

formation of tillers in wheat.

Five Iranian lines PETTERSON ML 68-10 IWA

8600542, IWA 8600883, IWA 8606258 and IWA

8606333 were selected on the basis of performance

under irrigated, restricted irrigated and rain-fed

conditions.


Table 1. Analysis of variance for morpho-physiological traits in 27 Iranian lines along with 8 checks under

Irrigated conditions during 2016-17

Mean Square of Characters

Source of variation DF DTG DTF DTM PH TPMRL

Block 1 0.357 0.351 0.357 0.241 114.2

Treatment 34 0.787* 2.294 1.750* 34.11* 480.36*

Error 34 0.121 1.308 0.382 13.85 139.15

Total 69


Restricted irrigated conditions during 2016-17


Source of variation Df DTG DTF DTM PH TPMRL

Block 1 0.12 0.9 0.39 5.24 0.26

Treatment 34 1.08* 2.80* 2.60* 68.59* 128.38*

Error 34 0.24 0.7 0.32 26.46 64.729

Total 69


Rain-fed conditions during 2016-17


Source of variation Df DTG DTF DTM PH TPMRL

Block 1 0.55 0.69 0.32 1.38 78.02

Treatment 34 0.41* 3.55* 1.20* 17.52* 89.84*

Error 34 0.14 1.05 0.55 6.034 24.56

Total 69

Abbreviations: DF –Degree of freedom, DTG- Days to germination, DTF- Days to flowering,

DTM- Days to maturity, TPMRL- Tillers per meter row length and * Significance at 5 %

Table 4. Ranges and mean values of morpho-physiological and yield components traits of Iranian lines and

checks under Irrigated conditions

Characters

DTG DTF DTM PH TPMRL

Landraces

Min 15 74 136 90.5 60.5

Max 18 84 138 106.5 98.7

Mean 16.5 79 131.5 98.7 79.6

Mean value of checks

Gladius 16 80 135 100.5 100

BWL 5233 16 78 135 112.5 105

C-306 16 77 135 114.5 108.5

PBW 660 15 82 136 113 105

C-518 16 78 135 113.6 107

C-591 16 75 135 112.5 108.5

C-273 15 75 136 110.5 100.4

PBW 175 15 79 136 111.4 104

Abbreviations: DF –Degree of freedom, DTG- Days to germination, DTF- Days to flowering, DTM- Days to

maturity and TPMRL- Tillers per meter row length


checks under Restricted irrigated conditions

Characters


Landraces Min 15 60 129 82.2 50

Max 20 78 134 102.5 89


Mean 17.5 69 131.5 92.3 69.5

Mean value of

checks

Gladius 17 77 133 98.5 73.75

BWL 5233 17 74 132 110.5 70.75

C-306 18 72 130 112.5 90.4

PBW 660 18 76 134 111.5 85.2

C-518 17 72 132 110.5 77

C-591 16 70 134 109.5 77

C-273 17 72 130 108.5 75.7

PBW 175 16 74 133 107.5 85.4




checks under rain-fed conditions

Characters


Landraces

Min 17 54 128 65.5 32

Max 20 74 132 90.5 73

Mean 18.5 64 130 78 52.5

Mean value of

checks

Gladius 17 70 130 84.5 71

BWL 5233 17 72 131 100.5 71

C-306 19 69 130 104.5 74.2

PBW 660 18 70 132 107.5 72

C-518 17 70 132 107.5 59.8

C-591 18 68 131 104.5 63.4

C-273 17 70 130 105.5 71

PBW 175 18 70 131 100.5 81.4



Table 7. Mean values of selected Iranian wheat landraces with 8 checks under Irrigated conditions

Sr.No Germplasm DTG DTF DTM PH TPMRL

1 PETTERSON ML68-10 16.0 78.0 136 98.1 87.7

2 Cltr 15395 16.0 74.0 136.5 107.5 81.0

3 IWA 8600064 17.0 81.0 138 104.5 65.0

4 IWA 8600091 15.00 75.0 138 100.5 80.5

5 IWA 8600179 16.0 74.0 137.5 102.5 72.5

6 IWA 8600191 16.0 76.0 137 99.5 68.5

7 IWA 8600232 15.0 80.0 136.5 100.5 93.5

8 IWA 8600397 16.0 79.0 135.5 90.5 85.2

9 IWA 8600435 16.0 75.0 135 101.5 95.0

10 IWA 8600440 18.0 83.0 135.5 105.5 75.0

11 IWA 8600542 17.0 84.0 136 100.5 90.0

12 IWA 8600567 17.0 76.5 137 106.5 95.5

13 IWA 8600596 17.0 77.5 137 104.5 85.5

14 IWA 8600715 16.0 79.5 137.5 100.8 98.7

15 IWA 8600795 15.0 81.5 138 90.5 75.5

16 IWA 8600796 15.0 81.5 135.5 101.5 60.5

17 IWA 8600841 16.0 78.0 137 106.5 94.5

18 IWA 8600846 16.0 76.5 137 104 92.5

19 IWA 8600883 17.0 83.0 135.5 100.5 92.5

20 IWA 8606258 16.0 79.0 136.0 102.5 89.5



21 IWA 8606633 17.0 83.0 137.0 101.5 85.5

22 IWA 8606661 15.0 81.0 137.0 100.0 84.5

23 IWA 8606739 16.0 82.0 136.5 98.5 86.5

24 IWA 8606753 15.0 79.5 136.0 104.5 72.5

25 IWA 8606741 16.0 79.5 137.5 106.5 79.0

26 IWA 8607572 15.0 81.0 138.0 100.5 85.5

27 IWA 8607576 16.0 82.0 137.0 90.5 90.4

28 Gladius 16.0 80.0 135.0 100.5 100.0

29 Bwl 5233 16.0 78.0 135.0 112.5 105.0

30 C-306 16.0 77.0 135.0 114.5 108.5

31 PBW660 15.0 82.0 136.0 113 105.0

32 C-518 16.0 78.0 135.0 113.6 107.0

33 C-591 16.0 75.0 135.0 112.5 108.5

34 C- 273 15.0 75.0 136.0 110.5 100.4

35 PBW175 15.0 79.0 136.0 111.4 104

CD (5%) 0.79 NS 1.25 7.56 23.9

Table 8. Mean values of selected Iranian wheat landraces with 8 checks under Restricted irrigated conditions


1 PETTERSON

ML68-10

15 74 130 88 71

2 Cltr 15395 18 68 132 82.2 60.4

3 IWA 8600064 18 70 130 102.5 61.4

4 IWA 8600091 17 60 134 86.2 63.4

5 IWA 8600179 18 70 134 100 73

6 IWA 8600191 16 68 129 87.8 54

7 IWA 8600232 17 68 132 88.6 68

8 IWA 8600397 19 74 130 83.9 82.25

9 IWA 8600435 19 68 132 85.1 80.5

10 IWA 8600440 18 70 130 85.8 60

11 IWA 8600542 18 70 132 85.5 88.75

12 IWA 8600567 17 68 133 100 63.75

13 IWA 8600596 17 68 134 84.7 76.5

14 IWA 8600715 16 70 130 90.5 82.2

15 IWA 8600795 17 74 133 86.5 78.4

16 IWA 8600796 17 78 131 94.5 51.25

17 IWA 8600841 18 70 133 84.7 50

18 IWA 8600846 16 69 132 78.8 66.4

19 IWA 8600883 18 78 130 90.5 82.75

20 IWA 8606258 17 68 132 98.5 88.2

21 IWA 8606633 18 74 134 98 89

22 IWA 8606661 20 78 133 84.5 70.5

23 IWA 8606739 18 68 132 87.8 63.25

24 IWA 8606753 18 74 130 98.5 64.25

25 IWA 8606741 18 74 133 100 82.25

26 IWA 8607572 17 77 133 98.5 83.25

27 IWA 8607576 18 78 135 80.5 84.5

28 Gladius 17 77 133 98.5 73.75


29 Bwl 5233 17 74 132 110.5 70.75

30 C-306 18 72 130 112.5 90.4

31 PBW660 18 76 134 111.5 85.2

32 C-518 17 72 132 110.5 77

33 C-591 16 70 134 109.5 77

34 C- 273 17 72 130 108.5 75.7

35 PBW175 16 74 133 107.5 85.4

CD(5%) 1.08 1.71 1.15.0 10.4 16.3

Table 9. Mean values of selected Iranian wheat landraces with 8 checks under Rain-fed conditions.

Sr. No. Germplasm DTG DTF DTM PH TPMRL

1 PETTERSONML68-

10

17 68 128 72.5 70.5

2 Cltr 15395 20 64 129 78.7 50

3 IWA 8600064 20 64 132 90.5 47

4 IWA 8600091 19 54 130 84 44.5

5 IWA 8600179 20 64 130 90 50

6 IWA 8600191 21 60 128 65.5 51

7 IWA 8600232 19 64 130 70.5 49

8 IWA 8600397 20 70 129 68.5 49

9 IWA 8600435 19 60 129 71.2 55

10 IWA 8600440 20 68 129 75 42

11 IWA 8600542 18 55 130 68.5 70.6

12 IWA 8600567 19 60 130 90 58

13 IWA 8600596 20 62 132 78 49

14 IWA 8600715 19 68 128 87.8 45

15 IWA 8600795 18 68 130 74.5 50

16 IWA 8600796 17 70 129 84.5 49

17 IWA 8600841 18 68 130 82.5 32

18 IWA 8600846 18 55 129 70.5 64

19 IWA 8600883 20 70 128 87.8 70.5

20 IWA 8606258 18 64 128 89.5 73

21 IWA 8606633 19 68 132 85 71.5

22 IWA 8606661 20 70 130 82.5 49

23 IWA 8606739 21 64 129 80.5 51

24 IWA 8606753 20 68 128 87.8 42

25 IWA 8606741 19 70 130 90.5 58

26 IWA 8607572 19 70 129 84.5 50

27 IWA 8607576 20 74 130 68.5 70

28 Gladius 17 70 130 84.5 71

29 Bwl 5233 17 72 131 100.5 71

30 C-306 19 69 130 104.5 74.2

31 PBW660 18 70 132 107.5 72

32 C-518 17 70 132 107.5 59.8

33 C-591 18 68 131 104.5 63.4


34 C- 273 17 70 130 105.5 71

35 PBW175 18 70 131 100.5 81.4

CD(5%) 0.77 2.08 1.51 4.99 10.1

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Rana, V., Sharma, S.C. and Sethi, G.S. (1999).

Comparative estimates of genetic variation in wheat

under normal and drought conditions. Journal of Hill

Research,12: 92-94.

Zhu, J., Kaeppler, S.M. and Lynch, J.P. (2005).

Mapping of QTLs for lateral root branching and

length in maize (Zea mays L.) under differential

phosphorus supply. Theoretical and

AppliedGenetics,111: 688-95.



RELATIONSHIP BETWEEN INDEPENDENT AND DEPENDENT VARIABLES OF

RECOMMENDED MAIZE PRODUCTION TECHNOLOGY

P.K. Netam*, Basanti Netam and A. Qureshi

1Department of Agricultural Extension CARS,Kanker, IGKV, Raipur, Chhattisgarh 2Department of Senior Agriculture Development Officer, Dhamtari,Chhattisgarh

3Department of Agronomy CARS,Kanker, IGKV, Raipur, Chhattisgarh


Received-04.01.2020, Revised-26.01.2020 Abstracts: This investigation was carried out in three district of Bastar plateau of Chhattisgarh State to assess the

relationship between independent and dependent variables of recommended maize production technology. 270 farmers were

considering as respondents for this study. Respondents were interviewed through personal interview. Collected data were

analyzed with the help of suitable statistical methods. The analysis of the results showed that relationship between

independent and dependent variables of recommended maize production technology, Farming experience, family size, land

size, occupation, annual income, irrigation facility, source of information, contact with extension personnel, participation in

extension activities, overall marketing, opinion about maize production, risk orientation, scientific orientation and

knowledge had significant correlation with adoption of maize, whereas, farming experience, family size, occupation, annual

income, irrigation facility, overall marketing, opinion about maize production, risk orientation, scientific orientation,

knowledge and land size had significant correlation with productivity of maize.

Keywords: Association, Adoption, Productivity, Zea mays

INTRODUCTION

aize (Zea mays L.) is one of the most

important cereal crops in the world and has the

highest production among all the cereals. It is a

miracle crop, it has very high yield potential, there is

no cereal on the earth which has so immense

potentiality and that is why it is called „queen of

cereal‟. Besides, maize has many types like normal

yellow, white grain, sweet corn, baby corn, pop corn,

waxy corn, high amylase corn, high oil corn, quality

protein maize, etc. Maize is the most important crop

in the world after wheat and rice (Verheys,Undated).

It is an important staple food in many countries and

is also used as animal feed and many industrial

applications. Maize is 3rd

major crop in India after

rice and wheat (Cox, R., 1956 & Reddy et. al. 2013).

Maize is important cereal crop which provides food,

feed, fodder and serves as a source of basic raw

material for a number of industrial products viz,

starch, protein, oil, food sweeteners, alcoholic

beverages, cosmetics, bio-fuel etc, it is cultivated

over 8.12 million hectare area with an annual

production of 19.77 million tones and an average

productivity of 2,435 kg ha-1 (Langade et. al. 2013).

Maize is the third most important food grain in India

after wheat and rice. In India, about 28% of maize

produced is used for food purpose, 11% as livestock

feed, 48% as poultry feed, 12% in wet milling

industry (for example starch and oil production) and

1% as seed (AICRP on Maize, 2007). Maize crop in

the state has an area of 123430 ha with the

production 254134 MT (C.G. Agriculture Statistic

Report 2014).The area and production of Maize crop

in Kanker district was 11511 ha and 25705 MT

respectively, area of maize crop in Kondagaon

district is 13586 ha with production of 31831 MT

while the coverage of maize in Bastar district is 9560

ha with the production of 22398 (C.G. Ag. statistic

Report 2014). The dependent and independent

variables has been studied with standard parameter

and their relationship with each other has been

investigation and presented. The present study was

undertaken with specific objectives to ascertain the

relationship between independent and dependent

variables about recommended maize production

technology among the respondents of Bastar plateau

of Chhattisgarh.


The present study was carried out in Bastar plateau

of Chhattisgarh State. Three districts in the zone i.e.

