Journal of Agricultural Science and Practice - IRJ -...

Third Quarter E-Book Volume 2: July-September 2017

ISSN: 2536-7072

Journal of Agricultural Science and Practice

ABOUT JASP

Journal of Agricultural Science and Practice (JASP) (ISSN: 2536-7072) is an Open Access, Peer-Reviewed Journal that publishes original and high-quality research articles in all areas of Agricultural Science. The Journal is committed to advancing and sharing creative, innovative and emerging ideas that will influence Agricultural policy and improve food sufficient around the world. The articles published in JASP will be of interest to Researchers, Government agencies and International organizations. JASP publishes per article and e-books every quarter. All published articles and e-books are freely accessible on our website. Editorial Office: [email protected] Customer Care: [email protected] Submit Articles: [email protected] Website: http://www.integrityresjournals.org

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Editors

Dr. Roslan bin Ismail Department of Land Management Faculty of Agriculture Universiti Putra Malaysia 43400 UPM Serdang, Selangor,Malaysia Dr. Lee Seong Wei Faculty Agro Based Industry Universiti Malaysia Kelantan Jeli Campus Jeli, 17600, Kelantan, Malaysia Prof. Ehab Abdel Haleem Elsayad Soils & Water Department Fayoum Faculty of Agriculture Fayoum University, Egypt Dr. Nagham Rafeek Ibrahim El Saidy Department of Hygiene & Preventive Medicine Faculty of Veterinary Medicine Kafer Elshikh university, Egypt Dr. Josiah Chidiebere Okonkwo Department of Animal Science and Technology Faculty of Agriculture Nnamdi Azikiwe University P.M.B 5025 Awka, Anambra State, Nigeria Assoc. Prof. Mohammad Reza Alizadeh Department of Agricultural Engineering Rice Research Institute of Iran (RRII) Agricultral Research, Education and Extension Organization (AREEO) P.O. Box: 41996-13475, Rasht, Iran

Prof. (Dr.) Mahendra Pal Ex-Professor of Veterinary Public Health College of Veterinary Medicine Addis Ababa University, Ethiopia Current Address: Flat No, 4, Aangan I Apartment Jagnath-Ganesh Dairy Roade Anand 388001, Gujarat, India Assoc. Prof. Elena Kistanova Institute of Biology and Immunology of Reproduction, BAS 73 Tzarigradsko shose, 1113 Sofia, Bulgaria Assoc. Prof. Dr. Kulaksız Recai Department of Reproduction and Artificial Insemination University of Balıkesir, Turkey

Table of Content: Volume 2: July – September 2017

Articles Pages

Assessment of suitability of facilities and competence of Higher National Diploma graduates in cattle production in College of Agriculture Lafia, Nasarawa State, Nigeria Garba Emmanuel Ekele

47-53

Inducing salt tolerance in wheat through inoculation with rhizobacteria containing 1-aminocyclopropane-1-carboxylate deaminase activity Muhammad Arshad Ullah, Syed Ishtiaq Hyder, Imdad Ali Mahmood, Tariq Sultan and Lal Badshah

54-57

Performance of cowpea (Vigna unguiculata (L.) Walp) under irrigation as influenced by weed management methods and intra row spacing Na-Allah M. S., Mukhtar A. A., Mahadi M. A., Tanimu M. U. and Muhammad A.

58-65

Economic analysis of Yam-Cowpea intercropping system in Obi Local Government Area, Nasarawa State, Nigeria Onuk E. G., Girei A. A., Ohen S. B. and Alaga M. H.

66-73

Identifying the potential of some heavy metals toxicity in urban and peri-urban cropping systems in Sierra Leone Abdul Rahman Conteh, Alusaine Edward Samura, Emmanuel Hinckley, Osman Nabay and Mohamed Saimah Kamara

74-85

Proximate composition of rumen digesta from sheep slaughtered in Zuru Abattoir, Kebbi State, Nigeria A. M. Sakaba, A. U. Hassan, I. S. Harande, M. S. Isgogo, F.A. Maiyama and B. M. Danbare

86-89

Journal of Agricultural Science and Practice Volume 2. Page 47-53. Published 31st July, 2017

ISSN: 2536-7072. Article Number: JASP-16.06.17-053 www.integrityresjournals.org/jasp/index.html

Full Length Research

Assessment of suitability of facilities and competence of Higher National Diploma graduates in cattle

production in College of Agriculture Lafia, Nasarawa State, Nigeria

Garba Emmanuel Ekele

Department of Agricultural Education, Federal University of Agriculture, Makurdi, Benue State, Nigeria. Email: [email protected].

Copyright © 2017 Ekele. This article remains permanently open access under the terms of the Creative Commons Attribution License 4.0, which

permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Received 16th June, 2017; Accepted 12th July, 2017

ABSTRACT: The purpose of this study was to assess the suitability of facilities and competence of Higher National Diploma graduates in cattle production in College of Agriculture, Lafia, Nasarawa State-Nigeria. A survey research design was used for this study. Four research questions guided the study. The population of the study was 51 which consist of 33 HND students, 9 lecturers, 3 instructors and 6 farm supervisors. The entire population was used for the study. The instrument for data collection was structured questionnaire with 27 competence items in cattle production and checklist for facilities/equipment and tools in the college. The Cronbach Alpha method was used to determine the internal consistency of the instrument which yielded reliability coefficient of 0.83. Mean (x) and percentage were used to answer the research questions while checklist was employed to determine the adequacy of staff and availability/suitability of facilities/equipment. Findings from this study revealed that equipment/tools are grossly inadequate, graduates of HND animal production possesses low competency level in cattle production and that staff are inadequate for running the programme. It was therefore recommended amongst others that workshop and training be organized for graduates to improve their level of competency in cattle production. Key words: Competence, College of Agriculture, production, suitability. INTRODUCTION Educational programme need assessment for effectiveness. Assessment is the process of gathering information for the purpose of decision making. It involves the collection of information about an individual’s knowledge, skills, attitude, judgment, interpretation and using the data for taking relevant decisions about the individual, instructional process, curriculum or programme (Ugodulunwa, 2014). Educational assessment involves proper management of information, changes in what people learn, how they learn, where they learn and when they learn. This is often occasioned by emergent of technology which leads to changes in assessment process. These changes in mode of assessment according to Ekele (2013a) require that quality and competence of HND graduate be assured in assessment

at all levels of education including Higher National Diploma level. The National Board for Technical Education (2007) states that National Diploma animal production students must have obtained a good National Diploma to qualify for admission into Higher National Diploma in Animal production.

Animal production as explained by Ekele (2011) refers to husbandry of such livestock as cattle, sheep and goat, poultry and pig. The author affirms that it involves nutrition and management practices in livestock produc-tion. Competent HND graduates in animal production are expected to be functional by creating opportunities for employment especially in cattle production (NBTE, 2007).

As stated by Ekele(2013b), competency involves psyco- productive skills where students are exposed to practice

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48 J. Agric. Sci. Pract. of skills and are expected to perform these skills in occupation in which they are employed. Onu (1999) further asserts that competency based education places premium on the ability of the students to perform the specific tasks associated with the programme. Perfor-ming the tasks means that the facilities available have to be suitable for any meaningful acquisition of skills on the job. Suitability of facilities as reported by Nwachukwu (2006) are facilities, equipment and instructional materials that are appropriate in transmitting knowledge and skills to the learner. The author explained that facilities assist in transmitting informative ideas and make the ideas to be more explicit for teaching and learning. Consequently, it is imperative that facilities are not only adequate but suitable to be used in training students. Obioma (2006) echoed similar view that no matter the strength of manpower resources in educational institutions, educational process of teaching and learning must require enough suitable facilities and equipment. Unfortunately, students come in contact with facilities and equipment only during the supervised work experience scheme (Osinem and Nworji, 2010). This ultimately affects their competency and performance level.

The ability of graduate of animal production to perform well arises from a repetitive process in which skill holders engage in their jobs, and this becomes part of the individual to the extent the performance becomes automatic. Payne(1991) identified the following areas of competencies in cattle production to include making a hay and silage for cattle, establish pasture for grazing, cow calf operation and use of paddocks. The author states that deworming cattle, castration, steaming of cattle, use of dips, growing of stocks and skill in baby beef in production are also competencies required by graduates of animal production for successful occupation in livestock industry. Ekele (2014) also identified branding and tattooing as entrepreneurial skills required by farmers in cattle production. The author emphasized that branding is done for the identification of cattle. The practice of, and competence in steaming up cattle involves putting the cow on a special (rich) diet to set all the organs in good order for milk production after birth. This happens about eight weeks to calving.

In the opinion of Aduku and Ekele (2015), synchronization of oestrus is also an important skill which is a controlled inducement of ovulation in farm animal so that all or a greater proportion of the animals come on heat at the same period. This technique according to the authors plays an important role in the application of artificial insemination; crystalline progesterone can be used for the inducement. In the context of this study, graduate of animal production who found themselves in the world of work are expected to focus on cattle production. Thus, the suitability of the impacts that graduate make in relation to the requirements of the world of work depends on the competence exhibited on the job by graduates. The researcher observed after

preliminary investigation that faculties being used for training HND students are obsolete and may not be available or suitable for cattle production. This may have resulted to the incompetence of HND graduate of animal production as they could not raise cattle for profitable business. Further inquiry from the graduates as to why this situation exists revealed that the graduates tend to lay the blame on obsolete facilities and dearth of teaching staff. It becomes necessary therefore to assess suitability of facilities and level of competence of HND graduates in cattle production in College of Agriculture, Lafia, Nasarawa State, Nigeria. Specifically, the study determined the: 1. suitability of facilities for running animal production

programme in College of Agriculture. 2. adequacy and availability of facilities for running

animal production programme in College of Agriculture.

3. level of competence of HND graduates of animal production programme in cattle production.

4. adequacy of teaching staff (Lecturers and Instructors).

Research questions 1. How suitable are the facilities for running animal

production progamme in College of Agriculture? 2. How adequate are the available facilities for running

animal production progamme in College of Agriculture?

3. What is the level of competence of HND graduate of animal production in cattle production?

4. How adequate are the available teaching staffs for running animal production programme in College of Agriculture?

MATERIALS AND METHODS Descriptive survey design was adopted for this study. It was conducted in Lafia, Nasarawa State, Nigeria. Nasarawa State is located in North Central Nigeria. Descriptive survey was used because it describes the characteristic features or facts about a given population. The design is therefore appropriate for the study since it collects and analyzes data from lecturers in Colleges of Agriculture and HND II students. The population of the study is 51 made up of 33 HND students, 9 lecturers, 3 instructors, and 6 farm supervisors. No sampling was carried out, the entire population was used. The instrument for data collection was a structured questionnaire titled: ‘competence level of graduates in cattle production questionnaire (CGICPQ) and check list designed for the study: The questionnaire was used only for competency level of HND graduate while checklist

Ekele 49

Table 1. Mean and standard deviation of Lecturers, Instructors and Supervisors on the suitability of facilities for running animal production programme in College of Agriculture (N=18).

S/No Facilities Mean x SD Remarks

1 Beef cattle unit 3.81 0.59 Suitable

2 Dairy cattle unit 3.81 0.69 Suitable

3 Milking parlour 3.76 0.69 Suitable

4 Slaughter house 4.00 1.02 Suitable

5 Feed mill with accessories 3.86 0.46 Suitable

6 Silage pits 3.81 0.59 Suitable

7 Biological pH meters 1.63 0.61 Not Suitable

8 Goman dissecting sets 3.76 0.67 Suitable

9 Surgeons dissecting sets 3.85 0.44 Suitable

10 Rubber hand gloves 3.83 0.45 Suitable

11 Scalpels 3.76 0.59 Suitable

12 Bone breaker 2.02 0.50 Not Suitable

13 Astall hearson dryer 3.63 0.80 Suitable

14 Chance bovver dips 2.12 0.61 Not Suitable

15 Sterilizer/autoclave 3.85 0.48 Suitable

16 Dissecting trays 3.81 0.56 Suitable

17 Dissecting boards 3.76 0.67 Suitable

18 Desiccators 3.78 0.66 Suitable

19 Light weight stereoscope 3.80 0.63 Suitable

20 Post mortem knife 3.85 0.48 Suitable

21 Scapula knives 3.83 0.58 Suitable

22 Long scissors 3.81 0.62 Suitable

23 Curved scissors 3.85 0.48 Suitable

24 Long forceps 3.81 0.53 Suitable

25 Scalpel holder 3.78 0.55 Suitable

26 Aluminium equipment tray 3.85 0.40 Suitable

27 Automatic syringes 3.73 0.68 Suitable

28 Microscope binocular 3.81 0.43 Suitable

29 Pocket hand lenses 3.83 0.41 Suitable

30 Disposable syringes 3.80 0.54 Suitable

31 Glass syringes 3.86 0.46 Suitable

32 Deep freezers 3.85 0.44 Suitable

33 Refrigerators 3.8 0.40 Suitable

34 Electronics balances 3.73 0.60 Suitable

was used for adequacy of equipment/staff in the College of Agriculture. The questionnaire was subjected to face validation by three experts, two from the Department of Vocational Agriculture and Technology Education and one from Department of Animal Production all in the University of Agriculture, Makurdi. The internal consistency of the instrument was determined using Cronbach Alpha. A coefficient of 0.83 was obtained. Any item with mean value of 2.50 and above was considered high in competence, while any item with the mean value of less than 2.50 was considered low in competence. For availability, of facilities/tools/equipment, adequacy and availability of teaching staff, any item with 70% and above level of availability was considered as adequate and any item with less than 70% was considered

inadequate. Any item with mean value of 2.50 and above was considered suitable and below 2.50 not suitable. Mean (x) and percentages were used to answer the research questions. RESULTS Research question 1 How suitable and functional are the facilities for running animal production programme in College of Agriculture? Data presented in Table 1 revealed that the mean of thirty one (31) suitable facilities ranges from 3.76 to 4.00. The standard deviation ranged from 0.40 to 0.70

50 J. Agric. Sci. Pract.

Table 2. Number and percentage of Instructors’ response to available/tools, and equipment used for teaching animal production programme in College of Agriculture

S/No Equipment/tools Nos

Required Nos

Available Percentage

(%) Remarks

1 Artificial insemination equipment 2 0 0% Inadequate

2 Knapsack 5 1 20% Inadequate

3 Weighing balance 5 1 20% Inadequate

4 Ear notchers 2 0 0% Inadequate

5 Tattooing machine 2 0 0% Inadequate

6 Hoof trimmers 2 1 50% Inadequate

7 Burdizzo 6 1 50% Inadequate

8 Rubber bairds 30 5 16.6% Inadequate

9 Heaters and thermometers 10 2 10% Inadequate

10 Foot mails and floor brushers 2 1 50% Inadequate

11 Feed troughs and water trough 10 5 50% Inadequate

12 Small drinkers 10 6 60% Inadequate

13 Spraying equipment 2 1 50% Inadequate

14 Record books 2 2 100% Adequate

15 Designed forms and stamps 2 2 100% Adequate

16 Kjedahl digestion apparatus 2 0 0% Inadequate

17 Oven and kjedahl flask 2 1 50% Inadequate

18 Spectrophotometer (Atomic absorption) 2 0 0% Inadequate

19 Soxhlet apparatus 2 1 50% Inadequate

20 Flame photometer (calorimeter) 3 1 33.3% Inadequate

21 Syringe/needles 10 4 40% Inadequate

22 Microscopes 15 3 20% Inadequate

23 Slaughter’s slap & slaughter kit 5 2 40% Inadequate

24 Scape blade and prepared slides 10 3 30% Inadequate

25 Staining reagent and microscopic slides 10 2 20% Inadequate

26 Suture materials iodine 15 5 33.3% Inadequate

27 Drying equipments 6 1 16.6% Inadequate

28 Branding iron and stethoscope 2 1 50% Inadequate

29 Drenching gun and hoof trimmers 5 1 20% Inadequate

indicating that the respondents were not very far from the mean or one another in their responses. However, three facilities were rated not suitable (mean value fall below 2.50) namely Biological PH meters, Bone breakers and chance bovver dips. This could possibly be due to their non-functionality.

Research question 2

How adequate are the available facilities for running animal production programme in college of Agriculture? Data presented in Table 2 showed that of the 29 equipment/tools, only designed forms/stamps and record books were found adequate. The remaining 27 equipment/tools were inadequate in the college. These facilities scored below 70%, hence, they are inadequate.

Research question 3

What is the level of competence of HND graduates of

animal production in cattle production? Analysis of data as presented in Table 3 revealed that of the 27 competency items on cattle production, 13 (thirteen) were rated low (mean do not meet the cut-off point of 2.50), hence, the graduate have low competence in these items. 14 items have mean ranging from 3.16 to 3.44 which indicates that graduates possessed high competence in these items as rated by supervisors. The standard deviation (SD) ranged from 0.36 to 0.49, indicating that the respondents were not very far from the mean or one another in their responses. Research question 4 How adequate is the available teaching staff for running animal production programme in College of Agriculture? Data presented in Table 4 showed the availability and adequacy of teaching staff by checklist. All the categories of teaching staff for animal production were found

Ekele 51 Table 3. Mean and standard deviation of supervisors ratings on the level of competence of HND graduates of animal production in cattle production (N=6).

S/No Items competencies on cattle production Mean (x) SD Remarks

1 Formulate and balance cattle ration 3.33 0.48 High

2 Make hay and silage for cattle 3.33 0.48 High

3 Establish a pasture for grazing 1.33 0.48 Low

4 Cattle fattening and finishing 3.33 0.48 High

5 Constrict and use of silo in beef cattle production 3.33 0.46 High

6 Skill in baby beef production 3.22 0.42 High

7 Cow calf operation 1.16 0.38 Low

8 Growing of stockers 3.22 0.43 High

9 Use of paddocks, feed bunks and water trough 3.16 0.38 High

10 Use of dips, weigh bridger and squeeze chute. 3.16 0.38 High

11 Deworm cattle 1,16 0.38 Low

12 Hoof trimming of cattle 1.22 0.42 Low

13 Castrate and spray cattle 1.22 0.43 Low

14 Steaming up in dairy cattle 3.22 0.42 High

15 Breeding efficiency in cattle 1.15 0.37 Low

16 Carryout essential steps in developing a profitable breeding programme 3.20 0.45 High

17 Ability to carry out the process of Reproductive development in dairy bull and cow e.g oestrus synchronization

1.99 0.36 Low

18 Ability to carry out mating system e.g artificial insemination 1.34 0.37 Low

19 Ability to classify the breeds of cattle into exotic and tropical 3.44 0.48 High

20 Identify the distinctive characteristics of exotic and indigenous breeds 2.23 0.44 High

21 Identify types and methods of cattle selection 1.44 0.36 Low

22 Ability to describe genetic effects of pedigree and carry out individual and family selection

1.34 0.48 Low

23 Identify the various factors to be considered in establishing a cattle herd 1.21 0.42 Low

24 Ability to identify and describe the following bull steer, stag, cow, heifer, calf, yearling

3.32 0.47 High

25 Ability to classify cattle based on use stecker cattle, feeder cattle, slaughter cattle, draught cattle.

1.16 0.38 Low

26 Ability to plan and design dairy building 3.18 0.39 High

27 Capacity to construct various types of dairy buildings eg standion stall and barn, freestalls and cattle buildings.

1.23 0.42 Low

inadequate because the percentage score of availability was less than 70%. Therefore, the teaching staffs for animal production in the College were considered inadequate. Major findings of the study 1. Some of the facilities available were not found

suitable and functional (Biological PH meter, Bone breakers and Chance bovver dips) for running animal production programmes in the College.

2. It was found out from research question 2 that most of the equipment/tools required for the programme are grossly inadequate.

3. Graduates of the programme (HND) as revealed from research question 3 have low competence level in key areas of cattle production.

4. It was found out that all categories of staff needed for animal production were inadequate.

DISCUSSION The finding that some of the facilities used for running of animal production programme in the College are not suitable was in consonance with the findings of Eya and Neboh (2001) who found out that facilities ought to be suitable for staff and students in the teaching and learning process. The finding that equipment and tools required for the programme are grossly inadequate was in agreement with the findings of Ogwo and Oranu (2006). The author affirmed that availability of equipments/tools when sufficient, dictates the pace of knowledge acquisition. The finding was also in line with the Ekwe (2002) who asserts that equipment/tools where


Table 4. Number and percentage of teaching staff of animal production programme in College of Agriculture, Lafia, Nasarawa State.

Lecturers Number Required Number Available % Percentage Remarks

Chief Lecturer 4 2 25% Inadequate

Principal Lecturer 4 1 25% Inadequate

Senior Lecturer 3 3 100% Inadequate

Lecturer 1 5 2 25% Inadequate

Lecturer 11 4 2 50% Inadequate

Assistant Lecturer 2 0 0% Inadequate

Instructors 4 2 50% Inadequate

available transmits informative ideas and make idea to be explicit. The findings from that HND animal production graduates possessed low competencies in production was in agreement with the findings of Duncan and Grubb (2005) who found out that low skill in vocational agriculture is a limiting factor to high production. In support of the findings, Fatunsin (1996) agreed that high competence possessed in animal production encourages the use of psychomotor skills which leads to performance. The author further reiterates that psycho productive skills, competencies and abilities possessed at high level are better for performing tasks in animal production. The findings that all categories of staff were inadequate was in conformity with the findings of Omoreige (2006) who found out that it is worthless having a good curriculum for a school that is not adequately staffed (Lecturer and Instructors). Thus, adequacy of staff determines the effectiveness of teaching which in turn determine the performance of HND animal production graduates.

Conclusion The quality of HND graduates from Colleges of agriculture depends on availability and functional facilities, tools/equipment and adequate staff students’ ratio. The study has established the prevalence of inadequate facilities and staff. This had resulted to low competency level of the graduates in cattle production. The essence of the objectives of National Board for Technical Education for HND animal production graduates is to make them competent, productive and employer of labour. This objective is far from being realized with the findings from this study.

Recommendations Based on the findings the following recommendations were made: 1. Ministry of Education with the assistant of state

government should ensure adequate provision of equipment/tools and facilities for effective running of

animal production programme in the College of Education.

2. Workshop and seminars should be organized where resource persons could train graduates in competencies required for cattle production.

3. Qualified staff should be recruited by Principal or Governing Council of the College. This will enhance the quality of teaching and learning on the College.

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farmers in cattle rearing for self reliance in Nasarawa state. Journal of Agricultural Economics, Extension and Science. University of Agriculture Makurdi, Nigeria. (1), 203-210.

Duncan, G., & Grubb, N. (2005). The nature of job training programme reviewed: technical assistant report: Berkeley, University of California at Berkeley 4, 5-9

Ekele, G. E. (2011). Evaluation of Higher National Diploma Animal production programme of Colleges of Agriculture in North Central Nigeria. Unpublished Ph.D thesis. Department of Vocational Education. University of Nigeria, Nsukka. PP 35.

Ekele, G. E. (2013a). Job entry skills in sheep and goat production for Senior Secondary School graduates in Kano State, Nigeria. Review of Education. Institute of Education Journal. University of Nigeria, Nsukka. 26(2), 35-46.

Ekele, G. E. (2013b). Evaluation of programme course content and facilities of HND Animal production programme of College of Agriculture, Yandev, Benue State. International journal of research in Science, Technology and Mathematics (IJRSTME, university of Jos, Nigeria) 1(1), 40-50.

Ekele, G. E. (2014). Entrepreneurial skills required for wealth creation by farmers for cattle production in Sokoto State. Taraba State University journal of Education Research and Production. 3(2), 5-9.

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Eya, P., & Nebo, O. (2001). Evaluation of available instructional materials for the implementation of the UBE programme. Enugu Educational zone. The Nigeria Universal Basic Education journal. 1(2), 205-209

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competency Based Rating Instrument (CBRI) for evaluating the teaching effectiveness of secondary school teachers of Agriculture in Enugu State, Nigeria. Unpublished Ph.D thesis. Department of Vocational Education. UNN. Pp. 20-30

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Journal of Agricultural Science and Practice Volume 2. Page 54-57. Published 31st July, 2017



Inducing salt tolerance in wheat through inoculation with rhizobacteria containing 1-aminocyclopropane-1-

carboxylate deaminase activity

Muhammad Arshad Ullah1*, Syed Ishtiaq Hyder1, Imdad Ali Mahmood1, Tariq Sultan1 and Lal Badshah2

1Land Resources Research Institute, National Agricultural Research Centre, Park Road, Islamabad-45500, Pakistan.

2Department of Microbiology Faculty of Health Sciences, Hazara University, Mansehra, KPK, Pakistan.

*Corresponding author. Email: [email protected]

Copyright © 2017 Arshadullah et al. This article remains permanently open access under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Received 23rd June, 2017; Accepted 12th July 2017

ABSTRACT: Wheat (Triticum aestivum) is the fundamental feed of people as it contributes 60% of the daily diet of ordinary man in Pakistan. Salinity is one of the most imperative stresses that hinder agricultural productivity in nearly every part of the world. Improved biosynthesis of ethylene in plants under salinity stress is well established. Higher ethylene concentration retards root growth and eventually disturbs the overall plant growth. Plant growth promoting Rhizobacteria (PGPR) emits 1-aminocyclopropane-1-carboxylate (ACC) deaminase action under salt stressed conditions which minimizes the power of ACC and ethylene justifying the lethal effects of salt stress on plant growth. The seeds inoculated with PGPR having ACC deaminase are comparatively more tolerant to salt stress. The study was conducted at National Agriculture Research Centre Islamabad to examine the influence of PGPR on wheat growth (cultivars Pak-13 NARC-11 and NARC-09) and ionic concentration under saline environment to see the impact of bacterial strains having ACC deaminase on wheat growth and ionic concentration. The experiment was set up following completely randomized design with three repeats. Wheat seeds were inoculated following rhizobacteria strains, WPR-61, WPR-51, WPS-09 and Consortium of WPR-61, WPR-51 and WPS-09. Salinity (10.62dS m

-1) was artificially

developed using salts. Shoot and root length significantly affected by different rhizobial strains. The maximum root and shoot length attained by the consortium of three strains. The best results were achieved on NARC-09 wheat variety.Pak-13 wheat variety was significant affected by different rhizobial strains and maximum phosphorus concentration attained by WPS-09 strain in Pak-13. Keywords: Ethylene, rhizobial strains, salinity, salt tolerance, wheat cultivars, wheat growth. INTRODUCTION The entire form of life is reliant on plants as they produce oxygen and form the staple food for humans and animals. According to report, 98% of the world’s food necessities are fulfilled by 12 plant species and 14 animal species. Above 50% of the world energy ingestion is met by crops such as wheat, rice and maize (Thrupp, 2000).

Soil salinity is one of the chief abiotic factors affecting soil microbial activities and crop productivity. Reports showed that over 20% of agricultural land internationally is affected by salt (Pitman and Läuchli, 2002). It is estimated that the salinization will cause the loss of 50% arability of agricultural land by the middle of the 21st

century (Wang et al., 2003). Saline soil adversely retards the plant growth and productivity by shifting the normal metabolism of plants. Mitigation of salinity stress by plant growth promoting rhizobzcteriain plants. One of the effects of salt stress is an increase in the band of 1-aminocyclopropane-1-carboxylic acid (ACC), a precursor of ethylene, which consequences in accretion of ethylene. Increase in the rank of ethylene away from a threshold level is termed ‘stress ethylene’, which minimizes plant growth (Penrose and Glick, 2003) and alters photosynthesis and photosynthetic components (Koryo, 2006). Besides salt stress, other stresses such as


flood, drought, wounding, pathogen attack, temperature stress, and mechanical stress also contribute to considerable rise in the level of endogenous ‘stress ethylene’ (Stearns and Glick, 2003).