Kanker, Kondagaon and Bastar were undertaken for

the study. Two blocks from each of the selected

district Block Antagarh and Koylibeda in Kanker

District, Keshkal and Baderajpur in Kondagaon,

Bastar and Bakawand in Bastar District. Each

selected block 3 villages viz. Irrabodi, Amagaon,

Godri, in Antagarh Block, Chotekapsi,

Kodosalhebhat, Manegaon, in Koylibeda Block,

Cherbeda, Toraibeda, Amoda in Keshkal Block,

Baderajpur, Toraipara, Khargaon(Manduki) in

Baderajpur Block, Ikchapur, Bagmohlai,

Dubeumargaon in Bastar Block, Belputi, Khotlapal

and Mangnar in Bakawand Block were selected and

from each selected village, 15 farmers were selected

randomly. In this way total two hundred seventy

respondents were selected to response as per the

interview schedule designed for the study. Collected

M

RESEARCH ARTICLE


26 P.K. NETAM, BASANTI NETAM AND A. QURESHI

data were analyzed by the help of various statistical

tools i.e. frequency, percentage, mean, standard

deviation, correlation and regression, etc.

The dependent and independent variables has been

studied with standard parameter and their

relationship with each other has been investigation

and presented.

(i) Mean Mean of sample was calculated by using the

following formula:

∑x

X = ……………………

N

Where,

X = Mean of the variables

∑x = Sum of scores (observation) of variables

N= Total number of respondents

(ii) Standard deviation Standard deviation was calculated by using following

formula:

x2 (x)

2

SD =

n n

Where,

S.D. = Standard deviation

x = Deviation obtained from mean

n= Number of observations

Pearson’s coefficient of correlation

This technique was used to find out the relationship

between independent and dependent variables with

the help of SPSS technique through coefficient of

correlation which is follows:

N xy – xy

r =

N x2 – (x)

2 . Ny

2 - (y)

2

Where,

r = Correlation coefficient

x = Score of independent variable

y = Score of dependent variable

N = Number of observation

Multiple regressions

For the present study SPSS technique was

used to know the partial and complete influence of

independent variables through linear model of

regression equation which is as follows:

Y1 = a + b

1x

1 + b

2x

2 + ………. + bnxn

Where,

Y1 = Dependent variable

x1…xn = Independent variables

a = Constant value

b1…bn = The regression

RESULTS AND DISCUSSION

The result and discussion of the present study have

been summarized under the following heads:

Correlation analysis of independent variable with

the adoption and productivity of maize

Table 1. Correlation analysis of independent variable with the adoption and productivity of maize

S. No. Independent variables Coefficient of Correlation “r” Values

Adoption Productivity

X 1 Education 0.078 0.058

X 2 Family size 0.277** 0.157**

X 3 Farming experience 0.181** 0.202**

X 4 Social participation 0.055 0.035

X 5 Land size 0.191** 0.153*

X 6 Occupation 0.414** 0.211**

X 7 Annual income 0.369** 0.304**

X 8 Irrigation facility 0.543** 0.618**

X 9 Source of information 0.244** 0.115

X 10 Contact with extension personnel 0.446** 0.105

X 11 Participation in extension activities 0.251** -0.011

X 12 Overall marketing 0.371** 0.200**

X 13 Opinion about maize production 0.455** 0.404**

X 14 Risk orientation 0.379** 0.291**

X 15 Scientific orientation 0.600** 0.427**

X 16 Knowledge 0.621** 0.556**

** Significant at 0.01 level of probability, * Significant at 0.05 level of probability


Correlation coefficient between the selected

characteristics of the respondents with adoption and

productivity of maize was worked out and the values

of correlation coefficient are presented in Table No.

1. It is cleared from the data that out of all selected

16 characteristics, the fourteen variables viz family

size, farming experience, land size, occupation,

annual income, irrigation facility, source of

information, contact with extension personnel,

participation in extension activities, overall

marketing, opinion about maize production, risk

orientation, scientific orientation and knowledge had

found to be positive and highly significant

correlation was found with adoption of maize at 0.01

level of probability. Whereas, two variable, viz.

education and social participation had no statistically

significant correlation with adoption of maize

production technique. Correlation coefficient

between the selected characteristics of the

respondents with productivity of maize, eleventh

variable viz. family size, farming experience,

occupation, annual income, irrigation facility, overall



found to be positive and highly significant

correlation was found with productivity of maize at

0.01 level of probability and one variable viz. land

size was found to be positively and significantly

correlated with the productivity of maize at 0.05

level of probability. Whereas, five variable viz.

education, social participation, source of information,

contact with extension personnel and participation in

extension activities had no significant correlation

with productivity of maize.

Multiple regression analysis of independent

variables with adoption and productivity of maize

production technique

The results of multiple regression analysis of selected

characteristics with adoption and productivity of

maize are presented in Table No. 2 Out of 16

independent variables, three variable viz. irrigation

facility, scientific orientation and knowledge

contributed positively and significantly related

towards adoption of maize production technique at

0.01 level of probability, whereas, two variables viz.

contact with extension personnel and opinion about

maize production contributed significantly related

towards adoption of maize production technique at

0.05 level of probability. Variable i.e. education,

family size, farming experience, social participation,

land size, occupation, annual income, source of

information, participation in extension activities,

overall marketing and risk orientation had no

significant related in adoption of maize production

technique.

The results of multiple regression analysis of selected

characteristics with productivity of maize, out of 16

independents variables, four variable viz. irrigation

facilities, overall marketing, opinion about maize

production and knowledge contributed positively and

significantly towards productivity of maize at 0.01

level of probability. Variable scientific orientation

contributed significantly towards productivity of

maize at 0.05 level of probability. Whereas, eleventh

variables viz. education, family size, farming

experience, social participation, land size,

occupation, annual income, source of information,

contact with extension personnel, participation in

extension activities and risk orientation had no

significant contribution in productivity of maize.

Table 2. Multiple regression analysis of independent variables with adoption and productivity of maize

S. No. Independent variable Regression analysis

Adoption Productivity

“t” value “b” value “t” value “b” value

X 1 Education -2.002 -0.221 -0.746 -0.348

X 2 Family size 1.126 0.363 -1.702 -2.314

X 3 Farming experience -1.109 -0.274 0.551 0.574

X 4 Social participation -1.290 -0.233 -1.645 -1.252

X 5 Land size 0.151 0.045 1.931 2.439

X 6 Occupation 1.203 0.142 -2.313 -1.152

X 7 Annual income -0.741 -0.268 0.785 1.200

X 8 Irrigation facility 5.984** 0.856 8.984** 5.414

X 9 Source of information -2.054 -0.156 -1.419 -0.456

X 10 Contact with extension personnel 2.047* 0.234 -3.221 -1.556

X 11 Participation in extension activities -0.746 -0.098 -4.620 -2.580

X 12 Overall marketing 1.557 0.064 2.694** 0.470

X 13 Opinion about maize production 2.045* 0.098 3.258** 0.658

X 14 Risk orientation 0.609 0.048 -0.718 -0.238

X 15 Scientific orientation 2.756** 0.229 2.241* 0.784

X 16 Knowledge 2.892** 0.148 4.948** 1.071

** Significant at 0.01 level of probability (2.594) R2 = 0.559 R

2 = 0.590

* Significant at 0.05 level of probability (1.969)


Model wise multiple regression analysis of

independents variables with adoption of maize

production technique.

Different models were tested for findings their

predicting ability and determine the best predictors

for adoption of maize production technique of

respondents (Table 3). Every time one or more

variables were dropped to find out the best model

with

Table 3. Model wise multiple regression analysis of selected independent variables with adoption of maize

production technique

Model No. Variables included in the models R2 ‘F’ value

M1 X16 0.386 171.682** at 1,273 df

M2 X16,X15 0.451 111.600** at 1,272 df

M3 X16,X15,X8 0.517 96.641** at 1,271df

M4 X16,X15, X8, X10 0.526 74.897** at 1,270 df

M5 X16,X15,X8,X10,X1 0.534 61.616** at 1,269 df

** Significant at 0.01 per cent level of probability

Note: X1- Education, X8- Irrigation facility, X10-

Contact with extension personnel, X15- Scientific

orientation, X16- Knowledge.

lowest number of variables explaining highest

adoption. Model – I revealed that 38 percent

adoption can be explained by considered 16

independent variables and one depend variable

(adoption) which have significant „F‟ value at 1

percent level. Model II, III, IV and V explained

about contribution of adoption as 45, 51, 52 and 53

percent, respectively.

Model wise multiple regression analysis of

independents variables with productivity of maize

Different models were tested for findings their

predicting ability and to determine the best predictors

for productivity of maize of respondents (Table 4).

Every time one or more variables were dropped to

find out the best model with lowest number of

variables explaining highest productivity. Model–I

revealed that 38 percent productivity of maize can be

explained by considering 16 independent variable

and one dependent variable (productivity of maize)

which have significant „F‟ value at 1 percent level.

Model II, III, IV, V and VI explained about

contribution of productivity of maize as 45, 48, 52,

53 and 55 percent respectively.

Table 4. Model wise multiple regression analysis of selected independent variables with productivity of maize

Model No. Variables included in the models R2 ‘F’ value

M1 X8 0.382 168.700** at 1,273 df

M2 X8,X16 0.455 113.366** at 1,272 df

M3 X8,X16,X11 0.489 86.415** at 1,271df

M4 X8,X16, X11, X13 0.523 73.901** at 1,270 df

M5 X8,X16,X11,X13,X10 0.539 62.909** at 1,269 df

M6 X8,X16,X11,X13,X10X12 0.553 55.242** at 1,268 df

** Significant at 0.01 per cent level of probability

Note: X8- Irrigation facility, X10- Contact with

extension personnel, X11- Participation in extension

activities, X12 - Overall marketing, X13- Opinion

about maize production, X16- Knowledge.

CONCLUSION

From the above research findings it can be concluded

that farming experience, family size, land size,

occupation, annual income, irrigation facility, source

of information, contact with extension personnel,

participation in extension activities, overall



significant correlation with adoption of maize,

whereas, farming experience, family size,

occupation, annual income, irrigation facility, overall


orientation, scientific orientation ,knowledge and

land size had significant correlation with productivity

of maize.

REFERENCES

Bawa, D.B. and Ani, A.O. (2014). Analysis of

Adoption of Improved Maize Production Technology

among Farmers in Southern Borno, Nigeria.

Research on Humanities and Social Sciences, 4(25):

137-141.

Chhattisgarh (2014). Annual statistics report.

CIMMYT (2005). Maize in India: production

systems, constraints, and research priorities.

Darandale, A.D. and Soni, N.V. (2011).

Relationship between Attitude of Tribal Maize

Growers Towards Organic Farming and Their


Selected Characteristics. Gujarat Journal of

Extension Education, 22: 89.

Gecho, Yishak and Punjabi, N.K. (2011).

Determination of adoption of improved Maize

technology in Damot Gale, Wolaita, Ethiopia. Raj. J.

Ext. Edu., 19: 1-9.

Gupta, Km. Saroj and Gyanpur, S.R.N. (2012).

Sustainability of scientific maize cultivation practice

in Uttar Pradesh, India. Journal of Agricultural

Technology. 8 (3): 1089-1098.

Langade, D. M., Shahi, J.P., Agrawal, V. K. and

Sharma, A. (2013). Maize as emerging source of oil

in india: an overview. Maydica, 58(3/4): 224-230.

R. Cox (1956). Control of helminthosporium

turcicum blight disease of sweet corn in South

Florida. Phytopathology, 5: 68-70.

Reddy, T. R.., Reddy, P. N., Reddy, R. R. and

Reddy, S. S. (2013). Management of Turcicum leaf

blight of maize, caused by Exserohilum Turcicum in

maize. International Journal of scientific and

Research publications, 3(10): 1-4.

Sharma, K.C., Singh, P. and Panwar, P. (2012).

Association of personal attributes with knowledge

and adoption regarding maize production in Bhilwara

Rajasthan. Agriculture Update, 7(3 & 4): 376-380.

Willy, V. (Undated) (2013). Soil plant growth and

production Vo. II National Science foundation

Flanders and geography department, Belgium:

University of Ghenl. (accessed on 02/01/2013).




MORPHOLOGICAL VARIATION OF TENDU (DIOSPYROS MELANOXYLON)

LEAVES IN DHAMTRI DISTRICT OF CHHATTISGARH, INDIA

Pratap Toppo1, R.K. Prajapati

1, M.L. Lakhera

2 and Abhishek Raj

3*

1Department of Forestry, College of agriculture Raipur, Chhattisgarh-INDIA

2Department of Agricultural Statistics, College of agriculture Raipur, Chhattisgarh-INDIA

3Department of Forestry, Faculty of Agriculture and Veterinary Sciences, Mewar University,

Chittaurgarh (Rajasthan) - 312901


Received-06.01.2020, Revised-27.01.2020 Abstract: In the present study, morphological variation of tendu (Diospyros melanoxylon) leaves Dhamtari district were

analyzed. The highest length of petiole was observed in year 2016 in site-2 (Nagri) (1.82 cm), followed by Site-1(Dugli) (1.8

cm) in year 2015. Minimum length of petiole was recorded in Site -1 (Dugli ) (1.5 cm) in year 2016. The highest diameter of

petiole was observed in year 2016 in site-1 (Dugli) (1.33 cm), followed by Site-2 (Nagri) (1.3 cm) in year 2015. Minimum

diameter of petiole was recorded in Site -2 (Nagri) (1.2 cm) in year 2016. The highest length of leaf was observed in year

2016 in site-2 (Nagri) (14.27 cm), followed by Site-2 (Nagri) (13.57 cm) in year 2015. Minimum length of leaf was recorded

in Site -1 (Dugli) (13.34 cm) in year 2016. The highest Width of leaf was observed in year 2016 in site-2 (Nagri) (7.97 cm)

,followed by Site-2 (Nagri) (7.02 cm) in year 2015. Minimum Width of leaf was recorded in Site -1 (Dugli) (6.62 cm) in

year 2016. The highest leaf area was observed in year 2016 in site-1 (Dugli) (72.92 cm), followed by Site-2 (Nagri) (72.7

cm) in year 2015. Minimum leaf area was recorded in Site -1 (Dugli) (86.18 cm) in year 2015.

Keywords: Diospyros melanoxylon, Forest, Petiole, Tribes, Heterogeneity

INTRODUCTION

iospyros melanoxylon Roxb. (Common name

Tendu or Kendu) an endemic plant of India and

Ceylon is used in various ways. Besides being the

source of Indian ebony, its wood is also utilized for

making boxes, combs, ploughs and beams. The fruits

are eaten and sold commercially. The bark is burnt

by tribals to “cure” small-pox. The seeds are

prescribed as cure for mental disorders, palpitation of

heart and nervous breakdown. Above all, the leaves

of this plant constitute one of the most important raw

materials of the “Bidi” (Indian cheap smoke)

industry. It is not only an extremely important non-

timber forest product that serves as a big revenue

earner for the state government but is also an

important economic resource to the indigenous tribes

and local population during the summer months

when they have no other form of employment. Tendu

leaves are used to make bidis, an indigenous leaf-

rolled cigarette made from coarse uncured tobacco,

tied with a coloured string at one end. It is widely

smoked in the Indian subcontinent and is gaining

popularity globally, especially in USA, Germany,

Middle East, Eastern Europe and Japan (Tobacco

Board of India, 2010). Although Tendu leaves and

Bidi rolling are perceived as an important source of

employment for the rural poor (Planning

Commission, 2001). Tendu plucking generates only

part-time employment for about 7.5 million people

(Arnold, 1995) while rolling bidis engages nearly 4.4

million women and children. Tendu plucking

provides 106 million person-days of employment in

collecting activities and 675 million person-days in

secondary processing (World Bank 2006).

The trade has tremendous socioeconomic value to the

local population and is a source of income to them in

the economically stretched summer months. Due to

extreme exploitation of the collectors, who are

mostly local indigenous people, the state

governments have established state control over its

collection and trade to earn revenue. The state and

the central governments have continuously sought to

empower the local populations, and several steps

have been taken to establish ownership rights of the

collectors over non-timber forest products. This has

culminated in the 73rd constitutional amendment in

1996 that has given the ownership right over non-

timber forest products to the Gram Sabhas (local

groups or entities). There is an established network

of selling agents composed of wholesalers and

retailers. Some big companies also export some

beedis (local cigarettes) to neighboring countries like

Pakistan, Sri Lanka, Bangladesh, and Nepal and to

distant countries such as the United States, France,

African and West Asian countries.


Dhamtari is abbreviated from “Dhamma” and

“Tarai". District is situated in the fertile plains of

Chhattisgarh Region. Jabarra village is located in

Nagri Tehsil of Dhamtari district in Chhattisgarh,

India. It is situated 18 km away from sub-district

headquarter Nagari, 58 km away from district

headquarter Dhamtari and 110 km from State capital

Raipur. Jabarra village is also a gram panchayat and

D

RESEARCH ARTICLE


32 PRATAP TOPPO, R.K. PRAJAPATI, M.L. LAKHERA AND ABHISHEK RAJ

has a total population of 458 peoples. There are

about 117 houses in Jabarra village. Jabarra comes

under medicinal plants conservation areas (MPCA)

of 200 hectares and comprises protected forest. This

was established by the assistance of Ministry of

Environment Forest and Climate Change in 2009.

The study was conducted in Dugli and Nagari forest

range in Dhamtari forest division situated in

Dhamtari district (Chhattisgarh) during the year

2015-2016.

The study sites are located in the Dhamtari district

(20o 29' 49'' to 20

o 33’12” N lat. and 81

o 52' 29" to

81o 53' 40" E long. with an altitude of 399 m above

the mean sea level within the Dhamtari Forest

Division in Chhattisgarh. The study area falls under

dry deciduous forest, agriculture lands and human

settlements surround the study area is common .

Most of the villages in study area are categorized as

forest villages and majorities of them are accessible

through Kaccha roads, which is motorable only in

dry season.

The climate of the study area is wet sub-tropical and

dry tropical. The year is divisible into three seasons

viz. rainy (mid June to September), winter season

(November to February) and summer (April to mid

June). October and March comprise transition

periods, respectively between rainy and winter, and

between winter and summer seasons. Mean monthly

value for temperature and rainfall based on five year

data (2013-2018) are plotted in figure 1.

The mean monthly temperature ranges between 18.4 oC in December and 34.8

oC in May and the mean

annual temperature averages 26.6 oC. The average

annual rainfall of the study area is 1104.3 mm. About

80% of the annual rainfall in the study area is

received during June to August. Relative humidity of

study area increases with the onset of South-West

monsoon and it becomes 86% during July and

August. Relative humidity is lowest during summer

and drops below 26.5% in the afternoon in April and

May. Water table varies between 15-20m.

Figure 1: Ombrothermic diagram of tropical dry deciduous forest based on five year data (2013-2018)

Experimental details

Site selection:

Assessment of morphological variations in Tendu

leaves from Dhamtari forest. Two site-1(Dugli) and

site-2(Nagri) forest area were selected in Dhamtari

forest to study the morphological variations in

leaves. The data was collected two years for the

experiment 2015 & 2016. Each forest sites twenty

trees were selected for the study of morphological

variation in leaves from each tree three leaves were

collected smallest, medium sized and largest leaves

respectively. The sample trees were selected random

covering heterogeneity of forest to collect the leaves.

Diospyros melanoxylon Roxb. (Common name

Tendu) an endemic plant of India and Ceylon is used

in various ways. The leaves were collected from 15

April to 15 June this is plucking period.


Morphological characteristics of tendu leaf

(Diospyrous melanoxylon) of Dhamtari forest area

The morphological variation of leaf is shown in

Figure 2. The data relevant to length of petiole (cm),

diameter of petiole (cm), length of leaf (cm), width

of leaf (cm) and leaf area (cm2) from each year and

sites were presented in Table 1 and figure 3. The

highest length of petiole was observed in year 2016

in site-2 (Nagri) (1.82 cm) ,followed by Site-1(Dugli)

(1.8 cm) in year 2015. Minimum length of petiole

0.00

50.00

100.00

150.00

200.00

250.00

300.00

350.00

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

90.00

100.00

JAN FEB MAR APR MAY JUN JULY AUG SEP OCT NOV DEC

Temperature Rainfall(mm)

Months

Rain

fall (mm

)Mea

n

Tem

per

atu

re (

0C

)


was recorded in Site -1 (Dugli) (1.5 cm) in year

2016. Whereas mean value of length of petiole was

higher (1.75 cm) in year 2015 as compared to year

2016. Ram et al. (2012) Reported similar observation

in litchi accessions assessed for morphological

characters of leaf Petiole differential In Purbi (0.83

mm) which was equivalent to Hong Kong (0.82

mm), Seedless-1 (0.75 mm), Shahi (0.72 mm) and

Serguja Se1.1 were observed higher in the petiole

range. Differences (0.46 mm) could be due to the

genetic composition of the cultivars and their

reaction to environmental conditions among the

various accessions the maximum leaflet blade width

was recorded in Kasba (4.81 cm).

Table 1. Morphological characteristics of Tendu leaf (Diospyros melanoxylon) of Dhamtari forest area 2015-

2016

Characteristics

2015 Site

1

2015 Site

2 Mean

2016 Site

1

2016 Site

2 Mean

Dugli Nagri Dugli Nagri

length of petiole (cm) 1.8 1.7 1.75 1.5 1.82 1.66

diameter of petiole (cm) 1.21 1.3 1.26 1.33 1.2 1.27

Length of leaf (cm) 13.38 13.57 13.48 13.34 14.27 13.81

Width of leaf (cm) 6.86 7.02 6.94 6.62 7.97 7.30

leaf area sq1 (cm) 68.18 72.7 70.44 72.92 69.77 71.35

Figure 3: Tendu leaf (Diospyros melanoxylon) of Dhamtari forest area

0

10

20

30

40

50

60

70

80

Dugli Nagri Dugli Nagri

2015 Site 1 2015 Site 2 Mean 2016 Site 1 2016 Site 2 Mean

Un

it (

cm)

Fig 2. Morphological characteristics of Tendu leaf (Diospyros melanoxylon) of

Dhamtari forest area 2015-2016

length of petiole (cm) diameter of petiole (cm) Length of leaf (cm)

Width of leaf (cm) leaf area sq1 (cm)

34 PRATAP TOPPO, R.K. PRAJAPATI, M.L. LAKHERA AND ABHISHEK RAJ

CONCLUSION

This study gives the information regarding

morphological variation among the two sites in

Dhamtari districts of Chhattisgarh state. The highest

length of petiole was observed in year 2016 in site-2

(Nagri) (1.82 cm), followed by Site-1(Dugli) (1.8

cm) in year 2015. Minimum length of petiole was

recorded in Site -1 (Dugli) (1.5 cm) in year 2016.

The highest diameter of petiole was observed in year

2016 in site-1 (Dugli) (1.33 cm), followed by Site-2

(Nagri) (1.3 cm) in year 2015. Minimum diameter of

petiole was recorded in Site -2 (Nagri) (1.2 cm) in

year 2016. The highest length of leaf was observed in

year 2016 in site-2 (Nagri) (14.27 cm), followed by

Site-2 (Nagri) (13.57 cm) in year 2015. Minimum

length of leaf was recorded in Site -1 (Dugli) (13.34

cm) in year 2016. The highest Width of leaf was

observed in year 2016 in site-2 (Nagri) (7.97 cm)

,followed by Site-2 (Nagri) (7.02 cm) in year 2015.

Minimum Width of leaf was recorded in Site -1

(Dugli) (6.62 cm) in year 2016. The highest leaf area

was observed in year 2016 in site-1 (Dugli) (72.92

cm), followed by Site-2 (Nagri) (72.7 cm) in year

2015. Minimum leaf area was recorded in Site -1

(Dugli) (86.18 cm) in year 2015.

REFERENCES

Arnold, J.E.M. (1995). Socio-economic benefits and

issues in non-wood forest product use. Report of the

international expert consultation of nonwood forest

products. Rome: Food and Agriculture Organization

of the United Nations.

Planning Commission (2001). Expert Group on

poverty estimation 1999–2000. New Delhi:

Government of India.

Ram, R. B., Kumar, V., Meena, M. L. and Rubee,

L. (2012). Diversity in leaf and shoot characteristics

in litchi (Litchi Chinensis Sonn.) accessions. Annals

of Horticulture, 5(1): 95-102.

Tobacco Board of India (2010). Annual report and

accounts of the tobacco board (2009–2010) India:

Guntur.

World Bank (2006). Unlocking opportunities for

forest-dependent people in India. New Delhi, India.



COMPATIBILITY OF ENTOMOPATHOGENIC FUNGI WITH BUPROFEZIN FOR

MANAGEMENT OF BROWN PLANTHOPPER, NILAPARVATA LUGENS STAL

(DELPHACIDAE: HEMIPTERA) IN RICE

B. Nagendra Reddy*, V. Jhansi Lakshmi1, G.S. Laha

2 and T. Uma Maheswari

3

1Division of Entomology, Indian Institute of Rice Research, Rajendranagar,

Hyderabad- 500030, Telengana India, 2Division of Plant Pathology, Indian Institute of Rice Research, Rajendranagar,

Hyderabad- 500030, Telengana India 3Department of Entomology, College of Agriculture, Rajendranagar, PJTSAU,

Hyderabad- 500030, Telengana India;


Received-04.01.2020, Revised-23.01.2020 Abstract: Compatibility between Buprofezin 25SC and entomopathogenic fungi studies were conducted at IIRR (Indian

Institute of Rice Research), Hyderabad. Buprofezin 25 SC was tested at three concentrations viz., recommended

concentration (RC), sub lethal concentration (0.5 RC) and more than recommended concentration (1.5 RC) against three

entomopathogenic fungi viz., Beauveriabassiana, Metarhiziumanisopliae and Lecanicilliumlecanii (Verticilliumlecani) by

using poison food technique under laboratory conditions. Buprofezin 25 SC was harmless to all three tested

entomopathogenic fungi at 0.5 RC and RC recorded 5.53 to 15.96 per cent inhibition of the entomopathogenic fungi. At 1.5

RC buprofezin was harmless to B. bassiana (19.57 per cent inhibition in growth of the fungus) and slightly harmful to M.

anisopliae and L. Lecanii recorded 20.21 and 23.40 per cent reduction in growth of the fungus respectively.Combined use of

imidacloprid with entomopathogenic fungi at recommended concentrations against BPH under glasshouse conditions

indicating buprofezin alone could cause 55.00 per cent mortality in BPH. Buprofezin combined with entomopathogenic

fungi increased the mortality of BPH compared to buprofezin alone spray.

Keywords: Beauveria, Brown planthopper, Entomopathogenic fungi, Lecanicillium, Metarhizium, Nilaparvata lugens

INTRODUCTION

ice is Life” describes the importance of rice in

human diet. It is grown worldwide over an area

of 153 million hectares with annual production of

more than 600 million tonnes. In India, it is

cultivated in an area of 44.80 million hectares with

an annual production of 89.31 million tonnes and

productivity over two tonnes of milled rice per

hectare (CMIE, 2014). Insect pests are the severe

constraints to rice production throughout the world

(Dale, 1994) where more than 100 species of insect

pests attack and damage rice (Pathak, 1968). Among

all brown planthopper (BPH), Nilaparvata

lugens (Stal) (Hemiptera: Delphacidae) is one of the

most economically important insect, which can cause

huge damage where both nymphs and adults suck the

plant sap directly and indirectly transmit viruses such

as ragged stunt and grassy stunt (Jena et al., 2006).

Due to infestation plants turn yellow and dry up

rapidly. At early infestation, round and yellow

patches appear, which soon turn brownish due to the

drying up of the plants which is called as 'hopper

burn', and could result in causing yield loss ranging

from 10-75% (Park et al., 2008). Insecticides are the

major means of managing the BPH. However,

continuous use of these insecticides causing health

hazards and environmental pollution, besides this it

cause development of insecticide resistance in the

insects (Jhansi Lakshmi et al., 2010b). So, it is very

difficult to manage the insect by insecticides alone,

for this BIPM (Bio-intensive Integrated Pest

Management) include combined use of chemical

pesticides with bio pesticides such as bacteria, fungi

and viruses for control of pests. Therefore, the

present investigation has been planned with

combined use of fungal formulations and buprofezin

for managing BPH. Buprofezin is a growth regulator

which inhibits chitin synthesis in insect.


Experiment was carried out to evaluate compatibility

between buprofezin and entomopathogenic fungi

(Beauveriabassiana, Metarhiziumanisopliae and

Lecanicilliumlecanii) both in the laboratory and

glasshouse at Indian Institute of Rice Research

(Formerly Directorate of Rice Research), Hyderabad.

Inhibitory studies in the laboratory (Poison food

technique)

Standard poison food technique was followed to

assess compatibility of the entomopathogenic fungi

with various insecticides (Moorhouse et al., 1992).

Desired quantity of insecticide (Buprofezin 25SC)

based on field application rate (recommended

concentration, half recommended concentration and

1.5 recommended concentration) was added to the

PDA medium (200 ml), autoclaved at 121○C (15 Psi)

for 15-20 minutes in the conical flask before

solidification (medium temperature 48○C) to get

R

RESEARCH ARTICLE


36 B. NAGENDRA REDDY, V. JHANSI LAKSHMI, G.S. LAHA AND T. UMA MAHESWARI

desired concentration and later was mixed

thoroughly. The medium was then poured equally

into the petriplates. Each treatment was replicated

four times. Small disc (5 mm dia.) of young fungal

mycelium was cut with sterile cork borer and placed

aseptically in the centre of plate containing the

poisoned medium. Petri plates were incubated at

27±1○C, 80±5% relative humidity. Suitable check

without poison was kept for comparison under the

same conditions. Diameter of the fungal colony was

measured at 2, 4, 6, 8 and 10 days after inoculation

(DAI) and compared with standard check. The data

were expressed as percentage growth inhibition of

fungiby insecticide treated PDA (Hokkanen and

Kotiluoto, 1992) and calculated by the formula

Y-Z

X = —— × 100

Y

Where X, Y, Z stand for percentage growth

inhibition, radial growth of the fungus in untreated

check and radial growth of the fungus in poisoned

medium, respectively. The pesticides were further

classified in evaluation categories of 1- 4 scoring

index. 1 = harmless (<20% reduction), 2 = slightly

harmful (20-35% reduction), 3 = moderately harmful

(35- 50% reduction), 4 = harmful (>50% reduction)

in toxicity tests in vitro according to Hassan’s

classification scheme (Hassan, 1989).