A large number of microorganisms live in a little bit of soil that is adapted or inclined by plant roots, called rhizosphere (Selosse et al., 2004). Useful bacteria can fasten to the roots or leaves of plants and thus are referred to as rhizosphere and phyllosphere bacteria respectively. They may also survive in the tissues of plant (endophyte bacteria) (Glick et al., 2007). Soil microorganisms play major role in the continuation of soil health (Jeffries et al.2003). Nakbanpote et al. (2013) reported salt-tolerant and plant growth-promoting bacteria isolated from Zn/Cd polluted soil.

Definite growth changes occur in the root system of the host due to colonization of the rhizosphere soil by rhizobacteria (German et al., 2000). These free-living rhizobacteria can be used in a number of ways when plant growth promotion is required (Lucy et al., 2004). The outcome of PGPR on agricultural crops has been investigated and published by various scientists during the last two decades (Asghar et al., 2002; Khalid et al., 2003; Asghar et al., 2004; Khalid et al., 2004; Zahir et al., 2004). The capability of these strains for improving plant growth was tested in agriculture by using bacterial inoculation in greenhouse as well as under natural field conditions (Salamone, 2000; Bent et al., 2001; Shaharoona et al., 2007, 2008).

Ethylene is a simple, two-carbon, unsaturated hydrocarbon which is a potent regulator of plant growth and progress (Binder, 2008). Initially, ethylene was known as a ripening hormone, but later demanding studies, tied with the advent of highly sophisticated analytical techniques, like gas chromatography, unveiled its role in growth and development all over the life cycle of the plant. On account of its varied and effectual role in plant growth and development, ethylene virtues equal category with other classes of plant hormones (Arshad and Frankenberger, 2002). Therefore, this study was planned at National Agriculture Research Centre Islamabad to examine the consequence of PGPR on wheat cultivars (Pak-13 NARC-11 and NARC-09) under saline environment. MATERIALS AND METHODS The wheat seeds of three cultivars namely Pak-13, NARC-11 and NARC-09 were inoculated with PGPR (WPR-61, WPR-51, WPS-09 and Consortium of WPR-61, WPR-51 and WPS-09) having ACC deaminase. The study was conducted at National Agriculture Research Centre Islamabad to examine the consequence of PGPR on wheat cultivars (Pak-13 NARC-11 and NARC-09) under saline environment to see the impact of bacterial strains on ACC deaminase on wheat growth and ionic

Ullah et al. 55

Table1. Physiochemical analysis of soil used in the experiment.

Characteristics Unit Values

pH - 7.02

Electrical conductivity (dS m-1

) 10.62

Organic Matter (%) 0.49

Na ppm 310

K ppm 42

P (AB-DTPA) ppm 0.51

Ca+Mg (meq/L) 24

Carbonate (meq/L) 0.6

Bicarbonate (meq/L) 0.20

SAR meq/L) 10.75

Soil type - Sandy Loam

concentration. The design was completely randomized, factorial with three repeats. Wheat seeds were inoculated with rhizobacteria strains which were: WPR-61, WPR-51, WPS-09 and Consortium of WPR-61, WPR-51 and WPS-09. Salinity (10.62dS m

-1) was artificially developed using

salts (Table 1). A soil sample (0 to 20 cm depth) was collected from experimental area before sowing of crop and fertilizers application. Plant samples were collected to see the effect of different rhizobial strains on the availability of nutrients to plants after two months. Soil samples were analyzed for various physicochemical properties using standard methods (Ryan et al., 2001; Sparks et al., 1996) and soil texture by Bouyoucous Hydrometer method (Kanwar and Chopra, 1959). The data obtained were subjected to statistical analysis using the STATISTIX statistical software (Version 8.1) and the mean values were compared using least significant difference (LSD) (Steel and Torrie, 1997). RESULTS AND DISCUSSION Shoot length was drastically affected by the inoculation wheat seeds with different rhizobial strains under artificially developed saline soil (ECe= 10.62 dS m

-1)

(Table 2). The highest shoot length (16.3 cm) was observed by inoculating with the consortium of three strains which was statistically at par with the results attained with WPS-8 and lowest shoot length (5.3 cm) was observed in control (without inoculation). This indicated that inoculation of wheat seed with rhizobial strains showed better responses in shoot length mitigating the adverse effects of saline conditions (ECe=10.62 dS m

-1). Varietal differences regarding shoot

length was very minute as indicated in Table 2. Similar trend was also noted in root length (Table 2). Significant results were achieved in plant fresh weight of three wheat varieties inoculated with strains under saline environment (ECe=10.62 dS m

-1) as shown in Table 2. Maximum fresh


Table 2.The effect of ACC deaminase on Shoot / root length and Plant fresh/dry weight of Wheat varieties (Pak-13, NARC-11and NARC-09).

Treatments

Shoot Length

(cm plant-1)

Root Length

(cm plant-1)

Plant fresh weight

(g plant-1

))

Plant dry weight

(g plant-1

)

V1 V2 V3 V1 V2 V3 V1 V2 V3 V1 V2 V3

T1 5.9c 5.4c 5.3c 6. 8b 6.6b 6.7b 1.0b 1.1b 1.2b 0.5b 0.5b 0.6b

T2 8.9b 8.1b 8.3b 9.1a 9.3a 9.9a 1.8a 1.7a 1.9a 0.9a 0.8ab 0.9a

T3 10.8b 10.0b 10.7b 9.6a 9.0ab 9.0ab 2.3a 2.4a 2.3a 1.1a 1.2a 1.3a

T4 12.5a 13.2a 12.7a 11.1a 11.3a 11.2a 2.3a 2.5a 2.4a 1.2a 1. 1a 1.3a

T5 15.7a 16.2a 16.3a 12.9a 13.3a 12.7a 2.5a 2.4a 2.5a 1.3a 1.2a 1.3a

LSD (0.5%) 5.1 4.2 0.9 0.5

Values followed by same letter(s) are statistically similar at P=0.05 level of significance. Pak-13=V1 NARC-11=V2 NARC-09= V3; Means= M, T1= Control, T2= WPR-61, T3= WPR-51, T4= WPS-09, T5= Consortium of WPR-61, WPR-51 and WPS-09.

Table 3. The effect of ACC deaminase on the Phosphorus concentration (%) of three wheat varieties (Pak-13, NARC-11 and NARC-09).

Treatments V1 V2 V3

T1 0.08f 0.09

e 0.07

f

T2 0.09e 0.09

e 0.07

f

T3 0.15c 0.14

d 0.14

d

T4 0.20a 0.18

b 0.14

d

T5 0.17b 0.16

c 0.15

c

LSD (0.5%) 0.02

Values followed by same letter(s) are statistically similar at P=0.05 level of significance. Pak-13 = V1, NARC-11 = V2, NARC-09 = V3, T1= Control, T2 = WPR-61, T3 = WPR-51, T4 = WPS-09,

T5 = Consortium of WPR-61, WPR-51 and WPS-09.

weight (2.5 g plant-1

) was attained with the consortium of three strains which was statistically at par with the results attained with WPS-8 and lowest shoot length (1.0 g plant

-

1) was noted in control (without inoculation). This

indicated that inoculation of wheat seed with rhizobial strains showed better responses in plant fresh weight extenuating the adverse effects of saline conditions (ECe=10.62 dS m

-1). Varietal differences regarding plant

fresh weight was very minute as shown in Table 2. Similar trend was also noted in plant dry weight (Table 2). Many researchers have studied better performance in plant growth inoculated with rhizobial bacterial containing ACC-deaminase (Mayak et al., 2004; Shaharoona et al., 2006). Ethylene is a stress hormone and is produced at higher concentration under any kind of stress including salinity. It is very liable that the rhizobacterial strains promoted root and shoot growth by lowering the endogenous inhibitory levels of ethylene in roots because of its high ACC metabolizing ability (Kang et al., 2010).

Ionic concentration of P (%) in wheat plants showed significant differences among treatments (Table 3). Uptake of P (%) was more (0.20%) by WPS-8 and control showed the lowest (0.07%). Singh et al. (2013) reported that judicious use of chemicals along with bio fertilizers

and organic resources can be helpful in sustaining the crop productivity and soil health. Conclusion Shoot and root length significantly affected by different rhizobial strains. The maximum root and shoot length attained by the consortium of three strains. NARC-09 showed the best results of root and shoots length among the wheat varieties. Pak-13 wheat variety was significantly affected by different rhizobial strains and maximum phosphorus concentration attained by WPR-61 strain was in Pak-13. REFERENCES Arshad, M., & Frakenberger, W. T. Jr. (2002). Ethylene:

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Journal of Agricultural Science and Practice Volume 2. Page 58-65. Published 8th August, 2017



Performance of cowpea (Vigna unguiculata (L.) Walp) under irrigation as influenced by weed management

methods and intra row spacing

Na-Allah M. S.1*, Mukhtar A. A.2, Mahadi M. A.2, Tanimu M. U.1 and Muhammad A.1

1Department of Crop Science Kebbi State University of Science and Technology, Aliero, Nigeria.

2Department of Agronomy Ahmadu Bello, University, Zaria, Nigeria.


Copyright © 2017 Na-Allah et al. This article remains permanently open access under the terms of the Creative Commons Attribution License 4.0,

which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Received 22nd May, 2017; Accepted 1st August, 2017

ABSTRACT: The study was conducted in the dry season of 2014/2015 at two locations: the experimental Farms of the Institute for Agricultural Research, Ahmadu Bello University Samaru, Zaria and Kadawa Kano, located in the Northern Guinea and Sudan Savanna Ecological Zones of Nigeria, to assess the effects of weed management methods and intra row spacing on performance of cowpea. The experiment was laid out in a split plot design with three replications. Treatments were five weed control methods involving the use of Pendimethalin at 1.0, 1.5 and 2.0 kg a.i. ha

-1, two hoe

weeding at 3 and 6 weeks after sowing (WAS) and a weedy check and four intra row spacing (20, 25, 30 and 35 cm). The herbicide treatments were assigned to the main plots while intra row spacings were assigned to the subplots. Results indicated that weed coverage score, weed density and weed dry weight were significantly decreased by the weed control methods compared to weedy check treatments. The application of Pendimethalin at the rate of 2.0 kg a.i ha

-1 and two hoe weeding at 3 and 6 WAS resulted to significantly higher values for plant height, canopy spread and

crop growth rate. Yield parameters including number pods per plant, seed weight and grain yield were also significantly increased in the herbicide treated plots and two hoe weeding compared to weedy check. In conclusion, the results obtained from this study indicated that two hoe weeding at 3 and 6 WAS and 20 cm intra row spacing effectively controlled weeds and produced the highest grain yield (kg ha

-1) in Samaru, Zaria and Kadawa, Kano.

Key words: Cowpea grain yield, intra row Spacing, treatments, weed control. INTRODUCTION Cowpea (Vignaunguiculata (L.) Walp) is a tropical herbaceous annual legume crop. It belongs to the family Fabaceae (formerly Leguminoseae) and sub family Papilinoideae of flowering plants. Kay (1979) cited Northeastern Nigeria as cowpea center of origin. Cowpea is the most important food legume in Semi-Arid Tropics covering Asia, Africa, Southern Europe and Central and South America (Singh, 2007). The major constraints to cowpea production are the presence of insect pests, diseases, plant parasitic weeds, drought and heat (Jackai et al., 1999). The cowpea plant is attacked by pests during every stage of its life cycle. Cowpea is infested by a number of weed species that compete with the crop right from germination to harvest, affecting the crop yield

adversely (Yadav et al., 1998). Striga and Alectra species are the major parasitic weeds infesting cowpea and severe yield losses have been reported by Aggarwal and Ouedrago 1989. Weeds also deteriorate the quality of produce through the physical presence of their seeds and debris. This emphasizes the need to control weeds in order to obtain optimum crop yield.

Herbicides, if properly used are safe and effective in controlling weeds in cowpea. The choice of herbicide however, partly depends on the predominant weed species and the availability of the herbicide. If herbicide is used at planting one hoe weeding may be required at 4 to 5 weeks after sowing. Application of a tank mixture of paraquat and pendimethalin within two days of planting is


recommended (Dugje et al., 2009). Paraquat controlled emerged grass and broad leaf weeds while Pendimethalin prevents weed seeds from germinating. According to Silva et al. (2003), the best post emergence weed control in cowpea was provided by phenoxaprop-ethyl at the rate of 80 gha

-1 associated with glyphosate

(1800 gha-1

) and it was effective against grasses. The conventional method of weeding such as hoeing, hand weeding and harrowing is expensive and labor is not available during peak workload (Khan et al., 2000). Therefore the use of herbicides in cowpea to control weeds appears to be useful (Dadari,2003; Silva et al., 2003). In general herbicides are effective only against few weed species which result in a serious infestation of other weeds. The phenomenon involved in crop yield increase as affected by different weed control methods has been well described by many researchers (Bukhtiar et al., 1992; Tomar et al., 2003; Patel et al., 2003). Tripath and Singh (2001) reported that the presence of weed in cowpea reduced yield by 82% whereas significant increase in pod yield was noted by controlling weeds up to 45 days of sowing. Parasuraman (2000) found that application of Pendimethalin (1.5 or 2.0 L/ha) or (fluchloralin 1.0 or 1.5 Lha

-1 ) at 3 days + hand weeding

twice at 30 days after sowing (DAS) resulted in significant reduction in weed population, dry matter and an increase in crop yield in rain fed cowpea. In an experiment to evaluate weed management strategy for cowpea, Patel et al. (2003) found that pre emergence application of Pendimethalin at 0.75 kg a.i ha

-1 + hand weeding at 5

weeks after sowing gave a higher grain yield (511 kgha-1

) and net return (RS.4705 ha) compared to other treatments. Jabir et al. (2004) reported that Pendimethalin at 1.0 kg a.i ha

-1 + hand weeding at 30

DAS gave the highest cowpea yield while weed density and weed dry biomass was lowest in this treatment. According to Akobundu (1984) chemical weed control combined with other cultural practices such as hoe weeding may be practical in reducing weed competition, crop loss and labour cost.