Inhibitory studies under glasshouse conditions The recommended dose of buprofezin 25 SC(2ml/l)

was mixed with the recommended dose of effective

fungal commercial formulations (5g/l) and sprayed

on to the rice plants. BPH were released on the

sprayed plants and mortality was recorded at 24 hrs

interval up to five days after spraying. The results

were compared with those of buprofezin and fungal

pathogens alone by recording data on per cent

mortality.


Effect of buprofezin 25 SCon growth of

entomopathogenic fungi

Buprofezin at 0.5 RC and RC did not significantly

inhibit the growth of three entompathogenic fungi

(5.53 – 15.96 %) (Table.1). However, the inhibitory

effect was observed at 1.5 RC and was found slightly

harmful to growth of the fungi recording 19.57 to

23.40 per cent reduction of radial growth over

control. When the media was mixed with 0.5 RC, RC

and 1.5 RC of buprofezin and inoculated with B.

bassiana, it resulted in 6.52, 11.96 and 19.57 per cent

reduction of radial growth of the fungus. Similarly

5.53, 15.74 and 23.40 per cent reduction in M.

anisopliae and 6.38, 15.96 and 20.21 per cent

reduction in case of L. lecanii was observed.

Anderson et al. (1989) also reported that insecticides

of microbial origin and chitin inhibitors such as

abamectin, thuringiensin and triflumuron were

compatible with B. bassiana even at higher doses

supporting the present observation where in

buprofezin, a chitin inhibitor was found to be slightly

harmful at higher concentration. Further, it was

confirmed by Andrew et al. (2005) who have

reported that the active ingredient buprofezin

provided an acceptable level of spore germination of

L. muscarium.

According to present results buprofezin was harmless

to all three tested entomopathogenic fungi at 0.5 RC

and RC. At 1.5 RC buprofezin was harmless to B.

bassiana and slightly harmful to M. anisopliae and L.

lecanii.

Effect of buprofezin 25 SC +entomopathogenic

fungi on BPH

Buprofezin is an insect growth regulator and it

mainly inhibits chitin synthesis affecting

development of BPH nymphs. Present results

indicated that buprofezin alone caused 55.00 per cent

mortality at 5 DAS, and mortality was increased by

combining buprofezin with the entomopathogenic

fungi, B. bassiana, M. anisopliae and L. lecanii.

Results presented in the Table 2.indicated that there

was negligible mortality of BPH for first two days

after spraying which increased with increase in time

when buprofezinwas used alone or combined with

entomopathogenic fungi. At 1 DAS, buprofezin

alone, buprofezin + B. bassiana, buprofezin + M.

anisopliae and buprofezin + L. lecanii recorded 2.50,

2.50, 0.00 and 1.25 per cent mortality, respectively

and at 2 DAS, mortality increased to 16.25, 11.25,

10.00 and 11.25 per cent, respectively. However,

mycosis was observed from 3 DAS and the mortality

increased in combination treatments compared to

buprofezin alone. At 3 DAS, highest mortality of

BPH was observed in buprofezin + L.

lecanii(48.75%) followed by buprofezin + B.

bassiana(43.75 per cent) and buprofezin + M.

anisopliae(43.75 per cent).Buprofezin alone recorded

36.25 per cent mortality which was on par with

buprofezin + B. bassiana and buprofezin + M.

anisopliaetreatments and these were significantly

superior over control (2.50 per cent mortality).

Mortality of BPH was increased in combination

treatments at 4 DAS i.e. buprofezin + B.

bassiana(63.75 per cent), buprofezin + M.

anisopliae(60.0 per cent) and buprofezin + L. lecanii

(66.25 per cent) which were on par with each other

and significantly superior over buprofezin alone

which recorded 46.25 per cent mortality. Similarly at

5 DAS, mortality has further increased to 77.5, 82.5

and 82.5 per cent inbuprofezin + B. bassiana and

buprofezin + M. anisopliae and buprofezin + L.

lecaniitreatments, respectively which were on par

with each other and significantly superior over

buprofezin alone which has recorded 55.00 per cent

mortality. In the present investigation, at five days

after spraying buprofezin + B. bassiana (77.50 per

cent), buprofezin + M. anisopliae (82.50 per cent)

and buprofezin + L. lecanii (82.50 per cent)

treatments recorded highest per cent mortality


compared to individual spraying of buprofezin (55.00

per cent mortality), B. bassianawith 8.75 per cent

mortality,M. anisopliaewith 10.00 per cent mortality

and L. lecanii with 12.50 per cent mortality.

Buprofezin being a growth regulator which inhibits

the growth of the insect, it doesn’t kill the insect

immediately and provide more time for disease

development. These findings are in corroboration

with the findings of Fenget al. (2011) who reported

54 to 60 per cent BPH mortality in the field by

spraying of Ma456 and Ma576 alone @ 1.5 x 1013

conidia/ha and they further suggested that mortality

could be increased to 80 to 83 per cent by

incorporating 30.8 g/ha buprofezin along with fungal

sprays; These reports support present study where in

by mixing of entomopathogenic fungi with

buprofezin, per cent mortality of BPH could be

increased from 55.00 per cent (buprofezin alone) to

82.50 per cent with M. anisopliae and L. lecanii and

77.50 per cent with B. bassiana.

Table 1. Effect of buprofezin 25 SC on growth of entomopathogenic fungi

Fungus

0.5 Recommended

Concentration

Recommended

Concentration

1.5 Recommended

Concentration Untreated

Control

Radial

growth (cm)

Mean Radial

growth

(cm)

Inhibition

(%)

Radial

growth

(cm)

Inhibition

(%)

Radial

growth (cm)

Inhibition

(%)

B. bassiana 4.30 6.52 4.05 11.96 3.70 19.57 4.60 4.16b

M. anisopliae 5.55 5.53 4.95 15.74 4.50 23.40 5.88 5.22a

L. lecanii 4.40 6.38 3.95 15.96 3.75 20.21 4.70 4.20b

Mean 4.75b 4.32c 3.98d 5.06a

CV (%) 3.19

LSD (5%)

Fungus 0.10

Concentration 0.12

Means with same letter are not significantly different at 5% level by DMRT

RC- Recommended Concentration

Table 2. Effect of buprofezin 25 SC in combination with entomopathogenic fungi on BPH

Treatment

Mortality (%)

1 DAS 2 DAS 3 DAS 4 DAS 5 DAS

Buprofezin 25SC @ 2ml/l

2.50

( 9.09)

16.25

(23.76)a

36.25

(37.00)b

46.25

(42.83)b

55.00

(47.85)b

Buprofezin 25SC @ 2ml/l +

B. bassiana@ 5g/l

2.50

(9.09)

11.25

(19.59)a

43.75

(41.39)ab

63.75

(52.96)a

77.50

(61.66)a


M. anisopliae@ 5g/l

0.00

(0.00)

10.00

(18.14)a

43.75

(41.39)ab

60.00

(50.75)a

82.50

(65.24)a


L. lecanii@ 5g/l

1.25

(6.42)

11.25

(11.59)a

48.75

(44.27)a

66.25

(54.46)a

82.50

(65.24)a

Control

0.00

(0.00)

0.00

(0.00)c

2.5

(9.09)c

3.75

(11.16)c

8.75

(17.20)c

CD N.S 5.89 7.28 8.03 5.58

SE(m) 2.77 1.94 2.39 2.64 1.84

Means with same letter are not significantly different at 5% level by DMRT

DAS- Days after spraying

38 B. NAGENDRA REDDY, V. JHANSI LAKSHMI, G.S. LAHA AND T. UMA MAHESWARI

ACKNOWLEDGEMENT

The first author expresses his heartfelt gratitude to

Department of Science and Technology, Ministry of

Science and Technology, Government of India, for

providing INSPIRE fellowship. The authors are

immensely thankful to Director, Indian Institute of

Rice Research for providing facilities to take up the

present investigation.

REFERENCES

Anderson, T.E., Hajek, A.E., Roberts, D.W.,

Preislev, H.K. and Robertson, J.L. (1989).

Colorado potato beetle (Coleoptera: Chrysomelidae):

Effects of combinations of Beauveriabassiana with

insecticides. Journal of Economic Entomology. 82:

83-89.

Andrew, G.S.C., Keith, F.A.W. and Carola, D. (2005). Compatibility of the entomopathogenic

fungus, Lecanicilliummuscarium and insecticides for

eradication of sweet potato whitefly,

Bemisiatabaci.Mycopathologia. 160: 35-41.

CMIE (2014). Executive Summary –GDP growth.

Centre for Monitoring Indian Economy (CMIE) pvt,

Ltd. Mumbai.

Dale, D. (1994). Insect pests of rice plants-their

biology and ecology. 363-485. In:Biology and

Management of Rice Insects (Heinrichs, E.A., ed.).

IRRI, Wiley Eastern Ltd.

Feng, J.S., Feng, M.G., Ying, S. H., Mu, W.J.

and Chen, J.Q. (2011). Evaluation of alternative rice

planthopper control by the combined action of oil-

formulated Metarhiziumanisopliae and low-rate

buprofezin.Pest Management Science. 67(1): 36-43.

Hassan, S.A. (1989). Testing methodology and the

concept of the IOBC/WPRS working group. Pp. 1-8.

In: Jepson, P.C.(Ed.). Pesticides and Non-target

invertebrates. Intercept, Wimborne, Dorset.

Hokkanen, H. M. T. and Kotiluoto, R. (1992).

Bioassay of the side effects of pesticides on

Beauveriabassianaand Metarhiziumanisopliae:

standardized sequential testing procedure.

IOBC/WPRS Bull. XI(3):148-151.

Jena, K. K., Jeung, J. U., Lee, J. H., Choi, H. C.

and Brar, D. S. (2006). High resolution mapping of

a new brown planthopper (BPH) reistance gene, Bph

18 (t), and marker-assisted selection for BPH

resistance in rice (Oryzasativa L). Theor. Appl.

Genet.112: 288-297.

Jhansi Lakshmi, V., Krishnaiah, N.V., Katti,

G.R., Pasalu, I.C and Chirutkar, P.M. (2010b).

Screening of insecticides for toxicity to rice hoppers

and their predators.Oryza. 47 (4): 295-301.

Moorhouse, E. R., Gillsepie, A. T., Sellers, E. K

and Charnley, A. K. (1992). Influence of fungicides

and insecticides on the entomogenous fungus,

Metarhiziumanisopliae, a pathogen of the vine

weevil, Otiorhynchussulcatus. Biocontrol Science

and Technolnology, 82: 404 - 407.

Park, D.S., Song, M.Y., Park, K., Lee, S.K., Lee,

J.H. (2008). Molecular tagging of the Bph 1 locus

for resistance to brown plant hopper

(NilaparvatalugensStal.) through representational

divergence analysis.Mol. Genet. Genomics. 280: 163-

172.

Pathak, M. D. (1968). Ecology of rice pests.Annual

Review of Entomology, 13: 257-294.

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PRODUCTION, PRODUCTIVITY AND PROFITABILITY OF MAIZE (ZEA MAYS)

AS INFLUENCED BY DIFFERENT AGRONOMIC PRACTICES

Urmila Painkra*, P.K. Bhagat, A.K. Paliwal, V.K. Singh and A. K. Sinha

RMD College of Agriculture and Research Station, Indira Gandhi Krishi Vishwavidyalaya

Ambikapur, Surguja- 497001 (Chhattisgarh)


Received-03.01.2020, Revised-25.01.2020

Abstract: A field experiment was carried out during the kharif season of 2018-19 at Research farm, Ambikapur, to study the

effect of different agronomic management practices on production, productivity and profitability of maize. Different

treatment combinations were included in the experiment viz. farmers‟ practice, ecological intensification (EI), EI- tillage

practices, EI-nutrient management, EI- planting density, EI- water management, EI- weed management and EI- disease and

insect management laid out in randomized block design and replicated thrice. The mean loss in kernel yield of maize due to

EI- weed management was 28.76%. Ecological intensification recorded higher yield and yield attributes significantly higher

over rest of the treatments. Ecological intensification recorded significantly minimum total weed density (7.94 m-2) and

weeds dry weight (3.98 g) as compared to all other treatments and recorded highest kernel and stover yield.

Keywords: Ecological intensification, Maize, Kernel yield, Weed management

INTRODUCTION

aize (Zea mays ) popularly known as “Corn” is

one of the most versatile emerging cash crop

having wider adaptability under varied climate

condition and globally, it is called “Queen of cereal”

because of it has highest genetic yield potential.

Maize is one of the most important cereal crops in

the world, ranked third after wheat and rice and

contributes to the nearly 9% of the national food

basket (Jeet et al., 2014).

Although India is well placed in meeting its need for

food grains. The major objective of food and

nutritional security for its entire population has not

been achieved. Agricultural production depends on

various factors and any set back in these factors

severely affects the yield of crop. Tillage

management, nutrient management, Planting

Density, water management, weed management, and

plant protection management are the most important

factors influencing crop production, eco-environment

and sustainability in agricultural production.

Continuous use of modern techniques of agricultural

production has some drawbacks like over use of

chemicals leads to soil and water pollution, use of

heavy machines in the field results in soil

compaction, deteriorate the soil structure and reduces

infiltration rate leads to run off and soil erosion.

Ecological intensification is the process of improving

both yields and environmental performance of crop

production with a focus on precise management of

all production factors and maintenance or

improvement of soil quality. The terms ecological

intensification and sustainable intensification were

first coined in the late 1990s (Cassman, 1999 and

Pretty, 1997). Ecological intensification comprises of

best tillage and residue management practices; best

planting density and genotype; precision nutrient

management based on nutrient expert, application of

water at critical growth stages; integrated weed,

disease and insect management. Therefore, the

present experiment was undertaken to find out the

effect and extent loss due to different agronomical

practices on the production, productivity and

profitability of maize in Northern Hill region of

Chhattisgarh.


The present investigation entitled „„Production.