Despite the numerous importance of cowpea, its yield in farmers’ field is relatively low. According to Okafor and Adegbite (1991) weed could constitute a major limiting factor to cowpea production in Nigeria. Also, Tijjani (2001) reported that weed could cause yield losses of cowpea ranging from 50 to 80%. The conventional methods of weeding such as manual and mechanical methods are expensive, tedious and labour intensive. Thus, in order to enhance cowpea productivity, efficient, economical and easier weed control method such as the use of herbicide is desirable. Also, intra row spacing has been reported to determine plant density which is a good measure of weed management and also classified as cultural control method through canopy management (Akobundu 1987). Ross and Lembi (1985) stated that when crops are maintained in dense stands, they are vigorous enough by themselves to keep weeds in check.

Na-Allah et al. 59 This study was therefore conducted to determine the effect of weed control methods and intra row spacing on performance of cowpea. MATERIALS AND METHODS Field trials were conducted during 2014/2015 dry season at the research farm of the Institute for Agricultural Research Samaru, Zaria located on latitude 11

0 11

1 N

and longitude 070 38

1 E, 686m above sea level in the

Northern Guinea Savanna Ecological Zone of Nigeria and at the Irrigation Research Station of the Institute for Agricultural Research, Kadawa located on latitude 11

0

39’N and longitude 0800 20’E, 500m above sea level in

the Sudan Savanna ecological zone of Nigeria. The experiment was laid out in a split plot design with

three replications. Treatments were five weed control methods involving the use of Pendimethalin at 1.0, 1.5 and 2.0 kg a.i ha

-1, two hoe weeding at 3 and 6 weeks

after sowing and a weedy check and four intra row spacing (20, 25, 30 and 35 cm). The experiment was laid out in a split plot design with three replications. The herbicide treatments were assigned to the main plots while intra row spacing was assigned to the subplots. Each subplot was made up of six ridges, 75 cm apart giving a gross plot area of 12 m

2. The net plot area

consisted of four middle ridges giving an area of 9 m2.

Water channels were constructed for effective supply of water to each furrow during irrigation. The seeds were treated with Apron star at the rate of 10 g of the chemical per 4.0 kg of seed before sowing, in order to protect the seeds from soil borne diseases and pests. The seeds were sown first on the 19th of February 2015 in Samaru and on the 26th of February 2015 in Kadawa. The intra row spacing was as per treatment. Three seeds were sown per hole at 1.5 cm depth and later thinned to two seeds per stand. The herbicide Pendimethalin was applied immediately after sowing as pre emergence treatment, using a CP3 knapsack sprayer fitted with a green deflector nozzle calibrated to deliver 220 liter ha

-1

spray volume at a pressure of 1.5 kgcm2. Spraying was

done in the morning when the weather was calm to avoid wind drift. Cowpea plant was sprayed at vegetative, flowering and podding stages with appropriate mixture of cypermerthrin plus dimethoate at the rate of 1.0 Lha

-1 to

control pest. Harvesting was done manually by hand picking at intervals, when the pods in each plot turned brown and dried. The harvested pods were spread on the ground for six days to allow the pods to dry well before threshing. This was followed by winnowing to separate the seeds from the chaff.

The data were collected on weed cover, weed dry weight, plant height, canopy spread, number of pod per plant, seed weight and grain yield. The weed species in the experimental site were collected randomly from a 1 m

2 quadrat within the plots and were identified and their

60 J. Agric. Sci. Pract. Table 1. Common weed species and their level of infestation at the experimental sites in Samaru and Kadawa during 2014/2015 dry season.

Weed species Level of infestation

Samaru Kadawa

Grasses

Cynodon dactylon (L.) Pers *** **

Brachiaria deflexa S. ** **

Chloris pilosa Shumach ** **

Dactyloctenium aegyptium Linn * **

Digitaria horizontalis. Willd * **

Eleusine indica Gaertn * *

Eleusine indica ** *

Pennisetum pedicellatum Trin ** *

Broad leaved

Euphorbia heterophylla Linn *** **

Euphorbia hirta (L) - *

Amaranthus spinousus(I.) * *

Leucas martinicensis (Jacq). Ait.F * *

Mitracarpus villosus (Sw).Dc ** *

Physalis angulata Linn - *

Commelina benghalensis L. * *

Sedges

Cyperus esculentus(L.) * *

Cyperus rotundus Linn * ***

***High infestation (60-90%), **Moderate infestation (40-50%), *Low infestation (1-39%).

intensity of occurrence was recorded. Data collected was subjected to analysis variance using SAS and the means were separated using Duncan multiple range test (Duncan, 1995). RESULTS The soil in Samaru was silt loam and sandy loam in Kadawa with medium pH 5.66 to 6.85, low nitrogen, and phosphorus and potassium values. Metrological data of both locations are presented in Appendix Table 1. The records of temperature, sunshine hours and relative humidity were collected from the meteorological unit of the Institute for Agricultural Research Samaru and Irrigation Research Station at Kadawa during the experimental period (Appendix Tables 2a and b).

At Samaru, the common dominant weed species were grasses such as Cynadondactylon, Brachiaria deflexa, Digitaria horizontalis, Dactyloctenium aegyptium. This was followed by broad leaved weeds such as Euphorbia heterophylla, Mitracarpusvillosus, Commelina

benghalensis and the least were sedges such as Cyperus rotundus and Cyperus esculentus. At kadawa, the common dominant weed species were also grasses such as Cynadon dactylon, Digitaria horizontalis, Chloris pilosa. This was followed by broadleaved such as Euphorbia heterophylla, Mitracarpus villosus, amaranthus sipinosus. The least were sedges such as Cyperus rotundus and Cyperus esculentus (Table 1). Weed coverage score and weed dry weight At 9 WAS, the highest weed coverage score was recorded in weedy check with mean value of 6.33. The least weed coverage was recorded in hoe weeded plots with mean value of 3.67 (Table 2). There was no significant effect on weed cover score in Samara, Kadawa and mean data for varying the intra row spacing from 20 to 35 cm throughout the sampling period. The effect of weed control and intra row spacing on weed dry weight is shown on Table 2. The weedy check plots recorded the highest weed dry weight at 9WAS in both locations. The lowest weed dry weight was recorded in the two hoe weeded treatment (Table 2). A significant difference was observed among the various intra row spacing at 9 WAS in Samaru with the 20 cm intra row spacing recording the least dry weight than 25, 30 and 35 cm. Cowpea height and canopy spread Cowpea height was significantly influenced by different weed control treatments (Table 3). Two hoe weeded plots produced the tallest plant followed by Pendimethalin at 2.0, 1.5, 1.0 kg a.i ha

-1 while the shortest was observed in

the weedy check at 9 WAS in Samaru. In kadawa and mean data, two hoe weeded plots and Pendimethalin at 2.0kg a.i ha

-1 produced the tallest plant while the shortest

was observed in the weedy check (Table 3). Varying the intra row spacing from 20 to 35 cm significant difference at 9 WAS in Samaru where the 35 cm had the taller plants than the other spacing. There was no significant effect on intra row spacing at Kadawa throughout the sampling period. Canopy spread showed significant difference among the treatments. Hoe weeded plot had significantly wider canopy spread than other treatments. There was also significant difference on cowpea canopy spread in Pendimethalin at all rates but they differed from weedy check plots in both locations (Table 3). There was no significant difference on intra row spacing with respect to canopy spread at 9 WAS in both locations.

Number of pods per plant and 100 seed weight In both locations the highest number of pod per plant was from the hoe weeded plot which was significantly higher

Na-Allah et al. 61

Table 2.Effect of weed control methods and intra row spacing on weed cover score and weed dry weight of cowpea at 9 WAS in Samaru and Kadawa.

Parameters Weed cover score (m

2) Weed dry weight (g/m

2)

Samaru Kadawa Mean Samaru Kadawa Mean

Weed control (w)

Pendimethalin (kg a.i ha-1

)

1.0 5.25b 7.42

a 6.33

b 87.08

b 57.92

b 145.00

b

1.5 4.00c 7.50

a 5.75

c 84.08b 52.29

b 134.37

b

2.0 3.42d 7.50

a 5.87

c 77.51b

c 38.27

b 115.78

c

Two hoe weeding (3& 6WAS) 3.67d 5.25

b 4.46

d 55.07

c 29.42

c 84.49

d

Weedy check 6.33a 7.58

a 6.95

a 185.99

a 116.2

a 302.19

a

SE± 0.179 0.248 0.362 4.199 4.234 4.133

Intra spacing (cm)

20 4.80 7.73 12.53a 84.94

b 45.90 130.84

d

25 4.60 7.00 11.60b 89.00a

b 58.08 147.08

c

30 4.60 7.00 11.60b 106.90

a 62.21 169.11

b

35 4.73 7.07 11.80b 111.41

a 69.12 180.53

a

SE± 0.159 0.222 0.235 3.898 3.930 3.755

Means followed by the same letter (s) within a column in each treatment are not significantly different at 5% using DMRT. * = Significant at 5%, NS = not significant. Kg a.i ha

-1 = kilogram active ingredient per hectare, WAS = weeks after sowing.

Table 3. Effect of weed control methods and intra row spacing on plant height and canopy spread of cowpea at 9WAS in Samaru and Kadawa.

Parameters Plant height Canopy spread


Weed control (w)


)

1.0 29.02c 26.63

b 27.82

d 56.27

d 73.87a

b 65.07

c

1.5 38.11b 26.69

b 32.40

c 93.08

c 69.23a

b 81.16

b

2.0 39.30b 31.41

a 35.36

b 102.40

b 72.37a

b 87.39

b

Two hoe weeding (3& 6WAS) 46.89a 32.25

a 39.62

a 108.26

a 88.17

a 98.22

a

Weedy check 13.85d 14.26

c 14.05

e 14.13

e 54.52

b 34.32

d

SE± 0.426 0.936 0.843 1.659 6.184 2.895

Intra spacing (cm)

20 31.02d 27.37 29.20

b 72.69 69.10 70.89

25 32.59c 26.22 29.40

b 72.86 64.16 68.51

30 33.79b 25.75 29.77

ab 75.17 79.27 77.22

35 36.33a 25.72 30.03

a 78.59 74.02 76.30

SE± 0.381 0.837 0.783 1.484 5.532 2.688

Means followed by the same letter (s) within a column in each treatment are not significantly different at 5%

using DMRT. * = Significant at 5%, NS = not significant. Kg a.i ha-1

= kilogram active ingredient per hectare, WAS = weeks after sowing.

than those recorded from application of Pendimethalin at all rates (Table 4). The lowest number of pods per plant was recorded from the weedy check.There was

significant effect of intra row spacing on number of pod per plant in both location in which 35 and 30 cm intra row spacing had higher number of pods per plant than 25 and


Table 4. Effect of weed control methods and intra row spacing on number of pods per plant and 100 seed weight of cowpea at Samaru and Kadawa.

Parameters Number of pods per plant 100 seed weight (g)


Weed control (w)


)

1.0 8.00c 8.00

c 16.00

d 17.25

c 16.84

c 34.09

1.5 10.00b 10.00

b 20.00

c 18.12

b 18.45

b 36.57

2.0 12.00a 11.00

a 23.00

b 20.00

b 19.42

b 39.42


a 25.00

a 24.53

a 23.84

a 48.37

Weedy check 5.00d 5.00

d 10.00

e 14.82

d 14.41

d 29.23

SE± 0.403 0.364 0.498 0.474 0.463

Intra spacing (cm)

20 8.00b 8.00

b 16.00

b 17.98

b 17.64

b 35.38

c

25 8.00b 8.00

b 16.00

b 18.70a

b 18.28

ab 36.98

b

30 10.00a 9.00

a 19.00

a 19.44

a 19.08

a 38.52

a

35 10.00a 9.00

a 19.00

a 19.64

a 19.28

a 38.92

a

SE± 0.375 0.337 0.410 0.294 0.414 0.399


-1 = kilogram active ingredient per

hectare, WAS = weeks after sowing.

20 cm respectively. Two hoe weeded plot gave the highest 100 seed weight which was significantly higher than other treatments while the lowest was from the weedy check in both locations (Table 4). Generally, in both locations weedy check produced significantly lowest 100 seed weight. The heaviest 100 seed weight was achieved in 35 and 30 cm spacing in both locations. Grain yield (kg ha

-1)

Cowpea grain yield was significantly affected by weed control methods and intra row spacing in both locations (Table 5). The grain yield was higher in hoe weeded plot followed by application of Pendimethalin at 2.0, 1.5, 1.0 kg a.i ha

-1 and weedy check in that order. The intra row

spacing exhibited significant difference with respect to grain yield. Grain yield in 20 cm plot was significantly higher than those of 25, 30 and 35 cm in that order in both locations. DISCUSSION At both locations, pendimethalin at higher rate of 2.0 kg a.i ha

-1 effectively control weed beyond the critical period

of cowpea growth. This minimized competition for growth resource between the crops and the weeds particularly during the critical period of weed interference in cowpea leading to greater efficiency in utilizing growth and yield

resources by the crop. This also led to vigorous crop growth and development of larger leaf area which intercepted more light for increased dry matter production and yield. This finding agree with that of Dadari (2003) and Silva et al. (2003) who reported that the use of herbicides in cowpea to control weeds appears to be useful and considered to be more effective against weeds. The wider canopy observed in both locations with two hoe weeding and application of pendimethalin at 2.0 kg a.i ha

-1, was because there was effective weed

control which suppressed weed growth there-by reducing competition for growth factors between the crops and weeds. The significant increase in cowpea height with application of Pendimethalin and the two hoe weeded plots could attributed to the fact that there was good weed control that ensured availability of growth resource. In both locations weedy check also resulted in shorter plants than all other treatments. The production of shorter plants by the weedy check is because weed competition for growth resources in plants usually retards growth.