Productivity and profitability of maize (Zea mays) as

influenced by different Agronomic practices‟‟ was

conducted during kharif season 2018-19 at Research

farm of RMD College of Agriculture and Research

Station, Ambikapur situated at 230 18' N latitude and

830 15' E longitude and at altitude of 623 meter

above mean sea level. The soil of the experimental

site was sandy loam in texture, acidic in reaction (pH

5.7), medium in organic carbon (0.56), available

nitrogen (234 kg ha-1), available phosphorus (8.4 kg

ha-1) and available potassium (268 kg ha-1). The

experiment was laid out in randomized block design

with 8 treatments replicated thrice. Treatments are

farmers‟ practice, ecological intensification (EI), EI-

tillage practices, EI-nutrient management, EI-

planting density, EI- water management, EI- weed

management and EI- disease and insect management.

Field preparation was done as per treatment. In

farmers' practice treatment, experimental plots were

ploughed once with tractor drawn cultivator and

leveled by harrowing whereas in ecological

intensification treatments, experimental plots were

deep ploughed twice with tractor drawn cultivator

and leveled by harrowing to obtain fine tilth. Sowing

and spacing were made as per treatment. Maize var.

“JK super 502” was sown in lines at a spacing of 50

M

RESEARCH ARTICLE


40 URMILA PAINKRA, P.K. BHAGAT, A.K. PALIWAL, V.K. SINGH AND A. K. SINHA

X 20 cm in farmers' practice treatment, whereas 60 X

20 cm in ecological intensification treatments.

Nutrient management was done as per treatment. In

farmers' practice treatment, fertilizers were applied in

experimental plots @ 120:60:40 kg ha-1

(N: P:

K)whereas in ecological intensification treatments,

SSNM based fertilizers were applied in experimental

plots @ 170:67:87 kg ha-1

(N: P: K).In farmers'

practice treatment, one third nitrogen, full dose of

P2O5 and K2O were applied as basal at the time of

sowing and remaining nitrogen was top dressed in

two equal splits at Knee high stage (30 DAS) and at

tasseling stage (50 DAS). In ecological

intensification treatments, one fourth nitrogen and

entire dose of P2O5 and K2O were applied as basal

dose at the time of sowing by placement method. The

Remaining nitrogen was applied as top dressing in

three equal splits at Knee high stage (30 DAS),

tasseling stage (50 DAS) and seed setting (65 DAS)

equally as per treatments. Weed management was

done as per treatment. In farmers' practice treatment,

Atrazine was applied as pre-emergence in

experimental plots @ 1 kg a.i. ha-1

whereas in

ecological intensification treatments, Atrazine was

applied as pre-emergence @ 1 kg a.i. ha-1

fb

Tembotrione 120 g a.i. ha-1

as post-emergence 25

DAS. Weed count and weed dry weight was recorded

at 60 DAS randomly at 2 places in each plot. Data on

weed population and weed dry weight subjected to

square root transformation because of wide

variations. Plant protection was made as per

treatment. In farmers' practice treatment, no plant

protection measures were adopted whereas in

ecological intensification treatments, Phorate 10 G

(2-3 granules) were applied in the leaf whorl to

control stem or shoot borer in each plant at 30 DAS.

Five random plants were tagged randomly from each

plot for recording of growth and yield attributes.

Gross returns, net returns and benefit: cost ratios

were calculated on the basis of prevailing market

price of inputs and produce. All data obtained in the

was statistically analyzed using F- test, the procedure

given by Gomez & Gomez (1984), critical difference

(CD) values at P= 0.05 were used to determine the

significance of differences between means.

RESULT AND DISCUSSION

Yield attributes

Yield attributes viz., cob length (cm), cob girth (cm),

no. of kernel rows cob-1

, no. of kernels row-1

and 100

kernel weight were significantly affected due to

various agronomical practices (Table 1). Data

revealed that ecological intensification (T2) recorded

higher yield attributes found at par with T6 i.e., EI-

water management, T8 i.e., EI-insect & disease

management found significantly superior over T3 i.e.,

EI- tillage practices, T5 i.e., EI- planting density, T1

i.e., farmer practices, T4 i.e., EI- nutrient

management and T7 i.e., EI-weed management.

Lower yield attributes were recorded under T7 i.e.,

EI-weed management as compared to other

management practices.

Weed dynamics and dry weight

Different agronomical practices significantly affected

the weed density and their dry weight (Table 1).

Ecological intensification had minimum weed

density and their dry matter showed parity with T6

i.e., EI- water management, T8 i.e., EI- insect and

disease management, T3 i.e., EI- tillage management,

T4 i.e., EI- nutrient management and T5 i.e., EI-

planting density. The maximum total weeds dry

matter was recorded with T7 i.e., EI-weed

management followed by T1 i.e., farmers‟ practices

and both of these treatments were significantly

inferior to other treatments.

Weeds always compete with crop for nutrient, water

and light which significantly affect the growth and

development of crops and ultimately reduced the

yield up to 42% depending upon the severity of weed

infestation. The findings of present study revealed

that total weed density was recorded higher under EI-

weed management followed T1 i.e., farmers‟

practices where only pre-emergence herbicide

atrazine were applied but in ecological intensification

and other treatments tembotrione was also used as

post emergence at 25 DAS. Ecological intensification

treatment had significant impact on weed density as

well as total weeds dry weight at 60 DAS. In latter

stage of crop growth, some weeds were germinated

as 2nd

or 3rd

flush but there was no side effect due to

these weeds and they are suppressed due to plant

canopy. Findings are in conformity with the finding

of Barua et al. (2019).

Table 1. Yield attributes and weed dynamics in maize as influenced by different agronomical practices

Tr.

No. Treatment

Yield attributes

Weed density

Total

weeds

dry

weight

(m-2)

Cob

length

(cm)

Cob

girth

(cm)

No. of

kernel

rows/cob

No. of

kernels/

row

Grassy

Weeds

(m-2)

Broad-

leaf

(m-2)

Sedge

(m-2)

Total

weeds

(m-2)

T1 Farmer‟s Practices 12.37 12.30 10.80 24.33

8.30

(68.53)

6.28

(39.00)

4.76

(22.20)

3.05

(8.83)

4.70

(21.59)

T2 Ecological

Intensification 18.73 13.44 13.47 36.73

5.03

(24.93)

4.50

(19.80)

3.74

(13.53)

2.20 (4.36) 3.98

(15.39)


T3 EI - Tillage practice

15.47 12.75 12.47 31.40 5.40

(28.67) 4.73

(21.93) 3.91

(14.80)

2.41

(5.30) 4.23 (17.42)

T4 EI-Nutrient

Management 11.93 11.90 9.93 25.93 5.44

(29.07) 4.81

(22.67) 3.96

(15.23)

2.58

(6.23) 4.18

(17.01)

T5 EI- Planting

Density 14.23 12.50 12.13 27.93

5.38

(28.53)

5.26

(27.17)

3.95

(15.13)

2.42

(5.37)

4.28

(17.82)

T6 EI- Water

Management 18.30 13.20 13.33 34.00

5.14

(25.93)

4.53

(20.07)

3.85

(14.30)

2.23 (4.47) 4.12

(16.45)

T7 EI- Weed

Management 10.23 9.74 9.47 23.00

9.83 (96.13)

7.66 (58.20)

6.61 (43.33)

4.32

(18.20) 7.09 (49.86)

T8 EI- Disease and

Insect Management 17.35 12.91 13.17 33.07

5.25

(27.13)

4.80

(22.53)

3.86

(14.43)

2.28

(4.73) 4.23

(17.38)

Sem±

0.67 0.52 0.41 1.28 0.14 0.12 0.10 0.11

0.10

C.D.

(0.05)

2.05 1.59 1.26 3.90 0.44 0.37 0.30

0.34

0.40

Note: Data in parenthesis (original value) was subjected to √X + 0.5 transformations.

Yield

The kernel, stover yield and HI (%) were

significantly influenced due to different agronomical

practices (Table 2). The grain yield was found to

significantly influenced due to different treatments.

The treatment T2 i.e., Ecological intensification

recorded maximum yield and harvest index closely

followed by T6 i.e., EI- water management, T8i.e. EI-

insect and disease management and these treatments

were found significantly superior to T3 i.e., EI-tillage

practices,T5 i.e., EI-plant density,T1 i.e., farmer

practices,T4 i.e., EI- nutrient management andT7 i.e.,

EI- weed management. The minimum yield and

harvest index were obtained from T7 i.e., EI- weed

management.

The yield is the function of interplay of yield

attributes and the growth characters. The grain yield

of maize depends on the cob length, cob girth,

number of rows cob-1

, number of kernels row-1

and

100 grain weight. Yield attributes of maize were

significantly influenced by adapting different

management practices and higher value were noticed

under treatments with best all best agronomical

management practices i.e., ecological intensification

provided with sufficient water, nutrient management

based on site specific nutrient management, better

plant spacing, lower weed density. The yield

attributes viz., cob length, cob girth number of rows

cob-1

, number of kernels row-1

and 100 grain weight

were found higher with T2 i.e., Ecological

intensification as well as under T6 i.e., EI- water

management over rest of the all treatments. This

result is found to be in close conformity with

Mukherjee (2014) Barod et al. (2012).

Economics

Different Agronomical practices had significant

influence on net return and benefit: cost ratio.Net

return was significantly affected due to various

treatments. Maximum net return were obtain under

treatment T2 i.e., Ecological intensification (Rs.

56548.20) which was at par with T6 i.e., EI- water

management (Rs.52125.07) and T8 i.e., EI- Disease

and insect management (Rs. 49827.08) and all these

treatments were found significantly superior over T3

i.e., EI- tillage practices (Rs. 42495.74), T1 i.e.,

farmers‟ practices (Rs. 36790.46), T5 i.e., planting

density (Rs. 34291.93), T4 i.e., EI- nutrient

management (Rs. 29144.00) and Minimum net return

was obtained with T7 i.e., EI- weed management (Rs.

12404.90).

The maximum benefit cost ratio was noticed under

T2 i.e., Ecological intensification (1.33) which

remained on par with T6 i.e., EI- water management

(1.25) followed by T8 i.e., EI- Disease and insect

management (1.19) but significantly superior over T3

i.e., EI- tillage practices (1.07), T1 i.e., farmers‟

practices (0.95). T5 i.e., planting density (0.78), T4

i.e., EI- nutrient management (0.68) and Minimum

benefit cost ratio was obtained with T7 i.e., EI- weed

management (0.30).

The practical utility of any treatment can be best

judged because of net return and B:C ratio.

Ecological intensification treatment showed

significant direct yield advantage over EI- weed

management in maximizing net return as well as B:C

ratio. All the management practices provided more

net return than that of EI- weed management and

farmers‟ practices. It was also observed that all the

management treatments were more beneficial as

compared to EI- weed management and farmers‟

practices. This was because of more net returns than

the money spent in crop production under these

treatments. These results are found to be in close

conformity with Upasani et al. (2017) and Prasad et

al. (2014).

CONCLUSIONS

It can be concluded that ecological intensification

was most effective to enhance yield attributes and

yield of maize which was at par with EI- water

management, EI – disease and insect management

42 URMILA PAINKRA, P.K. BHAGAT, A.K. PALIWAL, V.K. SINGH AND A. K. SINHA

and EI- Tillage practice and significantly superior

over rest of the treatments. EI- weed management

treatment reduced the yield attributes and yield of

maize at higher extent upto 28.76%. EI- weed

management recorded lowest BC ratio that is one of

the important factor which caused maximum loss.

Table 2. Yield and economics of maize cultivation as influenced by different agronomical practices

Treatment

Kernal Yield

(Kg ha-1)

Stover Yield

(Kg ha-1)

Harvest index

(%)

Net return

(Rs)

BC ratio

T1 Farmers‟ Practices

5044.44 15081.21 31.37 36790.46 0.95

T2 Ecological Intensification

6745.11 17225.07 35.56 56548.20 1.33

T3 EI- Tillage practice

5548.88 15651.82 31.28 42495.74 1.07

T4 EI-Nutrient Management 4815.55 13993.30 31.31 29144.00 0.68

T5 EI- Planting Density

5275.55 15203.43 31.56 34291.93 0.78

T6 EI- Water Management

6348.00 16720.09 34.27 52125.07 1.25

T7 EI- Weed Management

3593.33 10301.42 30.30 12404.90 0.30

T8 EI- Disease and Insect Management

6191.55 16066.55 33.15 49827.08 1.19

Sem±

220.98 842.74 0.59

3438.98 0.08

C.D.

(0.05)

660.61 2556.45 1.81

10432.1 0.26

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Effect of nutrient sources and weed control method

on yield and economics of baby corn (Zea mays) .

Indian Journal of Agronomy 57(1): 96-99.

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A. K. (2017). “Weed dynamics and productivity of

Maize (Zea mays L.) under pre and post emergence

application of herbicide.” Journal of Plant

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cereal production system: Yield potential, soil

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America. Vol. 96 (11): 5952-5959.

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productivity and profitability of QPM hybrid (Zea

mays L.) under dryland condition of Eastern Uttar

Pradesh. Indian J. Agri. Sci., 84(5): 589-594

Mukherjee, D. (2014). Influence of integrated

nutrient management on productivity, nutrient uptake

and economics of maize (Zea mays) – yellow sarson

(Brassica rapa) cropping system under rainfed mid

hill condition. Indian Journal of Agronomy 59(2):

221-228.

Prasad, D., Rana, D.S., Rana, K.S. and Rajpoot,

S.A. (2014). Effect of tillage practices and

diversification on productivity, resource – use

efficiency and economics of maize (Zea

mays)/soybean (Glycin max)-based cropping system.

Indian Journal of Agronomy 59(4): 534-541.

Pretty, J. (1997). Sustainable intensification in

agriculture system. Annals of Botany page 1-26

Upasani, R.R., Barla, S. and Puran, A.N. (2017).

Effect of tillage and weed control method in maize

(Zea mays) – wheat (Triticum aestivum) cropping

system. International Journal of Bio- resources and

Sterss Management .8(6): 758-766.



VARIETAL PERFORMANCE OF HIGH YIELDING VARIETY AND ECONOMICS

OF RADISH (RAPHANUS SATIVUS) THROUGH FRONT LINE DEMONSTRATION

(FLD) IN EAST KAMENG DISTRICT OF ARUNACHAL PRADESH

Manoj Kumar Singh*, Narendra Deo Singh, B.M. Singh and C.K. Singh

Krishi Vigyan Kendra, Pampoli, East Kameng district, Arunachal Pradesh

Krishi Vigyan Kendra, Dirang, West Kameng district, Arunachal Pradesh

Krishi Vigyan Kendra, Pashighat, East Siang district, Arunachal Pradesh

Krishi Vigyan Kendra, Tawang district, Arunachal Pradesh



Abstract: The Krishi Vigyan Kendra of East Kameng district of Arunachal Pradesh has conducted Front Line

Demonstrations with introduction of High Yielding Variety (HYV) of Radish viz., Arka Nishant, Arka hansh, Kashi sweta

and Kashi hansh variety in five villages during 2016-17 and 2017-18. The varieties introduceed were Arka Nishant, Arka

hansh, Kashi sweta and Kashi hansh against local check. Kashi hansh variety recorded the highest yield (175 q/ha) followed

by Kashi sweta (150 q/ha), Arka hansh (145 q/ha) and Arka Nishant (140q/ha). The increase in yield percentage over local

check variety was recorded to be the highest against Kashi Hansh (35%) followed by Kashi sweta (30%),Arka hansh (25%)

and Arka Nishant (24%). Benefit cost ratio was f/ound to be the highest in case of the variety Kashi hansh (2.22:1) followed

by var. Kashi sweta (2.16:1), Arka Nishant (2.08:1) and Arka hansh (1.98:1). Thus, all the four varieties had shown better

performance as compared to the local check variety in respect of yield and yield attributing characteristic and benefit cost

ratio.