The number of pod per plant, 100 seed weight and grain yield were higher in two hoe weeding than other weed control methods. This could be attributed to effective weed control in hoe weeded plots resulting in maximum nutrient utilization which led to production of high assimilation of photosynthates causing increase in grain yield. Similar results were observed on groundnut crop by other researchers (Mubarak 2004; Kumar 2009). They observed that pod yield was greatly increased with good weed control treatments, which encouraged early

Na-Allah et al. 63

Table 5.Effect of weed control methods and intra row spacing on grain yield of cowpea at Samaru and Kadawa.

Parameters Grain yield (kg ha

-1)

Samaru Kadawa Mean

Weed control (w)


)

1.0 796.86d 718.24

d 1515.10

d

1.5 974.02c 891.81

c 1865.83

c

2.0 1084.67b 1019.77

b 2104.44

b


a 2386.74

a

Weedy check 248.67e 284.31

e 532.98

e

SE± 7.167 7.063 7.882

Intra spacing (cm)

20 949.82a 835.10

a 1784.92

a

25 884.75b 821.69

a 1706.44

b

30 848.57b 802.17

ab 1650.74

c

35 827.01c 755.03

b 1582.04

d

SE± 6.653 6.556 7.235


-1 = kilogram active

ingredient per hectare, WAS = weeks after sowing.

flowering, developed higher leaf area index, increased number of pods and branches per plant and maximized pod yield. The higher grain yield obtained from application of Pendimethalin at 2.0 kg a.i ha

-1 and two

hoe weeding could be associated with the higher number of branches, leaf area index and wider canopy spread. These could have made for greater reception of light leading to increase in photosynthetic process of plants which was required for pod filling and improved grain yield of cowpea in both locations. The superior performance of these treatments as compared to the weedy check could be attributed to their effective in weed suppression that allow better efficiency in the use of available growth and yield resource. The results agree with findings of Adekpe (2004) who observed that crops are known to perform better under good weed management.

The intra row spacing used in this experiment exhibited significant increase in growth and yield parameters of cowpea in both locations. Growth parameters such as plant height, canopy spread and number of branches per plant were significantly affected by intra row spacing. Widely spaced plants (35 cm) were taller than closely spaced plants (20 cm). This may be due to sufficient nutrients and light at wider spacing. This may be attributed to vigorous plants with less competition for light, nutrients and space there by resulting in high crop performance. Adigun et al. (2014) reported similar finding. The influence of intra row spacing on yield components such as number of pod per plant, seed

weight and grain yield were significantly affected by intra row spacing. The increase in number of pods per plant with increasing plant spacing observed in this study was due to sufficient nutrients and light at wider intra row spacing. This is in line with the finding of El Naim et al. (2010) who reported increase in number of pods per plant with increased intra row spacing. Decreasing plant spacing decreased seed yield per plant in both locations. This was primarily due to the reduced number of pods per plant at closer spacing which led to the production of smaller sized seeds as result of increased competition for available resources such as moisture, sunlight and nutrients. This agrees with the finding of El Naim and Jabereldar (2010) that seed yield per plant substantially decreased with decreased plant spacing. They attributed this reduction to inter plant competition for assimilates and low pod yield. The higher yield obtained at 20 cm intra row spacing could be attributed to more harvestable plants per unit area which more than compensated for the reduction in yield of individual plants. The significant reduction in weed dry matter production in narrow intra row spacing at 9 WAS in Samaru was due to higher plant populations resulting to early and better canopy formation which enhanced weed suppression. This is in line with the finding of Adigun et al. (2014) who reported significant reduction in weed dry weight in narrow spacing due to better canopy cover of the crop under narrow spacing on cowpea. Reduction in weed bio-mass due to narrow rows has been reported by Tharp and Kells (2001) that crop planted at closer spacing form canopy

64 J. Agric. Sci. Pract. much earlier than those spaced widely apart and result in better weed suppression and low weed dry weight on corn. Conclusion Based on this finding, it can be concluded that hoe weeding at 3 and 6 WAS with intra row spacing of 20 cm reduced weed infestation and increase grain yield of cowpea in both locations. However, the result of this experiment showed that all rates of pendimethalin applied were not effective in the control of sedges. Thus, a combination of pendimethalin and metolachlor at different rates is recommended for further studies. REFERENCES Adekpe, D. I., Shinggu, C. P., Adesanya, A. A., & Bitrus, C. T.

(2004). Effect of pre emergence herbicides on the performance of roselle (Hibiscus sabdariffa) at Samaru Zaria. A paper presented at the 22nd Annual Conference of the Horticultural Society of Nigeria (HORTSON) held at Daula Hotel, Kano 4th-9th July 2004.

Adigun, J. A., Osipitan, A. O., Lagoke, S. T., Raphael, O. A., & Stephen, O. A. (2014). Growth and yield of cowpea (Vigna unguiculata (L.) Walp) as influenced by row intra row spacing and period of weed interference in South West Nigeria. Journal of Agricultural Science, 6,188-198.

Aggarwal, V. D., & Ouedraogo, J. T. (1989). Estimation of cowpea yield loss from Striga infestation. Tropical agriculture, 66(1), 91-92.

Akinyemiju, O. A., & Olaifa, J. A. (1991). Relative Importance of Weeds and Insect Pest Control in Cowpea Production. Nigerian Journal of Weed Science, 4, 43-53.

Akobundu, I. O (1984). Response of cowpea (Vigna unguiculata (L) Walp). Cultivars to pre emergence herbicide IITA P.M.B 5320 Ibadan Nigeria. Nigerian Journal of Plant Protection, 9, 31-35.

Akobundu, I. O. (1987).Weed Science in the Tropics. Principles and Practices. John Wiley and Sons limited, Great Britain, Pp. 159-161.

Bukhtiar, B., Naseem, A., & Tufail, M. (1992). Weed Control in Lentil under Irrigated Conditions. Pakistan Journal of Weed Science Research, 4, 99-104.

Dadari, S. A. (2003). Evaluation of herbicides in cotton/cowpea mixture in the Northern Guinea Savanna. Journal of Sustainable Agriculture. 5,153-159.

Dugje, I. Y., Omoigui, L. O., Ekeleme, F., Bandyopadhyay, R. P., Lava, K., & Kumar A. Y. (2009). Farmers Guide to Soya bean Production in Northern Nigeria. IITA, p.7

Duncan, D. B. (1995). Multiple Ranges and multiple F- test. Biometrics, 11, 1-42

El Naim, A, M., & Jabereldar, A. A. (2010). Effect of Plant density and cultivar on growth and yield of cowpea (Vigna unguiculata (L.)Walp). Australian Journal of Basic and Applied Sciences, 4(8), 3148-3153.

El Naim, A. M., El day, E. M., & Ahmed, A. A. (2010). Effect of

plant density on the performance of some sesame (Sesamum indicumL) cultivars under Rain fed. Research Journal of Agriculture and Biological Sciences, 6(4), 498-504.

Jackai, L., Goudou, C., Asiwe, J., & Tayo, B. O. (1999). Integrated control of the cowpea (Vigna unguiculata L.) aphid using seed dressing and varietal resistance. Samaru Journal of Agriculture Research, 17, 13-23.

Khan, B. M., Asif, M., Hussain, N., & Iqbal M. (2000). Agro economic impacts of different weed control strategies in wheat, Journal Research Science, 11, 46-49.

Kumar, N. S. (2009). Effect of plant density and weed management practices on production potential of groundnut (Arachishypogea L.). India Journal of Agricultural Research, 43, 1

Mubarak, H. A. (2004). Studies on weed management in irrigated groundnut (Arachishypogea L.) in the Sudan. Ph.D. Thesis. Faculty of Agricultural Science, University of Gezira, Wad Medani (Sudan).

Parasuraman, P. (2000). Weed Management in Rain-fed cowpea (Vignaunguiculata) and green gram (Phaseolusradiatus) under north-western agro-climatic zone of Tamil Nadu. Indian Journal of Agronomy; 45, 732-736.

Patel, M. M., Patel, A. I., Patel, I. C., Takka, S. B. S., Henry, A., Kumar, D., & Singh, N. B. (2003). Weed control in cowpea under rain fed condition.in proceeding of the national symposium on arid legume, for food nutrition security and promotion of trade. Advances in Arid Legumes Research, Pp. 203-206.

Ross, M. A., & Lembi, C. A. (1985). Applied Weed Science. Burses publishing company, Minneapolis Minnestota, 35p.

Silva, J. B. F., Pitombeira, J. B., Nunes, R. P., & Pinto, J. L. N. (2003). Weed Control in Cowpea under no till system. Planta Dawinha, 21, 151-157.

Singh, B. B. (2007). Recent progress in cowpea genetics and breeding. In: International Conference on Indigenous Vegetables and Legumes. Prospectus for Fighting Poverty, Hunger and Malnutrition 752, Pp. 69-76.

Tijjani, E. H. (2001). Influence of intra row spacing and weeding regime on the performance of cowpea [Vignaunguiculata (L.) Walp]. Nigerian Journal of Weed Science, 14,11-15.

Tomar, R. K., Singh, R. N., Garg, V. K., Gupta, R. N., & Arora, R. P. (2003). Effect of weed management practices on weed growth and yield in wheat and rice based cropping system under varying levels of tillage. Annals pl Project Science; 11, 123-8.

Tripathi, S. S., & Singh, G. (2001). Critical period of weed competition in summer cowpea (Vigna unguiculata (L.)) Indian Journal for Weed Science; 33:67-8.

Yadav, R. L. (1998). Factor productivity trends in a rice–wheat cropping system under long-term use of chemical fertilizers. Experimental Agriculture, 34(1), 1-18.

Na-Allah et al. 65 Appendix

Appendix Table 1. Physical and chemical properties of soil of the experimental sites at Samaru and Kadawa in 2014/2015 dry season.

Composition Samaru Kadawa

0-30 cm 0-30 cm

Particle Size Analysis (%)

Sand 36.00 58.00

Silt 6.00 36.40

Clay 58.00 5.60

Textural Class Silt Loam Sandy Loam

pH H2O 1.2.5 6.20 7.29

pH in 0.01MCaCl2 5.66 6.85

Organic Carbon (%) 1.51 1.37

Total Nitrogen (%) 0.51 0.42

Available Phosphorus (mg kg-1) 3.07 2.20

Exchangeable bases (Cmol kg-1)

Ca 3.50 1.90

Mg 1.60 1.45

K 0.16 0.19

Na 0.18 0.20

Cation Exchange Capacity CEC (Cmolkg-1

) 6.00 5.00

Appendix Table 2a. Meteorological data showing monthly rainfall, air temperature, relative humidity and sunshine hour in 2015 at Samaru.

Month Rainfall (mm) Temperature (

0C)

Relative humidity (%) Sunshine hour Max. Min. Mean

January 0.00 28.97 13.60 21.52 19.74 NA

February 0.00 31.54 15.68 23.61 12.36 NA

March 90.90 36.19 21.13 28.66 20.45 6.42

April 0.00 36.27 21.53 28.00 12.13 7.37

May 90.10 37.35 21.53 30.77 52.52 6.91

Total 180.90

Mean 217.18

NA, Not Available. Source: Meteorological Unit of Institute for Agricultural Research (IAR), Ahmadu Bello University, Samaru, Zaria.

Appendix Table 2b.Meteorological data showing monthly rainfall, air temperature, relative humidity and sunshine hour in 2015 at Kadawa.

Month Rainfall (mm) Temperature (

0C)

Relative humidity (%) Sunshine hour Max. Min. Mean

January NA 32.52 14.77 23.65 36.29 10.50

February NA 36.89 19.07 27.98 27.32 10.00

March NA 37.84 22.23 30.03 28.03 7.03

April 19.40 40.67 26.10 33.38 38.80 7.86

May 58.1 39.94 26.58 33.26 58.39 8.22

Total 77.50

Mean 15.50

NA, Not Available.Source: Meteorological Unit of Institute for Agricultural Research (IAR), Ahmadu Bello University, Samaru, Zaria.

Journal of Agricultural Science and Practice Volume 2. Page 66-73. Published 14th September, 2017



Economic analysis of Yam-Cowpea intercropping system in Obi Local Government Area, Nasarawa State,

Nigeria

Onuk E. G.1, Girei A. A.1*, Ohen S. B.2 and Alaga M. H.1

1Department of Agricultural Economics and Extension, Nasarawa State University, Keffi, Nigeria.

2Department of Agricultural Economics, University of Calabar, Calabar, Cross River State, Nigeria.


Copyright © 2017 Onuk et al. This article remains permanently open access under the terms of the Creative Commons Attribution License 4.0, which


Received 16th June, 2017; Accepted 10th August, 2017

ABSTRACT: Though Nigeria is blessed with vast land and human resources suitable to produce enough food for her teeming population, low productivity in crop production has constrained her food sufficiency effort; this however calls for crop production mixture expansion strategies. The study evaluates the economics of yam-cowpea intercropping in Obi Local Government of Nasarawa State, Nigeria. The specific objectives were to describe the Socio-economic characteristics of yam–cowpea intercrops farmers; identify the sources of fund; to estimate input-output relationship in yam-cowpea production in the study area; determine the cost and returns on yam–cowpea production; and identify the major constraints to yam-cowpea inter-cropping system. A multi-stage sampling technique was used to select 80 yam-cowpea intercrops farmers, farm input-output data were collected based on 2015 cropping season with the aid of a structured and validated questionnaire. The results revealed that 83.8% of the respondents were males; most of the farmers (76.4%) had formal education and majority of the respondents (77.6%) had farm size of 0.5 to 2 ha. The results further revealed that majority of the farmers (57.5%) got their finances from their personal savings. The double-log production function analysis reveals that the coefficient of multiple determination, (R

2 = 0.908) indicated that 91% of the

variation in the value of the output (₦/ha) was explained by independent variables. Yam sett and labour were found to be significant at 1% while agrochemical was found to be significant at 5% in increasing the value of the output. The gross margin analysis showed that Gross Margin (GM) was N25, 455.30 with return per naira invested of 0.11. The study also revealed that high cost of inputs, pests and diseases and inadequate capital were the major constraints to yam-cowpea production in the study area. The study recommended that inputs (yam setts and agrochemicals) supply at subsidized rate to farmers in the area should be enhanced. There is need to make funds accessible and available for the farmers in the study area through the creation of functional rural micro finance institutions.