Keywords: Varietal performance, Yield, Net income, B:C ratio

INTRODUCTION

adish is a popular vegetable in East Kameng

district of Arunachal Pradesh. It is cultivated

under glass house conditions for early market, but

large scale cultivation in the field is more common.

Radish (Raphanus sativus) is a root vegetable grown

and consumed all over the world and is considered

part of the human diet, even though it is not common

among some populations. Usually, people eat

radishes raw as a crunchy vegetable, mainly in salad,

while it also appears in many Arunachal dishes. In

addition, the edible root of radish varies in its flavor,

size, and length throughout the world. Being a quick

growing crop it can be easily planted as a companion

crop or intercrop between the rows of the other

vegetables. It can also be planted on ridges,

separating one plot from another. It is cultivated all

over India, especially near the city markets. The

botanical name of radish is Raphanus sativus. The

enlarged edible roots are fusiform and differ in

colour from white to red. There are two distinct

genetical groups in radish. The Asiatic varieties,

which are primarily for tropical climates, produce

edible roots in the first season and seed in the second

season as a biennial crop. On the other hand, the

exotic or European varieties produce roots in the

plains of tropical and subtropical climate and seeds

in the hills of temperate climate. Moreover, farmers

of the district are unaware about improved verities

and package and practices released by different

research institutions. In order to enhance the

productivity of Radish KVK of East Kameng district

has conducted front line demonstration (FLD)

Programme with HYV of Radish along with

improved package and practices.


The investigation was carried out to Front line

demonstration (FLD) programme was conducted on

Radish in five villages viz. New Sopung, Pampoli,

Wessang, Sngrikwa and Jayanti of East Kameng

district including twenty five numbers farm and

farm women family in an around 2 ha of land. The

Front line demonstration FLD is carried out in two

consecutive years i.e. 2016-17 and 2017-18 in the

farm land of same farm families. The main objective

of the programme was enhancement of productivity

through varietals intervention in turn improves the

farm income and to propagate the improved package

of practices in the district. In the programme, four

high yielding Radish varieties of 30 -45 days

duration viz., Arka Hansh and Arka Nishant released

from Indian Institute of Horticulture Research,

Benglor, Karnataka and Kashi Hansh and Kashi

sweta released from Indian Institute of Vegetable

Research, Varanasi Uttar Pradesh. All agronomic

measures were undertaken in each of the farmer’s

field from sowing to the crop harvesting by the KVK

scientist along with farmers. For comparative study

the HYV of Radish demonstration conducted with

proper package and practices nearby local check

varieties with farmers practices. Before and during

the demonstration period trainings were conducted

on HYV Radish cultivation, field day organized for

R

RESEARCH ARTICLE


44 MANOJ KUMAR SINGH, NARENDRA DEO SINGH, B.M. SINGH AND C.K. SINGH

popularizing the varietal performance against local

check, crop harvesting experiment conducted to find

out yield performance in presence of representative

of district agriculture officers, local leaders and

farmers and farm women.


Radish can be grown on nearly all types of soils, but

the best results are obtained on light friable loam soil

that contains ample humus. Heavy soils produce

rough, mis-shapen roots with a number of small

fibrous laterals and, therefore, such soils should be

avoided. The crop yield and yield attributing

characteristic were recorded during the experiment

such as Plant height (cm), Root length (cm), Root

diameter (cm), Number of Leaf/Plant and Yield/ha

(q) of each farmers plot against the local check.

Table 1. Yield attributing characteristics of high yielding varieties of Radish and local Radish variety (Average

data of 2016-17 and 2017-18)

Variety

Average plant

height (cm)

Average Root

length (cm)

Average Root

diameter (cm)

Average effective

no. of leaf/plant

Average root

weight (g)

Average

yield (q)

Arka Hansh 15.42 22 2.8 11 100-110 145

Arka Nishant 13.25 25 2.2 10 110-118 140

Kashi Sweta 14.02 28 3.5 12 120-140 150

Kashi Hansh 12.32 31 3.2 15 115-130 175

Local check 9.45 15 1.9 08 90-95 95

The Average plant height of Arka Hansh, Kashi

sweta, Arka Nishant and Kashi Hansh and local

check were recorded 15.42, 14.02, 13.25, 12.32 and

9.45 cm, respectively. Average Root length (cm) was

recorded highest against variety local check Kashi

Hansh (31) followed by Kashi Sweta (28), Arka

Nishant (25), Arka Hansh (22) and local check (15).

The Average Root diameter (cm) also was recorded

highest against local variety Kashi Sweta (3.5)

followed by Kashi Hansh (3.2), Arka Hansh (2.8),

Arka Nishant (2.2) and local check (1.9). The other

properties like Average effective number of

leaf/plant were recorded Kashi Hansh (15) followed

by Kashi Sweta (12), Arka Hansh (11), Arka Nishant

(10) and Local cheak (08). Also were recorded

Average root weight (g) highest was Kashi Sweta

(120-140), followed by Kashi Hansh (115-130), Arka

Nishant (110-118), Arka Hansh (100-110) and local

check (90-95). The Average yield (q) were highest

found Kashi Hansh (175), followed by Kashi sweta

(150), Arka Hansh (145), Arka Nishant (140) and

local cheak (95).

Table 2. Yield Performance of HYV and Local check varieties of Radish

Year Season Variety

No of

Farmers

Area

in ha

Demo

yield

(q/ha)

Yield of

local check

(q/ha)

Increase

in yield

(%)

2016-17 Ravi

Arka Hansh 06 0.08 145.0 98.0 25

Arka Nishant 06 0.08 140.0 95.1 24

Kashi Sweta 06 0.08 150.0 97.2 30

Kashi Hansh 07 0.08 175.0 96.5 35

Total/average 25 2.00 610.0 386.8 114

2017-18 Ravi

Arka Hansh 06 0.08 142.0 97.0 24

Arka Nishant 06 0.08 138.0 98.2 25


Kashi Sweta 06 0.08 151.0 95.4 29

Kashi Hansh 07 0.08 177.0 95.9 33

Total/average 25 2.00 608.0 386.5 111

It is observed from Table 2 that in both the years,

Kashi Hansh variety was recorded highest yield

followed by variety Arka Hansh, Arka Nishant and

Kashi Sweta as compared to yield of local check

variety in both the years. Table revealed that the

average yield of demonstrated varieties was 610 q/ha

against 386.8 q/ha of local check varieties and

increase in yield was 35%. Among the HYVs, Kashi

hansh variety was recorded the highest yield (175

q/ha) followed by Kashi sweta (150 q/ha), Arka

Hansh (140 q\ha) and Arka Nishant (140 q/ha).

Table 3. Economic performance of HYV and Local check varieties of Radish

Year Crop

Av. Cost of cultivation

Rs./ha

Av. Gross return

Rs./ha

Av. Net return Rs./ha Benefit cost ratio

Demo Local Demo local Demo Local Demo Local

2016

Arka Hansh 90750 95000 180000 150000 89250 55000 1.98 1.57

Arka Nishant 85450 82000 178000 142000 92550 60000 2.08 1.73

Kashi Sweta 85450 80000 185000 145000 99550 65000 2.16 1.81

Kashi Hansh 85450 75145 190000 135452 104550 60307 2.22

1.80

Average 347100 332145 733000 572452 385600 240307 8.44 6.91

2017

Arka Hansh 90750 94000 180000 150000 89250 59589 1.98 1.59

Arka Nishant 85350 82000 178245 141589 92895 59456 2.08 1.72

Kashi Sweta 85350 80000 184750 145000 101400 65000 2.21 1.81

Kashi Hansh 85000 75000 189690 135000 104690 60000 2.23 1.80

Average 346450 331000 732685 571589 388235 244045 8.5 6.92

The economic analysis of demonstration showed that

variety Kashi Hansh showed highest average gross

return (Rs. 190,000) followed by variety Kashi Sweta

(Rs. 185000), Arka Hansh (Rs. 180000) and Arka

Nishant (Rs. 178000). The variety Kashi Hansh

recorded the highest average net return (Rs. 104550)

followed by variety Kashi Sweta (Rs. 99550), Arka

Nishant (Rs. 92550) and Arka Hansh (Rs. 89250).

Benefit cost ratio was also found to be the highest in

variety Kashi Hansh (2.22) followed by var. Kashi

Sweta (2.16), Arka Nishant (2.08) and Arka Hansh

(1.98). Although among the HYVs the yield was

recorded to be the lowest in case of Arka Nishant,

due to its fine root quality the price of the produce is

higher than the other two varieties leading to higher

benefit cost ratio and net return of the variety Kashi

Hansh. (Table 3)

Front Line Demonstration on high yielding varieties

of radish showed that the variety Kashi hansh, Kashi

Sweta, Arka hansh and Arka Nishant were superior

over the local check variety in terms of yield and

yield attributing characteristic and the duration of

HYV were almost same with local check and the

varieties were preferred by the farmers. From the

economic point of view too, the farmers found the

varieties suitable for enhancement of their economy.

The farmers have started growing these varieties in

their farm. The seeds of these varieties have been

multiplied in the KVK demonstration farm and

distributed to the farmers for large scale adoption and

also supplied to the DDA and HDO Office of the

district for popularizing the varieties through further

demonstrations in different parts of the district. The

consistent good results of almost all of the

parameters had given comfortable yields both for

plot and total tuber yield from the rest of the

treatment.

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*Corresponding Author ________________________________________________ Journal of Plant Development Sciences Vol. 12(1) : 47-49. 2020

EFFECT ON PRODUCTION AND PROFITABILITY OF HYBRID RICE (ORYZA

SATIVA L.) THROUGH NUTRIENT MANAGEMENT PRACTICES

Kishan Singh, D.K. Gupta*, V.K. Singh, A.K. Paliwal and N. Chouksey

Raj Mohini Devi College of Agriculture and Research Station, Ambikapur (C.G.), India



Abstract: The field experiment was conducted at Research-cum-instructional farm of Raj Mohini Devi College of Agriculture and Research Station, Ajirma, Ambikapur, Chhattisgarh during kharif 2018 to study the effect of “Effect on production and profitability of hybrid rice (Oryza sativa L.) through nutrient management practices”. The experiment was laid out with 02 hybrid rice varieties as main plot (V1: IRH-103, V2: IRH-111.) and 05 nutrient management practices as sub plot T1- 100% RDF (Standard check),T2- 75% RDF through inorganic and organic {Topdressing of (Vermicompost @2q/ha+ DAP@ 25kg/ha) at 25-30 DAT and remaining NPK through inorganic},T3- 100% RDF through inorganic and

organic {Topdressing of (vermicompost @2q/ha+ DAP@ 25 kg/ha) at 25-30 DAT and remaining NPK through inorganic},T4- 150% RDF through inorganic and organic {Topdressing of (Vermicompost @2q/ha+ DAP@ 25 kg/ha) at 25-30 DAT and remaining NPK through inorganic},T5- 150% RDF in split plot design with four replications. The result revealed that hybrid rice variety IRH-103 on significantly higher grain yield (67.98q/ha), HI% (48.26 %) and test weight (24.21g) comprised to IRH-111. Among the nutrient management practices were significantly higher grain yield (65.11 q/ha), HI% (44.23 %) and test weight (24.46 g) on 150% RDF through inorganic and organic {Topdressing of (Vermicompost @2q/ha+ DAP@ 25 kg/ha) at 25-30 DAT and remaining NPK through inorganic} and statistically at par with 150% RDF through inorganic. In case of monetary higher gross return (184697.76`/ha), net return (138771.78`/ha) and

B: C ratio (3.02) were also observed in hybrid rice variety IRH-103 than IRH-111 and nutrient management practices application of 150% RDF through inorganic and organic {Topdressing of (Vermicompost @2q/ha+ DAP@ 25 kg/ha) at 25-30 DAT and remaining NPK through inorganic} recorded significantly higher gross return (177034.36`/ha), net return

(129526.86`/ha) and B: C ratio (2.73) and which was on par with 150% RDF through inorganic.

Keywords: Hybrid, Nutrient, Management practices, Rice

INTRODUCTION

ice (Oryza sativa L.) is one of the major

important cereal food grain crops of india in

terms of area, production and consumer demand.

India is the 2nd largest producer and consumer of rice

in the world. Rice is occupies the largest cropped

area of 43.90 million ha with annual production of

104.8 metric tonnes and productivity of 2.39 t ha-1

(Economic Survey India, 2016). Chhattisgarh is an

important rice growing state in eastern part of India.

In Chhattisgarh state rice occupies major area of 3.74

million ha out of 5.9 million ha area with productivity of 22.12 q/ha. (Anonymous, 2018). In

Chhattisgarh first hybrid variety Indira Sona

developed by IGKV in 2006. The current new

approaches such as new plant type, hybrid rice and

molecular biotechnology techniques only hybrid rice

seems to be better and viable approach because it

gives the minimum 10-15% yield advantage to the

best cultivated variety.


The field experiment was conducted during kharif

2018 at Research-cum-instructional farm of Raj

Mohini Devi College of Agriculture and Research

Station, Ajirma, Ambikapur, Chhattisgarh.

Geographically, Ambikapur is situated in the north of

Chhattisgarh.The climate of Surguja region is of sub-

humid with hot and dry summer and cold winter.

The average annual rainfall is about 1356 mm. The soil of experimental field was “Inceptisols”, slightly

acidic (5.7) in nature and medium in fertility status

having low N,, medium P2O5 and high K2O. The

experiment was laid out in split plot design with four

replications with 02 hybrid rice varieties as main plot

(V1: IRH-103, V2: IRH-111.) and 05 nutrient

management practices as sub plot (T1- 100% RDF

(Standard check),T2- 75% RDF through inorganic

and organic {Topdressing of (Vermicompost

@2q/ha+DAP@ 25kg/ha) at 25-30 DAT and

remaining NPK through inorganic},T3- 100% RDF through inorganic and organic {Topdressing of

(vermicompost @2q/ha+ DAP@ 25 kg/ha) at 25-30

DAT and remaining NPK through inorganic},T4-

150% RDF through inorganic and organic

{Topdressing of (Vermicompost @2q/ha+ DAP@ 25

kg/ha) at 25-30 DAT and remaining NPK through

inorganic},T5- 150% RDF through inorganic).


Yield attributes as well as grain yield of hybrid rice variety was significantly influenced by integrated

nutrient management sources (Table 1).The data

concluded to the grain yield of hybrid rice variety

IRH-103 was recorded significantly the highest grain

yield (67.98 q ha-1) and this was 11% higher grain

yield as compare to IRH-111 (54.88 q ha-1).

R

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48 KISHAN SINGH, D.K. GUPTA, V.K. SINGH, A.K. PALIWAL AND N. CHOUKSEY

A critical perusal of data revealed that the highest

grain yield of 65.11 q ha-1

was achieved with

application of 150% recommended dose of fertilizer

through organic and inorganic, which remained

statistically at par with 150% RDF through inorganic

(63.17 q ha-1

which was 6% higher than 100% RDF

through inorganic) . Next in order of grain yield

performance was 100% recommended dose of

fertilizer through organic and inorganic (60.29 q ha-1

)

followed by 100% RDF through inorganic-standard

check (59.48 q ha-1

) and 75% RDF through

inorganic and organic sources of nutrient (59.12 q/

ha-1

).

Table 1. Effect of nutrient management practices and hybrid rice varieties on Bundle weight (q ha-1

), grain yield

(q ha-1

) and straw yield (q ha-1

).

Treatment Bundle weight

(q ha-1)

Grain yield

(q ha-1)

Straw yield (q

ha-1)

Main plot-Variety (2)

V1- IRH-103 141.73 67.98 73.75

V2-IRH-111 140.73 54.88 86.25

SE(m) 2.77 0.96 1.96

C.D.5% N.S. 4.28 8.78

Sub plot-Nutrient management practices (5)

T1- 100% RDF (Standard check) 139.17 59.48 79.69

T2- 75% RDF through inorganic and organic

(Topdressing of {Vermicompost @2q/ha+ DAP@

25kg/ha} at 25-30 DAT and remaining NPK through

inorganic)

137.40 59.12 78.28


(Topdressing of {vermicompost @2q/ha+ DAP@ 25

kg/ha} at 25-30 DAT and remaining NPK through

inorganic)

139.27 60.29 78.98


(Topdressing of {Vermicompost @2q/ha+ DAP@ 25

kg/ha} at 25-30 DAT and remaining NPK through

inorganic)

146.93 65.11 82.82

T5- 150% RDF through inorganic 143.40 63.17 80.23

SE(m) 2.80 0.97 1.00

C.D.5% 8.44 2.83 3.03

Hybrid rice variety with nutrient management

practices also influenced the grain yield with

application of 150% RDF through inorganic and

organic with variety IRH-103 resulted in

significantly higher grain yield (72.08 q ha-1

) than

other combinations. However, the lowest grain yield

(52.71 q ha-1

) was associated with application of 100

% RDF through inorganic (T1) and 75 % RDF

through inorganic and organic (T2) with variety IRH-

111(53.13 q ha-1

) .

Better performance of combined use of organic

manures with chemical fertilizers might be due to

synergistic effect of inorganic fertilizer and organic

manures, as well as the slow release of nutrients

throughout the crop growth, thus helping to form

more photosynthesis and translocation the same from

source to sink and also the immediate release of N

and improved soil physical properties due to

application of organic manures and inorganic

fertilizer enhanced the crop growth and in turn yield

attributes of rice. This was evidenced by Banik et al.,

(2006) and Mondal et al., (2003).

In case of monetary among the different hybrid rice

variety IRH-103 also recorded (table 2) significantly

higher net return and B: C ratio (Rs. 184698, 138772

ha-1

and 3.02) over the IRH-111(Rs. 153456, 107530

ha-1

and 2.34). Treatments fertilized with either

inorganic or organic along with 75, 100 or 150%

RDF, significantly influenced the gross return, net

return and B:C ratio. The application of 150% RDF

through inorganic and organic recorded significantly

higher gross return, net return and B:C ratio (Rs.

177034, 129527 ha-1

and 2.73 respectively) being at

par with 150% RDF through inorganic (Rs.173760,

126833 ha-1

and 2.70). The lowest gross return, net

return and B:C ratio (Rs.163443,118529 ha-1

and

2.63) were obtained with 75% RDF through

inorganic and organic. The combination between

hybrid rice variety and nutrient management

practices on net return and B:C ratio were observed

in non-significantly influenced.


Table 2. Effect of hybrid rice varieties and nutrient management practices on cost of cultivation, gross return,

net return and B: C ratio. Treatment Cost of cultivation

(Rsha-1)

Gross return

(Rsha-1)

Net return

(Rsha-1)

B:C

Main plot-variety (2)

V1- IRH-103 45925.98 184697.76 138771.78 3.02

V2-IRH-111 45925.98 153456.35 107530.39 2.34

SE(m) 2707.59 2707.61 0.06

C.D.5% 12104.55 12104.63 0.26

Sub plot-Integrated nutrient management (5)

T1- 100% RDF (Standard check) 44500 164635.38 120135.38 2.70


(Topdressing of {Vermicompost @2q/ha+ DAP@ 25kg/ha} at 25-30 DAT and remaining NPK

through inorganic)

44913.99 163442.56 118528.61 2.63


(Topdressing of {vermicompost @2q/ha+ DAP@ 25 kg/ha} at 25-30 DAT and remaining NPK through

inorganic)

45781 166512.90 120731.90 2.64

T4- 150% RDF through inorganic and organic (Topdressing of {Vermicompost @2q/ha+

DAP@ 25 kg/ha} at 25-30 DAT and remaining NPK

through inorganic)

47507.5 177034.36 129526.86 2.73

T5- 150% RDF through inorganic 46927.4 173760.08 126832.68 2.70

SE(m) 2213.70 2213.69 0.03

C.D.5% 6463.07 6463.05 0.09

REFERENCES

Anonymous (2018). Chhattisgarh main vibhinna

faslon ke antargat khestrafal awam utpadakta , krishi

darshika, IGKV, Raipur:4.

Banik, P., Ghosal, P.K., Sasmal, T.K.,

Bhattacharya, S., Sarkar, B.K. and Bagchi, D. K. (2006). Effect of organic and inorganic nutrients for

soil quality conservation and yield of rainfed low

land rice in sub-tropical plateau region. Journal of

Agronomy and Crop Science. Vol.192(5): 31–43.

Economic, Survey (2016). Economic

survey,Government of IndiaMinistry of Finance.

Department of Economic Affairs.Economic

Division.09 January 2016. Oxford University

Press.New Delhi.

Mondal, S.S., Sitamgshu, S., Aruoghosh, Das, J. (2003). Response of summer rice (Oryza sativa L.)

to different organic and inorganic sources of

nutrients. Crop Research. Vol.25:219-222.

50 KISHAN SINGH, D.K. GUPTA, V.K. SINGH, A.K. PALIWAL AND N. CHOUKSEY



HERITABILITY AND GENETIC ADVANCE STUDIES FOR GRAIN YIELD AND

RELATED ATTRIBUTES IN HUSKED BARLEY (HORDEUM VULGARE L.)

Arun Kumar Singh* and Javed Ahmed Siddiqui

Department of Botany, D.A-V College, Kanpur- 208001 (U.P.)

Received-02.01.2020, Revised-21.01.2020 Abstract : Twelve husked barley strains were intermated in diallel fashion, excluding reciprocals. Parents alongwith F1s and

F2s were evaluated for plant height, days to reproductive phase, productive tillers per plant, length of spike, grains per

spike, spikelets per spike, biological yield per plant, harvest index, grain yield per plant, grain weight per spike and 1000-

kernel weight. The heritability and genetic advance were estimated for all the attributes in narrow sense using genetic

components. High heritability (more than 30%) was observed for plant height, days to reproductive phase, grains per spike,

spikelets per spike and harvest index in both the generations and for grain yield per plant in F1 and biological yield per plant

in F2 generation. Moderate heritability (10 to 30 %) was noticed in productive tiller per plant, length of spike and 1000-

kernel weight in both the generations and grain weight per spike in F2 generation. Low heritability (less than 10%) was

exhibited in grain weight per spike in F1 generation. An advancement of 6.98 g based on F1 and 5.92 g based on F2 were

expected per cycle of selection for grain yield per plant. For 1000-kernel weight it was approximately 3 g. The expectation

for advancement in grain weight per spike and length of spike was quite meager. Considering comparative genetic

advancement in percentage over mean, maximum advancement to the tune of, approximately, 42% was estimated for grains

per spike, where as an approximation of 22-25% of mean were estimated for plant height, days to reproductive phase,

harvest index and grain yield per plant. Genetic advance is conforming to the heritability estimates. In order to achieve

expected genetic advance, the attributes which are highly heritable (above 30%) may be improved through progeny selection

whereas, the attributes like grain weight per spike for which heritability estimates were moderate, hence bulk selection

followed by progeny selection would be appropriate. Considering heritability estimates, the economic attribute like grain

yield it was moderate to high quantified the involvement of non additive gene action in considerable proportion. Hence for

improvement in grain yield the progeny selection followed by biparental mating would be appropriate.

Keywords: Barley, Hordeum vulgare L., Heritability, Genetic advance, Grain yield

INTRODUCTION

arley (Hordeum vulgare L.) is the oldest crop of

the World's Agriculture. It was the first cereal to

be domesticated in the Middle East around 9000

years ago. Its sanskrit name is depicted in Veda as

Yav and mentioned its uses in different religious

ceremonies revealing its cultivation in India since

ancient time.

Hordeum vulgare L., a diploid with 2n = 14

chromosomes is the only cultivated species which

has three distinct phenotypic forms, viz, two, four

and six-rowed based on ear morphology. Initially

these two forms were classified as two separate

species but now these have been grouped in to one

single species, i.e., Hordeum vulgare L.

It is easily digestible, having cool and diuretic effect

on the body. It is beneficial for the diabetic patients

and those suffering from stomach problems on

account of intestine ulcer. Feeding trials conducted

in Australia on birds, animals and human volunteers

indicated that barley base diet reduces the risk of

coronary heart disease by lowering down

cholesterol; β-glucon and water soluble fiber fraction

present in barley also lowers down the blood plasma

cholesterol.

Barley is an important crop of arid and semi arid

region and can thrive well under moisture stress

conditions. Moreover it can tolerate salinity and

alkalinity up to a greater extent. Therefore, this crop

has become a boon to the poor farmers surviving on

marginal and sub-marginal holdings. Keeping in

view, its utility and sustainable productivity under

stress environmental conditions, adoption of

appropriate breeding methodology, so as to achieve

anticipated advancement in productivity is of vital

significance.


In the present study twelve genetically diverse

genotypes of husked barley were inter mated in all

possible combinations excluding reciprocals. The

parents along with F1s and F2s progenies were

evaluated in a Randomized Block Design with three

replications. Single row of parents and F1s and two

rows of F2s were sown during (2017-18). Inter plant

spacing was maintained at 3cm in a row of 5m

length. All the required agronomical practices were

adopted to grow a good crop. The observations on

grain yield and related parameters viz., plant height,

days to reproductive phase, productive tillers per

plant, length of spike, grains per spike, spikelets per

spike, biological yield per plant, harvest index, grain

yield per plant, grain weight per spike and 1000-

kernel weight on five plant basis in parents and F1s

where as In F2s on 20 plants basis were recorded.

The mean were subjected to various statistical and

biometrical analyses as per Hayman, B. I. (1954)

The heritability based on genetic components was

B

SHORT COMMUNICATION

52 ARUN KUMAR SINGH AND JAVED AHMED SIDDIQUI

worked out according to the method suggested by

Crumpacker, D.W. and R.W. Allard (1962) and

genetic advance according to Robinson et al. (1955).

Table 1. Heritability and genetic advance estimates for yield related attributes in F1 and F2 generation of barley. Characters Mean (X) Heritability

(narrow senses)

%

Genetic advance Genetic advance

in % over mean

F1 F2 F1 F2 F1 F2 F1 F2

Plant height (cm) 90.63 89.77 66.13 58.04 18.85 17.62 20.79 19.62

Days to reproductive phase 47.23 45.71 47.99 53.43 10.77 11.02 22.80 24.10

Number of tillers per plant 18.28 17.489 20.84 14.14 1.96 1.78 10.72 10.18

Length of the main spike (cm) 9.79 9.08 15.58 14.55 1.72 0.38 17.56 4.18

Number of grains per main spike 54.29 55.40 31.62 38.55 22.78 24.26 41.95 43.79

number of spikelets per main spike 22.37 20.71 43.38 30.22 4.46 3.67 19.93 17.72

Biological yield per plant (g) 83.00 76.95 24.23 31.36 11.05 12.51 13.31 16.25

Harvest index (%) 37.60 34.42 41.93 41.44 8.86 8.94 23.56 25.97

Grain yield per plant (g) 31.02 26.55 37.90 28.09 6.98 5.92 22.50 22.29

Grain weight per main spike (g) 2.90 2.56 7.10 12.64 0.13 0.53 4.48 20.70

1000-kernel weight (g) 50.60 46.72 23.50 12.73 3.76 2.59 7.43 5.54


High heritability estimate i.e. more than 30% were

observed for plant height, days to reproductive

phase, grains per spike, spikelets per spike and

harvest index in both the generations and for grain

yield per plant in F1 and biological yield per plant in

F2 generation due to more contribution of additive

genetic components (Table-l ). The results are in

accordance with Vimal, S.C. and Vishwakarma, S.R.

(1998), Sinha, B.C. and Saha, B.C. (1999) and

Yadav et al. (2002) Moderate heritability (10-30%)

was observed for tillers per plant, length of main

spike and 1000-kernel weight in both the generations

and grain weight per spike in F2 generation which

were in accordance with the reports of Bouzerzour,

H. and Djakoure (1998) A. The contribution of non-

additive components was significant for controlling

the traits like grain weight per spike in F1 generation

as evident from low heritability in F1 generations

(7.10%). This finding follows the results reported by

Sinha, B.C. and Saha, B.C. (1999), Yadav et al

(2015), Raikwar et al (2014), Manoj Kumar et al

(2013) and Ajeet Pratap Singh (2011).

The genetic advance for 5% selection intensity

showed that an advancement of 6.98 g based on F1

and 5.92 g based on F2 were expected per cycle of

selection for economic attribute like grain yield per

plant. Accordingly for 1000-kernel weight an

advancement of approximately 3 g was also

estimated. The expectation for advancement in grain

weight per spike and length of spike was quite

meager. Considering genetic advancement in

percentage over mean, maximum advancement to the

tune of, approximately, 42% was estimated for

grains per spike where as an approximation of 22 to

25% gain was estimated for plant height, days to

reproductive phase, harvest index and grain yield per

plant. However, meager gain (below 10%) was

recorded for grain weight per spike in F1, length of

spike in F2 and for 1000- kernel weight in both the

generations. Genetic advance is conforming to the

heritability, though in certain cases it differs due to

phenotypic standard deviation. Number of grains per

main spike was observed as most important character

while going for selection for high grain yield. The

attributes which are highly heritable may be

improved through progeny selection where as the

attributes like grain weight per spike are required to

be subjected for bulk selection followed by progeny

selection.