Keywords: Food crops, gross margin, inputs, output, resources.

INTRODUCTION

Though Nigeria is blessed with vast land and human resources suitable to produce enough food for its teeming population, low productivity in crop production has constrained its food sufficiency efforts. Going by the rapid rate of population growth in Nigeria, it is logical to conclude that the rate of growth in output of food crops may not be sufficient to sustain the demand for food by the increasing population (Lawal et al., 2014). The continuous cultivation of a particular piece of land by farmers with little or no measures to improve the soil condition seriously affects the productivity of the farmer. This however calls for crop production mixture expansion

strategies. Intercropping of tubers and legumes is wide-spread among farmers due to the ability of the legumes to contribute to addressing the problem or declining levels of soil fertility.

Intercropping is a very common feature in the cropping system among the resource poor farmers in the less developing countries of the world. It is thought to have evolved to meet the local situation and condition such as increase in income, stability and uniformity of yield (Eskandari et al., 2009). Intercropping according to Wikipedia (2013) is a multiple cropping practice involving growing two or more crops in proximity. The common


goal is to produce a greater yield on a given piece of land by making use of resources that would otherwise not be utilized by a single crop. The merits of intercropping over sole cropping include security of returns and profitability due to higher combined return per unit area of land (Anil et al., 1998). In addition, the practice controls weed, maintains soil fertility and reduces soil runoff.

Intercropping, according to Parsons (1999) refers to the growing of more than one crop in the same land area in rows or definite proportion and pattern. He further stated that it is a practice often associated with sustainable agriculture and is commonly used in the tropical parts of the world and the system uses the practice of sowing a fast growing crop with a slow growing crops so that the fast growing crops is harvested before the slow growing starts to mature. The earlier harvested crops provide both food and financial income to the farmers for expansion and for carrying out all the needed farm operations for the major crop (Gana and Busari, 1999). The income raises the socio-economic status of small and marginal resource constrained farmers, especially for rural women and youth (Gana and Busari, 2013).

Although there is no recorded history for intercropping, however, considering the available evidence, planting crops as a combined has a long history. Intercropping is a multiple cropping system, in which two or more crops species are planted simultaneously in a field during a growing season. Of course this does not mean that intercropping, plants can be planted at a time together, but it is the purpose that two or more crops are together in one place, during their growing season or at least in a time frame. Therefore it is possible that the plants are different in terms of planting time and a plant is planted after the first plant (Mazaheri et al., 2006). Intercropping is the growing of two or more crops on the same piece of land within the same year (Sullivan, 2003). Intercropping is advocated due to its benefits for yield increase on a given piece of land by making use of resources that would otherwise not be utilized by a single crop (Gana and Busari, 2003). One of the goals of intercropping is to control weed (Poggio, 2005) and control legume root parasite infections (Fernandez-Aparicio et al., 2007). Careful planning is required for the practice of intercropping arable crops. This includes taking into account the soil, climate, crops, and varieties. It is particularly important not to have crop competing with each other for physical space, nutrients, water or light. Example of intercropping strategies are planting a deep rooted crop with a shallow-rooted crop or planting a tall crop with a shorter that requires partial shade. When crops are carefully selected, other agronomic benefits are also achieved (Gana, 2013). Adetiloye et al. (2006) defined intercropping as an agricultural practice that involves the growing of two or more crops on the same piece of land within a cropping season.

Yam (Dioscorea Spp.) is a tuber crop that stores its food in the underground tissues. In Nigeria, yam is widely

Onuk et al. 67 cultivated in the agro-ecological zones covered by the humid rain forest, the derived Guinea Savannah and the Guinea Savanna (Adetiloye et al., 2006).

According to Eneji (2009), the domestication of yams in Africa, Asia and tropical America took place separately with different species involved. More than ninety-five percent (95%) of the world’s yam are currently grown in Sub-Saharan Africa, with the remainder grown in the West Indies and part of Asia and south Central America. The author further reported that, there were more than 600 yam species grown throughout the world, but in West Africa, the three major species are: white yam, yellow yam and water yam. Yam is a preferred staple food crop in West Africa and also has a prominent Socio-cultural role in various communities in West-Africa. White yam, a native of West Africa is grown in greater hecterage than any other yam species in the world. It is the most favoured yam specie in West Africa because it possesses a highly viscous starch, which is suitable for pounded yam preparation. Ekine and Okeke (2013) reported that in terms of cultivation and utilization, white yam (Dioscorea rotundata) and water yam (Dioscorea alata) are the most important food yams. They further stated that in Africa, consumer demand for yam is generally very high and despite its high cost of production, yam cultivation is very profitable. Pounded yam is one of the most popular and prestigious food in West African sub region (Onwueme, 2008).

In Africa, the production of yam is largely confined to the “yam zone” comprising of Nigeria, Cameroon, Benin, Togo, Ghana and Cote d’Ivoire, where approximately ninety percent (90%) of the world’s production takes place (Eneji, 2009). As revealed by Food and Agriculture Organization of the United Nations (FAO, 2000) statistic, 96% of the 37.5 million tonnes of yam produced worldwide were in Africa. The leading producer was Nigeria with 26 million tonnes followed by Ghana with more than 3 million tonnes and Cote d’Ivoire with 2.9 million tonnes.

Cowpea on the other hand (Vigna unguiculata(L) walp) is an annual legume. It is commonly referred to as southern pea, black eye pea, crowder pea, lubia, niebe or frijole. Cowpea originated in Africa where it is widely grown. The crop is grown in latin America and South East Asia. The history of cowpea dates to ancient West Africa cereal farming, five to six thousand years ago, where it was closely intercropped with sorghum and pearl millet (Eneji, 2009). Cowpea is considered to be the most important staple food grains in the dry savannah of tropical Africa for both the rural and urban dwellers (Chege, 2004). It is rich quality protein and has content almost equivalent to that of cereal grains and it a source of quality fodders for livestock and provides cash income (Langyintuo et al., 2006). Cowpea is an important legume grown in the semi-arid tropics, covering Africa, Asia, southern Europe and Central South America (Davis et al., 2013). It is one of the ancient crops known to man and is

68 J. Agric. Sci. Pract. cultivated primarily for gain, but also as vegetable (leafy green, green pods, shelled dried peas and fresh shelled green peas), a fodder and cover crop. Moreover, cowpea forage is significant to animal feeds mainly during the dry season when the demand for the feeds is at its peak. Its ability to replenish soil nitrogen gives it a key position in the modern crop farming system in rotation with the other crops, with the view for long term sustainable agriculture development prospect. Due to the increase in the demand for the crop, arising from the growing population in the country, Nigeria remains the largest producer and consumer of cowpea both in West Africa and in the world. In Nigeria, the greatest production of cowpea comes from the northern region. The north produces about 1.7 million tonnes from 40 million hectares. This represents over 60% of the total production (Coker et al., 2014). Sole cropping system with the use of improved technologies can yield 1,500 to 2000 kg of cowpea. However, 200 to 250 kg/ha yield is obtained by small scale farmers who are domestic producers in the country (Wakili, 2013).

Hence, the research specific objectives are to: (i) describe the socio-economic characteristic of yam-cowpea intercrops farmers in the study area (ii) identify the sources of fund for yam-cowpea intercrop farmers in the study area (iii) estimate input-output relationship in yam-cowpea production in the study area (iv) determine the costs and returns on yam-cowpea production in the study area and (v) identify the major constraints to yam-cowpea intercropping system in the study area.

METHODOLOGY The Study Area The study was conducted in Obi Local Government Area (LGA), Nasarawa State. The LGA is located in the Southern part of Lafia and lies between latitude 8

021' and

8040' in the North and longitude 8

069' and 8

08' in the

East. It headquarter is in the town of Obi. It covers land area of about 967 m

2 and a population of 148,874 based

on the 2006 census and a projected population of 190,558 applying a 2.8% growth for 2016 (NPC, 2006). The Local Government Area is characterized by long period of rainy season (March to October). The mean annual rainfall is about 1270 to 1540 mm for period of over seven to eight months (April to October) of rainy season with five months of dry wind spell with Harmattan starting from November to late March and annual temperature ranging from 22.7 to 36.8˚C (Nasarawa State Meteorological Department, 2008). The major tribes are Alago, Migili, Gwandara, Eggon, others include Tiv, Kwalla, Hausa, Fulani and Igbo. The main predominant occupation of the inhabitants is farming. About 70% of the populations of the area are farmers while 30% constitutes civil servants, student, business men and women. The economic activities is largely agrarian with the majority of the people as subsistence farmers who

cultivate crops such as yam, rice, maize, cassava, sorghum, millet, cowpea and a few other crops. Obi local Government Area has five (5) districts which include Obi, Agwatashi, Adudu, Daddere and Riri (Ladan and Oyigbenu, 2000).

Sample size and sampling technique

A multi-stage sampling technique was used for this study. Obi Local Government Area consists of five (5) districts. First, from these districts, four (4) districts were selected using Simple random Sampling. Secondly, two (2) villages were randomly selected from each of the four (4) districts. The villages selected include: Doyan Abakwa, Doyan Jukun, Owolosoho, Obi Town, Madaki, Galadima, Oleye and Okayarda. Finally, ten (10) yam-cowpea farmers were purposively selected from each selected village which gave a total of eighty (80) respondents that were interviewed for the study. Data collection Primary data were collected with the aid of structured questionnaire and personal interview. Data were collected on socio-economic characteristics of respondents, sources of funds, input/output in production and constraints encountered by yam-cowpea intercrops farmers

Analytical techniques

Descriptive statistics such as frequency distribution, mean and percentages were used to analyze objectives (i), (ii) and (v) of the study. The estimation of yam-cowpea production costs and returns in objective iv was computed using gross margin analysis.

The gross margin budgetary technique was given as

GM/ha = TR/ha − TVC/ha ----------------------------Eq. 1 Where GM = Gross Margin (₦/ha), TR = Quantity of Output (₦/ha) and TVC = Quantity of Input (₦/ha).

RNI =GM

TVC----------------------------Eq. 2

Where RNI = Return per Naira Invested, GM = Gross Margin (₦/ha) and TVC = Total Variable Cost (₦/ha).

However, double-log production function model was used to estimate the input-output relationship of yam-cowpea production (objective iii). The model is specified as follows. Log (Y) = βo + β1log(x1) + β2log(x2) + β3log(x3) + β4log(x4) + β5log(x5) + e

Where Y= Value of output (₦/ha), X1=Value of seed (₦/ha), X2= Yam sett (₦/ha), X3= Agrochemical (₦/ha), X4= Labour (Mandays/ha), X5= Value of fertilizer (₦/ha), Βo = Constant term, β1- β5 = Regression coefficient and e = Error term.

RESULT AND DISCUSION Socio-economic characteristics of respondents The socio-economic characteristics of the respondents in the study area were presented in Table 1. The study revealed that yam-cowpea intercropping was dominated by males (83.8%) as against females with 16.3%. This could be attributed to the laborious nature of yam production which most females cannot contend with. The findings are in consonance with the findings of Ebewore et al. (2013) whom reported that yam production is labour intensive that is why it is dominated by males. Also, most of the respondents 73.8% are within the age bracket of 31 to 50 years, with a mean age of 38 years, which was in agreement with some studies (Adesehinwa and Bolorunduro, 2007; Oyegbami et al., 2010). Their studies indicated that the majority of the respondents interviewed had abled aged bracket of 31 to 50 years. This implies that most of the farmers were youth; an economic active age that can contribute immensely and productively to agriculture production.

The result also shows that most of the farmers (81.3) were married while others are single, divorce, or widow(er). This finding agrees with that of Oderhohwo (2008). The implication of the findings is that marriage remains a value culture in the study area. The high percentage of married respondent is due to the fact that they derived enough income from the production of yam and cowpea to support their families. As regards to farming experience, 30% had farming experience of 11 to 15 years, 26.3% had 16 to 20 years and 12.5% had experience of above 20 years, the mean years of farming experience of the farmers was computed to be 9.7. This indicates that yam–cowpea farmers in the study area were relatively experienced implying a significant level of specialization and expertise in production.

On the household size, majority of the respondents 76.3% had household size ranged between 1 to10 persons with a mean of 7.9 indicating that the study area had low household size. Banmeke, (2003) asserted that family size is an important index in any rural development intervention which can affect the outcome of such intervention.

Analysis of the nature of farming of respondents showed that majority of the yam-cowpea intercrops farmers (73.8%) were fulltime farmers, 17.5% were part-time farmers while 8.8% considered farming as a hobby. Majority of the respondents (76.4) had formal education. This may probably have positive influence on adoption of innovation. The study also revealed that large proportion

Onuk et al. 69 Table 1. Distribution of respondents according to socio economic variables.

Variable Frequency Percentage Mean value (�̅�)

Gender Male 67 83.8 Female 13 16.3 Total 80 100 Age < 20 1 1.3

38.0

21-30 13 16.3 31-40 31 38.8 41-50 28 35.0 51-60 4 5.0 >60 3 3.8 Total 80 100 Marital Status Married 65 81.3 Single 10 12.5 Divorce 3 3.8 Widow(er) 2 2.5 Total 80 100 Farming Experience 1-5 1 1.3

9.7

6-10 24 30.0 11-15 24 30.0 16-20 21 26.3 20 and above

10 12.5

Total 80 100 Household size <5 26 32.5

7.9

6-10 35 43.8 11-15 9 11.3 16-20 10 12.5 >20 0 0.0 Total 80 100 Nature of farming Part-time 14 17.5 Full-time 59 73.8 Hobby 7 8.8 Total 80 100 Level of Education Non formal education

19 23.8

Primary 9 11.3 Secondary 27 33.8 Tertiary 25 31.3 Total 80 100 Farm Size <1 29 36.3 2 33 41.3 3 13 16.3 4 4 5.0 5 1 1.3 Total 80 100

Source: Field survey, 2016.


Table 2. Distribution of respondents based on sources of fund.

Sources of fund Frequency Percentage

Personal savings 46 57.5

Friends and relatives 9 11.3

Agricultural bank 4 5.0

Local money lenders 13 16.3

Cooperative society 8 10.0

Total 80 100.0

Source: Field Survey, 2016.

Table 3. Input-output relationship of Yam-Cowpea intercrops.

Parameters Unstandardized

Coefficient (Beta) Std Error

Standardized

Coefficient (Beta) t-value

Constant 1.972 0.523 3.771

Seed (₦/ha) 0.098 0.108 0.088 0.912NS

Yam sett (₦/ha) 0.433 0.075 0.424 5.761***

Agrochemical (₦/ha) 0.302 0.123 0.271 2.452**

Labour (₦/ha) 0.196 0.070 0.187 2.794***

Fertilizer (₦/ha) 0.066 0.053 0.062 1.246NS

R= 0.953;

R2

= 0.908; Adjusted R square = 0.902;

F-value = 147.553***

Source: Field survey, 2016. ***= significant at 1%; ** =significant at 5%; NS= not significant.

of the respondents (77.6%) had farm size of less than or equal to one–to- two hectares of land, 16.3% had farm size of three hectares, 5% and 1.3% cultivated about four and five hectares of land respectively. This shows that the farm sizes are relatively small. This agrees with the findings of Ebewore et al. (2013). They opined that relatively small farm size is disadvantageous to a large extent, as farm size determines output level. Respondents’ sources of fund The sources of fund for the respondents are presented in Table 2. The study revealed that majority of the respondents (57.5%) obtained their capital from their personal savings. 16.3% of the respondents got their capital from local money lenders, 11.3% obtained capital from friends and relatives, while 10% and 5% of the respondents got their capital from cooperatives and Agricultural Bank respectively. This disagree with the findings of Abdulkarim (2015) who stated that local money lenders use stringent policy measures in recovering their money, which had the lowest proportion with 1.2%

Input-output relationship of Yam-Cowpea intercrops

The result presented in Table 3 showed that the coefficient of multiple determinations (R

2) was 0.908,

indicating that 91% of the variation in the dependent variables was explained by the independent variables. The F-test values of 147.533 significant at 1% indicates a significant estimation and a significant R

2. The result

revealed that the regression coefficient for yam sett was 0.433. This implies that if yam sett is increased by 1%, the value of output (₦/ha) will increase by 0.43% and it is significant at 1%. The regression coefficient for agrochemical was 0.302. This implies that if agrochemical is increased by 1% the value of output (₦/ha) will increase by 0.30% and it is significant at 5%. Likewise the regression coefficient for labour was 0.196 which indicates that if labour is increased by 1% the value of output (₦/ha) will increased by approximately 0.20% and is significant at 1%.

Costs and returns to Yam-Cowpea intercrop production

The cost and return analysis of yam-cowpea intercrops

Onuk et al. 71

Table 4. Cost and returns of Yam-Cowpea intercrop production.

Item (Variable Costs/ha) Value (N) Percentage

Labour 24,595.50 10.63

Planting materials (yam sett and seeds)

i. Yam 188,726.54 81.60

ii. Cowpea 706.30 0.31

Agrochemicals 4.472.33 1.93

Fertilizer

i. NPK 1.230.56 0.53

ii. Urea 8,099.20 3.50

iii .Organic Matter 419.84 0.18

Transportation 3,048.53 1.32

Total Variables Costs (TVC) 231,299.12 100.0

Revenue/ha

Yam 464,204.83

Cowpea 21,647.29

Total Revenue (TR) 485,852.12

Gross Margin/ha(TR/ha-TVC/ha) 25,455.30

Return per Naira invested (RNI) 0.11

Sources: Field survey, 2016. farmers is presented in Table 4. Findings from the study revealed that planting materials (yam setts) accounted most to the total variable cost of production with 81.60%, followed by labour 10.6%, fertilizer 4.21%, Agrochemicals 1.9% Transport 1.32%, while cost of seed had the lowest proportion of 0.31%. This finding agrees with that of Ebewore et al. (2013). They asserted that yam setts constitute the highest component of the total variable cost, representing 25.11% of the cost expended by yam farmers in Ika South Local Government Area of Delta State. However, these findings are not in consonance with the findings of Bamire and Segun-Olasanmi (2010) who indicated that labour accounted for the highest proportion of the total variable cost, representing about 50% and 43% of the cost incurred by Male and Female maize–cowpea intercrop farmers respectively in Oyo State. The average gross margin (GM) was N25,455.30 per hectare. The returns per Naira invested (RNI) was 0.11, that is for every 1 Naira invested there was a gain of 11Kobo. These positive values showed that yam–cowpea intercrop production in Obi Local Government Area of Nasarawa state is a profitable enterprise.

Constraints associated with Yam–Cowpea production Presentation in Table 5 revealed the problems associated with yam-cowpea farmers in the study area in decreasing magnitude of importance. The result on constraints to yam-cowpea production in the study area indicates that high cost of inputs with 66.3% is the major constraints that affect yam-cowpea intercrop farmers in the study area. This finding agrees with that of Abubakar et al. (2005), in their study to determine the profitability in yam production in Northern part of Taraba State, Nigeria. They ascertained that the cost of input used in production is high. They further indicated that high cost of inputs serve as disincentive as it negatively affects producers’ profit margin from marketable surplus. Other constraints identified to have contributed negatively to Yam-cowpea production includes; pest/diseases and inadequate capital accounted for 46.3% and 41.3% respectively. Inadequate/lack of extension contact and government policy ranked equally and accounted for 37.5% each. Poor marketing outlet and Inadequate storage facilities


Table 5. Constraints faced by Yam-Cowpea farmers in the study area.

Constraints Frequency Percentage Rank

High cost of input 53 66.3 1st

Pest and diseases 37 46.3 2nd

Inadequate capital 33 41.3 3rd

Inadequate/lack of extension contact 30 37.5 4th

In consistent government policy 30 37.5 5th

Poor marketing outlet 23 28.8 6th

Inadequate storage facilities 20 25.0 7th

Soil fertility 12 15.0 8th

High cost of transportation 11 13.8 9th

Others 4 5.0 10th

Source: Field survey, 2016. *Multiple responses were recorded.

account for 28.8% and 25.0% respectively. Soil infertility and high cost of transportation which are closely related constitutes 15.0% and 13.8% respectively. Others (insecurity, theft, ethnic crisis) were ranked the least in the order of magnitude of importance with 5.0%.

Conclusion The study shown that men participated more in yam-cowpea inter-cropping compared to Women. Yam-cowpea production required much yam setts as indicated by the proportion of yam setts contribution to the total variable cost of production. Yam setts (₦/ha), labour (man-days/ha) and agrochemical (₦/ha) were the significant factors that influenced the value of yam-cowpea output (₦/ha) in the study area. The positive value of the average gross margin per hectare (N 25,455.30) showed that yam-cowpea intercropping is a profitable enterprise. Based on the findings of the study, the following recommendations were made: 1. Farmers should be mobilized to form co-operatives

societies that will facilitate the provision of credits and other agricultural inputs at affordable prices.

2. There is need by development agencies to encourage more female farmers in yam- cowpea intercrops system by better extension service.

3. Improved planting materials (Yam setts and seeds), fertilizers and agro chemicals (pesticides, Insecticides and Herbicides) supply at subsidized rate to farmers in the area should be enhanced.

4. Adequate funds should be made accessible and available for farmers in the study area through the creation of functional rural agricultural microfinance institutions.

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Journal of Agricultural Science and Practice Volume 2. Page 74-85. Published 21st September, 2017



Identifying the potential of some heavy metals toxicity in urban and peri-urban cropping systems in Sierra

Leone

Abdul Rahman Conteh*, Alusaine Edward Samura, Emmanuel Hinckley, Osman Nabay and Mohamed Saimah Kamara

Njala Agricultural Research Centre, Sierra Leone Agricultural Research Institute (SLARI), Sierra Leone.

*Corresponding author. Email: Email: [email protected]. Tel: 232-79 501 135.

Copyright © 2017 Ekele. This article remains permanently open access under the terms of the Creative Commons Attribution License 4.0, which


Received 20th August, 2017; Accepted 11th September, 2017

ABSTRACT: As an essential coping strategy for providing the vital augmentation of food stocks in urban centers, there has been a considerable expansion of urban and peri-urban agriculture in Sierra Leone since the end of the civil war in 2002. In many of these urban and peri-urban cropping sites, sources of water are usually polluted by urban wastes posing potential risk of heavy metal toxicity. This study was carried out to determine the risks associated with heavy metal contamination in urban and peri-urban cropping systems in Sierra Leone. Soil and plant samples were collected from 72 sites from the largest and second largest cities, Freetown and Bo. The samples were analyzed for Zn, Cu, Cr, Ni, Pb and Cd, and the results compared to established reference values. Heavy metals were detected across all sites, with highest concentrations found in Freetown. Values obtained were mostly below the reference values for both soil and plant samples. Some mild risk of toxicity by Cd was observed in densely populated areas of Freetown, but this was not reflected in the plant uptake of Cd. In general, the risk posed by heavy metals in the urban centers of Sierra Leone is minimal, but measures should be taken to prevent further increase in heavy metal concentration in urban cropping sites. Key words: Heavy metal, soil contamination, urban agriculture, urban garbage. INTRODUCTION Sierra Leone experienced a civil conflict between 1991 and 2002, because of which many people fled to the urban centers, especially the capital city, Freetown. Due to urban migration and natural population growth (UNFPA, 2007), Sierra Leone's cities have been growing rapidly. The increase in population has been so fast that the delivery of basic services, such as water supply, sanitation and waste removal cannot keep up. At the end of Sierra Leone’s ten-year civil war in 2002, a significant proportion of the population who had sought refuge in the urban centers decided to remain in these urban centers in search of jobs with the hope of improving their living conditions (Kanu et al., 2009). This resulted in an unprecedented increase in urban populations in Sierra Leone creating high pressures on food supplies. The bulk

of these refugees were rural migrants with a strong agricultural background. In the absence of regular employment, many of these migrants entered into urban and peri-urban agriculture (CFF, 2008), cultivating leafy vegetables and marketing fruits and vegetables within and near the urban centers, especially in Freetown, the capital city and in Bo, the second largest city.

During and after this period, urban farming became one of the survival strategies adopted by the urban population of Freetown, and has significantly contributed to the food supply in the city. Consequently, local and international non-governmental organizations initiated urban and peri-urban agriculture programmes in Freetown. Since 2005, in order to mitigate the impending food crisis, the Ministry of Agriculture in Sierra Leone has been promoting urban


farming under the United Nations Food and Agriculture Organization’s Special Project for Food Security (FAO, 2008a). This caused an expansion of urban and peri-urban agriculture as an essential coping strategy for providing the vital augmentation of food stocks (Kanu et al., 2009). Urban agriculture is now increasingly being recognized as a reliable coping mechanism for redressing food shortages and gaining employment in the urban centers of Sierra Leone.

Urban and peri-urban agriculture is an industry located within (intra-urban) or on the fringes (peri-urban) of a town, a city or a metropolis, which grows and raises, processes and distributes a diversity of agriculture products, using largely human, land and water resources, products and services found in and around that urban area (FAO, 2008b). In addition to supplementing rural agriculture in food supply, urban agriculture creates an avenue for recycling readily available urban organic wastes. However, despite the potential benefits of urban agriculture (Cofie, 2003), there are also potential risks such as heavy metal toxicities (USDA, 2003). The application of numerous bio-solids (livestock manures, composts, and municipal sewage sludge) to land inadvertently leads to the accumulation of heavy metals such as Cadmium (Cd), (Chromium) (Cr), Copper (Cu), Lead (Pb), Nickel (Ni), and Zinc (Zn) in the soil (Farid et al., 2015). Under certain conditions, metals added to soils in applications of biosolids can be leached downwards through the soil profile and can have the potential to contaminate groundwater. Recent studies on some New Zealand soils treated with biosolids have shown increased concentrations of Cd, Ni, and Zn in drainage leachates (Wuana and Okieimen, 2011).

Plants grown in polluted environment can accumulate heavy metals at high concentration causing serious risk to human health when consumed (Naser et al., 2011). Traditional treatments for metal contamination in soils are expensive and cost prohibitive when large areas of soil are contaminated (Tella et al., 2013; Jiang et al., 2014). Moreover, heavy metals are toxic because they tend to bio-accumulate in plants and animals, bio-concentrate in the food chain and attack specific organs in the body (Chatterjee and Chatterjee, 2000; Akinola et al., 2008). Vegetables, especially leafy vegetables, accumulate higher amounts of heavy metals. Roots and leaves of herbaceous plants retain higher concentration of heavy metal than stems and fruits (Yargholi and Azimi, 2008).

There has been a plethora of studies on heavy metal concentration and toxicity in soil, and the literature is abound with such studies (McLaughlin et al., 2000: Mecray et al., 2001; Crusberg et al., 2004; Ghosh and Singh, 2005; Isa and Jimoh, 2013; Chiroma et al., 2014). However, similar studies have not been carried out extensively in the sub-Sahara Africa region. Some studies related to heavy metal concentration have been reported in Nigeria (Ogbonna et al., 2009; Fagbote and Olanipekun, 2010; Opaluwa et al., 2012; Chibuike and

Conteh et al. 75 Obiora, 2014) and in Ghana (Ampofo and Awortwe, 2017). Similar studies carried out in Sierra Leone are rare. As a country recovering from the twin effects of a civil war (1991 to 2002) and the deadly Ebola outbreak (2014 to 2015), understanding the occurrence and concentrations of potentially toxic heavy metals in urban agricultural systems in Sierra Leone will provide a very useful guide for future agricultural and land-use planning and the development of timely intervention strategies. Thus, this study was carried out to determine the risks associated with heavy metal contamination in urban and peri-urban cropping systems in Sierra Leone, with particular reference to the largest and second largest cities of Freetown and Bo.