Considering heritability estimates, the economic

attribute like grain yield, was moderate to high

quantify the involvement of non additive gene action

in considerable proportion. Hence for improvement

in grain yield, the progeny selection followed by

biparental mating would be appropriate.

REFERENCES

Yadav, et al. (2015). Genetic variability and direct

selection criterion for seed yield in segregating

generations of Barley (Hordeum vulgare L.).

American journal of plants sciences 6 (09), 1543,

2015.

Raikwar, R.S., Upadhyay, A.K. and Tyagi, P.K. (2014). Heritability and genetic variability for yield

component under two regimes of soil in barley

(Hordeum vulgare L.). The bioscan 9 (4), 1613-

1617, 2014.

Kumar, Manoj, Vishwakarma, Siyaram,

Bhushan, Bharat and Kumar, Arun (2013).

Estimation of genetic parameter and character

association in barley, Journal of Wheat Research 5

(2), 2013.

Singh, Ajeet Pratap (2011). Genetic variability in

two – rowed barley (Hordeum vulgare L.). Indian

journal of Scientific Research 2 (3), 21-23, 2011.

Yadav, V.K., Ram, L., Kumar, R. and Singh, S.P.

(2002). Genetics of yield components and some

malting attributes in barley. (Hordeum Vulgare L.)

Prog. Agric. 2 (1) :14-18 .


Sinha, B.C. and Saha, B.C. (1999). Genetic studies,

hertability and genetic advance in barley (Hordeum

vulgare L.). Journal- of-Applied-Biology. 9 (2) :

108-116.

Vimal, S.C. and Vishwakarma, S.R. (1998).

Hertability and genetic advance in barley under

partially reclaimed saline sodic soil. Rachis. 17 : 1-2,

56-57.

Bouzerzour, H. and Djakoure, A. (1998).

Inheritance of grain yield and grain yield

components in barley. Rachis, 16 (1-2): 9-16.

Crumpacker, D.W. and Allard, R.W. (1962). A

diallel cross analysis of heading date In Phaseolus

vulgaris L. variety cross. Crop Set. 5 : 17-18.

Robinson, H.F., Comstock, R.E., Khalil, A. and

Harvey, P.H. (1955). Dominance verses, over

dominance in heterosis: evidence from cross

between open pollinated varieties of maize, Amber

Natt. 90 : 127-13l.

Hayman, B.I. (1954). The theory and analysis of

dialle 1 crosses. Genetics, 39: 789-803.

54 ARUN KUMAR SINGH AND JAVED AHMED SIDDIQUI



EFFECT OF DIFFERENT VARIETIES AND PLANTING METHODS ON

GROWTH, YIELD AND QUALITY OF SUGARCANE UNDER NORTHERN HILL

ZONE OF CHHATTISGARH

Ramakant Singh Sidar*, S.S. Tuteja1 and V.K. Singh

Department of Agronomy, RMD College of Agriculture and Research Station,

Ambikapur (C.G.) – 497001 1College of Agriculture Raipur, Indira Gandhi Krishi Vishwavidyalaya, Raipur (C.G.)



Abstract: A field experiment was conducted during cropping seasons of 2015–16 and 2016-17 at Instructional cum

research farm RMD CARS Ambikapur to evaluate sugarcane mid–late varieties (Co 86032,Co 62175, CoT 8201) under 12

treatment combinations related to three sugarcane varieties viz.(V1), CoT 8201, (V2), Co-86032, (V3), Co 62175 in main

plots and four planting methods (P1) Flat planting at 75 cm row spacing (P2) Flat planting at 90 cm row spacing (P3)

Trench planting at 75 cm(P4) Pit planting in sub plot were tested in split plot design with three replication. The result on

sugarcane varieties exhibited no significant variation on growth attributes viz. Germination percentage, cane height, No. of

shoots, No. of nodes, length of nodes, and yield attributes viz. No. of millable cane, cane weight, and cane yield were the

highest with Co 86032 (V2). Quality parameters were non-significant due to variety. Among the planting methods, pit

planting (P4) recorded maximum cane yield (96.74 t ha-1) Highest NMC was (84.54x 10-3 ha-1) under pit planting method.

The sugarcane quality parameters in terms of pol %, purity %, Brix % were no significant variations due to various planting

methods and varieties. In case of economics, gross income (Rs 290090 ha-1) and maximum net income (Rs 215862 ha-1) in

pit planting and benefit cost ratio (3.07) was registered under (P1) Flat planting at 75 cm row spacing.

Keywords: Sugarcane, Planting method, Chhattishgarh

INTRODUCTION

ugarcane is an important cash crop grown in

India an area of 47.74 lakh hectares with an

annual production of 3550 lakh tonnes and the

average productivity is 74.41 t ha-1

. In Chhattisgarh,

it occupies an area of 0.30 lakh ha, with the

production of 12.47 lakh tones and productivity is

41.6 t ha-1

(Anonymous 2018). Despite all the

attempts, productivity of sugarcane in state is quite

less than the national productivity.

Sugarcane (Saccharum spp.) crop occupies an

important position in Indian agriculture, as it is the

second largest organized agro-industry in the

country, next only to textiles. Recently the plateauing

yield levels and increasing cost of producing

sugarcane has posed serious concerns on the

sustainability of this crop. Determination of precise

planting technique to improve uniformity in plant

population and crop stand is an important issue for

improving the sugarcane-system productivity.

Planting method plays a crucial role in sustaining

higher number of millable canes and sugarcane yield

in both plant and ratoon crops. The variation in

planting techniques in different regions aims to

improve the growth, increase the plant density and

reduce the tiller mortality to obtain higher number of

heavier millable canes per unit area. In North India,

spring sugarcane is generally planted on flat beds in

single rows spaced 75 cm apart. However, planting

of sugarcane in paired rows compared with that in

planting in single rows has proved beneficial in India

(Yadav et al., 1997)


An experiment was conducted during spring seasons

of 2016 and 2017 at Instructional farm, RMD

College of agriculture and research station

Ambikapur to find out the suitable mid late varieties

with integrated nutrient management for northern hill

zone of Chhattisgarh condition. The soil was sandy

loam in texture, acidic in reaction pH 5.6, 0.33%

organic carbon, 195.5, 8.3 and 276.0 kg/ha available

N, P and K, respectively. To evaluate sugarcane

mid–late varieties under 12 treatment combinations

related to three sugarcane varieties viz.(V1), CoT

8201, (V2), Co-86032, (V3), Co 62175 in main plots

and four planting methods (P1) Flat planting at 75

cm row spacing (P2) Flat planting at 90 cm row

spacing (P3) Trench planting at 75 cm(P4) Pit

planting in sub plot were tested in split plot design

with three replication during spring season. Urea,

Single super phosphate and muriate of potash were

taken as sources of nitrogen, phosphorus and

potassium, respectively. Full dose of P and K were

applied as basal at the time of planting and full N in

two equal splits during first and second earthling up

during both the seasons in each year. The sugarcane

was planted in second week of February during

spring season respectively and harvested on second

week of February during both the years. The mean

rainfall received during the crop growth period was

S

SHORT COMMUNICATION


56 RAMAKANT SINGH SIDAR, S.S. TUTEJA AND V.K. SINGH

mm.1223.23.Cane juice was extracted with power

crusher machine and juice quality was estimated as

per method given by Spencer and Meade (1955). Net

returns was calculated by deducting the total cost of

cultivation from the gross returns for each treatment

and expressed as per hectare on the basis of cost of

inputs and prices of outputs in experimentation year.

The benefit: cost ratio was calculated as ratio of

gross return to cost of cultivation.


The data pertaining those different varieties of

sugarcane had no significant effect on germination

percentage. Sugarcane variety ‘Co-86032’ had

recorded the highest germination per cent (65.97%)

at 45 DAP. Among the planting methods

significantly highest germination per cent (65.74)

was recorded with pit planting at 45 DAP. The

variation in germination percentage was owing to

chemical composition of soluble solids in juice as

well as enzymes and hormones present in cell sap,

which varies from genotype to genotype. Sugarcane

variety ‘Co 86032’ showed significantly highest

number of shoots (121.34 x103 ha

-1) at 120 DAP but

it was comparable to ‘Co 62175’ (120.32 x103 ha

-1)

and CoT 8201 (119.60 x103 ha

-1).

Planting methods had significant influence on

number of shoots. Highest numbers of number of

shoots (122.74 x103 ha

-1) at 120 DAP was recorded

under pit planting. While lowest under flat planting

at 90 cm row spacing. Highest numbers of number of

shoots (122.74 x103 ha

-1) at 120 DAP was recorded

under pit planting. The variation in number of tillers

among different variety might be due to genetic

characters of varieties. Sinare et al. (2006) also

observed higher number of tillers at closer row

spacing this might be due to higher dose of chemical

fertilizers which increased the population of tillers

due to immediate and quick supply of plant nutrients.

The highest cane girth (8.36 cm) and average cane

weight (2.56 kg cane-1

) was recorded under pit

planting found significantly superior over rest of the

treatments assured and efficient utilization of

nutrients to sugarcane for growth and development.

This result is agreement with the finding of

Manickam et al. (2008).Improvement in average

diameter of cane was due to increased metabolic

processes in plant, resulting in greater metabolic

activity thereby improving the sink size which

manifested in to thicker canes.

Table 1. Growth yield attributes of sugarcane as influenced sugarcane varieties and nutrient management

Treatment Germi

nation

(% ) at

45DAP

No. of

shoots

(x103

ha-1

)

Cane

girth

(cm)

Cane

weight

(kg cane-1

)

NMC

( x 10-

3 ha

-1)

Cane

yield

(t ha-1

)

Varieties

V1 CoT 8201 65.26 119.60 8.23 2.33 81.11 92.22

V2 Co 86032 64.74 121.34 8.31 2.63 82.96 94.63

V3 Co 62175 64.97 120.32 8.29 2.56 82.28 93.20

SEm± 0.45 0.65 0.08 0.01 0.51 1.37

CD (P=0.05) NS NS NS 0.04 NS NS

Planting methods

P1 Flat planting at 75 cm row spacing 64.45 119.44 8.20 2.40 82.42 90.68

P2 Flat planting at 90 cm row spacing 63.72 118.70 8.24 2.49 77.19 89.84

P3 Trench planting at 75 cm row

spacing 66.06 122.74 8.31 2.53

83.85 96.18

P4 Pit planting 65.74 120.88 8.36 2.56 84.54 96.70

SEm± 0.46 0.67 0.06 0.02 1.39 1.45

CD (P=0.05) 1.38 1.99 NS 0.05 4.12 4.30

The data pertaining to cane yield (94.63 t ha-1

) was

recorded by Co 86032 found superior over Co 62175

and CoT 8201. Pit planting of sugarcane recorded

highest NMC was (84.54x 10-3

ha-1

) and significantly

higher cane yield (96.70 t ha-1

) at par with trench

planting at 75 cm spacing. Sugarcane variety had

different potentialities and hence caused significant

variation in cane yield. This may be due to inherent


superiority of various growth characters and

assimilating apparatus in some varieties.

Performance of different varieties with variation in

the yield was reported by kadam et al. (2008).

Table 2. Quality prameters and economics of sugarcane as influenced sugarcane varieties and planting methods

Treatment Brix (%) Pol (%) Purity

(%)

Net return

(Rs ha-1

)

B. C.

ratio

Varieties

V1 CoT 8201 18.53 15.52 83.85

208217 2.91

V2 Co 86032 18.60 15.66 84.17

213932 3.01

V3 Co 62175 18.56 15.53 83.95

210167 2.95

SEm± 0.25 0.05 1.15

3295.08 0.06

CD (P=0.05) NS NS NS NS NS

Planting methods

P1 Flat planting at 75 cm row spacing 18.54 15.51 83.85

211302 3.07

P2 Flat planting at 90 cm row spacing 18.53 15.40 84.17

203802 2.94

P3 Trench planting at 75 cm row spacing 18.58 15.57 83.95

212122 2.96

P4 Pit planting 18.60 15.57 83.85

215862 2.85

SEm± 0.30 0.06

1.15 5811.89 0.06

CD (P=0.05) NS NS NS

17260.46 0.18

Varieties of sugarcane influences non significant

variation in juice quality with respect of brix

percentage, pol percentage, and purity percentage.

Among the varieties showed highest brix (18.60%),

pol (55.66%) purity (84.17%) was recorded under

variety Co 86032. This might be due to genetic

ability of this variety due to accumulate more sucrose

in juice.

Sugarcane ‘Co 86032 recorded significantly higher

net returns (Rs 213932ha-1

) and benefit: cost ratio

(3.01). Pit planting recorded highest net return.

While lowest B:C ratio under flat planting at 75 cm

row spacing.

CONCLUSION

It concluded that highest net return under pit planting

and B: C ratio under flat planting at 75 is the best

option to achieving the productivity and profitability

of sugarcane.

REFERENCES

Anonymous (2018). Ministry of Agriculture and

Farmers Welfare,Government of India

Kadam, B.S., More, S.M., Veer, D.M. and Nale,

V.N. (2008). Response of promising sugarcane

genotypes with different levels of nutrients under

vertisol for south Maharashtra. Cooperative Sugar,

40(2): 51-54.

Manickam, G., Panneerselvam, R., Jayachandran,

M., Karunanidhi, K. and Rajendran, B. (2008).

Effect of varied levels of NPK fertilization on growth

and yield of sugarcane (Saccharum officinarum)

genotypes. Cooperative Sugar, 39(9): 35-37.

Sinare, B. Sinha, U. P., Singh, H. and Singh, B. K. (2005). Effect of genotypes and fertility levels on

growth, yield and quality of sugarcane under rainfed

condition. Indian Sugar, 55(7): 23-26.

Spencer, G.L. and Meade, G.P. (1964). Cane sugar

handbook, Edition 2nd, p. 433-437. John Wiley and

Sons.

Virdia, H. M. and Patel, C.L. (2010). Integrated

nutrient management for sugarcane (Saccharum spp.

hybrid complex) plant-ratoon system. Indian Journal

of Agronomy, 55 (2): 147-151.

Yadav, R.L., Singh, R.V., Signh, R. and

Srivastava, V.K. (1997). Effect of planting

geometry and fertilizer N rates on nitrate leaching,

nitrogen use efficiency and sugarcane yield. Tropical

Agri., 74(2): 115-120.

58 RAMAKANT SINGH SIDAR, S.S. TUTEJA AND V.K. SINGH

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