MATERIALS AND METHODS Study area

Sierra Leone is in the lowland humid tropics on the west

coast of Africa, between latitude 6 55’N and 10 00’N and

longitude 10 16’W and 13 18’W. The country covers a total area of 7.2 million hectares, of which 5.4 million hectares are arable (WFP, 2015). Approximately 56.0 percent of the land is less than 150 meters above sea level. Agriculture, forestry and fisheries are the mainstay of the economy in terms of employment, engaging about 65 percent of the labour force, mostly working in subsistence agriculture (ILO, 2015). The climate is tropical with two pronounced seasons: an intense rainy season from May to October and a dry season from November to April. Annual precipitation ranged between 3,000 and 5,000 millimeters. The national temperatures

generally range from an average of 24.1 to 28.3C, except in the Harmattan period, between November and

February, when it can drop to below 20C at night. The soils are generally poor, acidic, rich in iron oxide and prone to heavy leaching (Rhodes, 1988; Amara Denis et al., 2013).

In collaboration with the Ministry of Agriculture, Forestry and Food security (MAFFS) in Sierra Leone, existing farmer-based organisations and other emerging groups were identified and sensitized on the project with the aim of forming a platform of urban and peri urban farmers in Bo (southern province) and in Freetown (Capital city, western area). Sites were also identified for the assessment of risk of contamination by biotic and abiotic factors and geo-referenced, taking note of the location, chiefdom, longitude, latitude and elevation. Seventy-two sites from the largest and second largest cities, Freetown and Bo, were identified (Figure 1) from which soil and plant samples were collected.

Sample collection and preparation

The study was carried out between June and August


Figure 1. Map of Sierra Leone showing study locations.

2016. Soil and plant samples were collected in July 2016. Shoots of sweet potato (Ipomoea batatas (L.) Lam) were also sampled, as this crop was found in all the sites sampled. Furthermore, this crop is mostly grown in urban farms for the leaves, which are consumed extensively in Sierra Leone as a source of vegetable protein. Using a clean stainless steel shovel, the soil samples were carefully dug out from 0 to 15 cm depth around the plant and the plants were pulled out carefully, ensuring that no part of the root was lost. Plant and soil samples were kept in separate polythene bags and properly labeled. All soil samples were spread on plastic trays and allowed to dry at ambient temperature for 8 days. The dried samples of soils were then ground with a ceramic coated grinder and sieved through a nylon sieve. The final samples were kept in labeled polypropylene containers at ambient temperature before analysis. Compost samples were also collected from selected farms to identify the potential toxicity of these compost materials that are applied to the soils.

In order to eliminate dust, dirt, and possible parasites or

their eggs, the plant samples were initially washed in fresh running water and then again washed with deionized water. The cleaned plant samples were air-dried and then placed in an electric oven at 65°C for 72 h. The dried plant samples were then homogenized by grinding using a ceramic coated grinder normally used for metal analysis. Soil characterization Soil analyses for site characterization were carried out using methods described jointly by the International Soil Reference and Information Centre (ISRIC) and the FAO (ISRIC/FAO, 2002). Soil colour was visually compared with the Munsell Chart. Soil pH was determined on 1:1 soil:water and 1:1 soil:KCl extracts. Exchangeable cations (Na, K, Ca and Mg) were measured on neutral 1N ammonium acetate extracts. Exchangeable K and Na were read on a Flame Photometer while exchangeable Ca and Mg were read on an Atomic Absorption

Conteh et al. 77

Table 1. Summary of Soil characteristics across all sampled sites.

Parameters Minimum Maximum Mean Median Coefficient of Variability (%)

pH (1:1 H2O) 4.33 5.83 4.97 4.96 6.80

pH (KCl) 3.82 4.89 4.16 4.15 5.07

% Organic Carbon 0.60 3.00 1.79 1.60 37.35

Total Nitrogen (%) 0.07 0.16 0.12 0.12 23.45

P (Bray 1) mg/kg 1.16 8.35 3.06 2.54 54.46

Exchangeable K cmol(+)/kg 0.11 0.95 0.56 0.74 60.27

Exchangeable Ca cmol(+)/kg 1.10 2.45 1.77 1.90 23.71

Exchangeable Mg cmol(+)/kg 0.35 1.55 1.18 1.35 32.33

Exchangeable Na cmol(+)/kg 0.05 0.45 0.17 0.15 58.75

Exchangeable Acidity (H+Al) cmol(+)/kg 3.40 5.49 4.77 4.79 8.29

Effective CEC cmol(+)/kg 6.95 9.78 8.46 8.48 8.77

Spectrophotometer (AAS 205, Buck Scientific). Exchangeable Acidity (Al + H) was extracted by 1M KCl and titrated with 0.025 M NaOH. Effective Cation Exchange Capacity (CEC) was calculated as the sum of exchangeable cations and exchangeable acidity (Table 1).

Digestion and determination of heavy metals For the analysis of heavy metals in soils, 2.0 g of prepared soil sample was digested with a mixture of 15.0 ml nitric acid (HNO3), 20.0 ml perchloric acid (HClO4) and 15.0 ml hydrofluoric acid (HF) and placed on a hot plate for 3 hours. On cooling, the digest was filtered into a 100.0 ml volumetric flask and made up to the mark with distilled water. Blanks were prepared to check for background contamination by the reagents used (Louhi et al., 2012).

The plant samples were digested using the nitric–perchloric acid digestion, following the procedure recommended by the AOAC (1990). One gram of plant sample was placed in a 250 ml digestion tube and 10 ml of concentrated HNO3 was added. The mixture was boiled gently for 30 to 45 min to oxidize all easily oxidizable matter. After cooling, 5 ml of 70% HClO4 was added and the mixture was boiled gently until dense white fumes appeared. After cooling, 20 ml of distilled water was added and the mixture was boiled further to release any fumes. The solution was cooled, further filtered through Whatman No. 42 filter paper and then transferred quantitatively to a 25 ml volumetric flask by adding distilled water (Farid et al., 2015).

Analytical grade chemicals were used throughout the analysis. There was no further purification for the preparation of all reagents and calibration standards. Deionized water was used with conductivity <1 dS/cm. Certified metal stock solutions of 1000 mg/L were used by successively diluting with deionized water for preparing calibration standards.

Determination of heavy metals The heavy metal (Zn, Cu, Cr, Ni, Pb and Cd) concentrations were determined by atomic absorption spectrometry using a BUCK SCIENTIFIC Atomic Absorption Spectrophotometer (AAS 205, Buck Scientific, CT, USA) equipped with hollow cathode lamps. The spectral range extends at least from 180 to 900 nm. Quality control was based on the use of standard metal solutions and duplicate analysis (Louhi et al., 2012).

Methods of potential ecological risk assessment Hakanson's potential ecological risk method was used to assess the potential ecological risk of the heavy metal (Hakanson, 1980). This method is able to reflect the effects of various contaminants and reveal the comprehensive influence of multiple contaminants in a particular environment. The specific calculating formulas are as follows: The single Contamination Coefficient, Cf, of a particular heavy metal and is given by: Cf = Ci/Cb Where, Ci is the measured heavy metal content in the soil and Cb is a reference value. The reference value used here is the background content of the soil metal without contamination (Table 2). The Potential Ecological Risk index, ERi, of a particular heavy metal i, is given by: ERi = Ti X Ci Where, Ti is the Toxic Response Factor of a particular heavy metal (Table 3) and Ci is the Contamination Coefficient of that metal.


Table 2. Typical and unsafe heavy metal soil levels (mg/kg sample).

Metal Zn Cu Cr Ni Pb Cd

Typical background Levels for Uncontaminated Soil 125 50 90 50 70 1.0

Unsafe for Leafy or Root Vegetables 200 200 100 200 500 10

Source: Interpreting Soil Heavy Metals. A&L Eastern Laboratories, Inc. 7621Whitepine Road· Richmond, Virginia 23237-2296. www.al-labs-eastern.com.

Table 3. Toxic response factor for selected heavy metals in soils.

Elements Zn Cu Cr Ni Pb Cd

Toxic response factor 1 5 2 2 5 30

Source: Hakanson, 1980; Mugoša et al., 2016.

Table 4. Categories of sampled sites.

Urban Centre Category Title Number of

Sites Sampled

Central GPS Coordinate

Longitude (ºW) Latitude (ºN)

Bo Bo1 4 7º 57.830 11º 43.370

Bo Bo2 4 7º 57.427 11º 47.650

Bo Bo3 4 7º 57.263 11º 44.789

Bo Bo4 4 7º 55.267 11º 43.190

Western Rural WR1 6 8º 19.136 13º 03.578



Western Urban WU1 8 8º 27.601 13º 12.979





The toxic-response factor for the given element mainly reflects the heavy metal toxicity level and the degree of environment sensitivity to heavy metal pollution. The toxic response factor represents the potential hazard of heavy metal contamination by indicating the toxicity of particular heavy metals and the environmental sensitivity to contamination.

Data were analyzed using descriptive statistics, correlation and regression analysis using Microsoft Excel©.

RESULTS AND DISCUSSION

The 72 urban and peri-urban sites identified were categorized into 12 groups, based on proximity of Global Positioning System (GPS) Coordinates (Table 4). While variations existed, it appears from the data that the levels of heavy metals in all sites were mostly below the reference values. In general, the heavy metal concentrations tend to increase as we move from Bo in the south of the country to the major urban center,

Freetown (Table 5). Mean Zn content of the soils across all sites ranged

between 24.19 and 106.79 mg/kg as compared to a reference value of 125 mg/kg while the mean Cu content of the soils across all sites ranged between 15.53 and 77.14 mg/kg as compared to a reference value of 50 mg/kg (Table 5). While the lowest concentration of heavy metal was observed with the Cd, there were more sites showing higher Cd content than the reference value as compared to the other metals.

Mean values for Cr, Ni and Pb ranged between 22.85 and 59.66 mg/kg, 10.42 and 46.00 mg/kg, and 14.79 and 74.34 mg/kg respectively. The highest mean concentration of Zn, Cu, Cr, Ni and Pb were observed in WU4 (Table 5). This does not come as a surprise because WU4 is a densely populated region of Freetown in the Western Urban district with massive and uncontrollable deposition of domestic and industrial waste. In terms of mean values of heavy metals in the various locations studied, the trend observed is Zn>Pb>Cu>Cr>Ni>Cd.

Conteh et al. 79

Table 5. Means of heavy metal levels in soil samples from different locations (mg/kg).

Location Zn ± sd Cu ± sd Cr ± sd Ni ± sd Pb ± sd Cd ± sd

Bo1 40.63 ± 3.66 15.53 ± 1.40 22.85 ± 2.06 10.42 ± 0.94 21.29 ± 1.92 0.85 ± 0.08 Bo2 30.13 ± 3.62 21.71 ± 2.61 23.02 ± 2.07 21.5 ± 12.15 14.79 ± 1.77 0.59 ± 0.06 Bo3 24.19 ± 1.94 19.24 ± 1.54 24.49 ± 2.94 21.49 ± 1.72 17.54 ± 1.40 0.77 ± 0.06 Bo4 25.94 ± 3.37 17.22 ± 2.24 36.93 ± 5.54 15.17 ± 1.67 21.62 ± 2.81 0.91 ± 0.10 WR1 63.25 ± 9.49 32.33 ± 4.85 44.93 ± 4.49 28.70 ± 2.58 26.20 ± 3.93 1.17 ± 0.11 WR2 50.99 ± 4.08 20.77 ± 1.66 38.04 ± 3.04 25.40 ± 3.30 32.52 ± 2.60 1.09 ± 0.14 WR3 60.90 ± 9.74 30.30 ± 4.85 32.79 ± 4.59 29.09 ± 3.20 25.61 ± 4.10 1.21 ± 0.13 WU1 92.32 ± 12.93 41.10 ± 5.75 40.68 ± 7.32 39.47 ± 4.74 44.47 ± 6.23 1.05 ± 0.13 WU2 64.18 ± 10.91 30.25 ± 5.14 40.21 ± 6.43 37.65 ± 5.65 36.60 ± 6.22 0.96 ± 0.14 WU3 78.13 ± 7.81 40.30 ± 4.03 42.70 ± 4.27 35.42 ± 5.67 50.74 ± 5.07 1.09 ± 0.17 WU4 106.79 ± 14.95 77.14 ± 10.80 59.66 ± 9.55 46.00 ± 6.44 74.34 ± 10.41 0.96 ± 0.13 WU5 100.81 ± 16.13 53.99 ± 8.64 42.00 ± 7.56 45.30 ± 8.15 69.84 ± 11.17 1.21 ± 0.22 Reference 125.00 50.00 90.00 50.00 70.00 1.00

Table 6. Variability in heavy metal content of soil and plant samples across all sites.

Parameters Zn Cu Cr Ni Pb Cd

Soil levels (mg/kg)

Min 8.50 10.13 0.96 10.05 10.00 0.25 Max 180.00 118.13 73.00 67.70 136.27 1.65 Mean 65.04 35.31 38.67 31.30 38.46 1.01 SD 44.54 25.49 15.25 11.81 27.27 0.28 Reference 125.00 50.00 90.00 50.00 70.00 1.00 Plant levels (mg/kg)

Min 0.34 0.74 0.59 0.04 0.21 0.01 Max 4.99 5.59 1.70 0.20 1.30 0.05 Mean 2.04 2.01 1.00 0.12 0.55 0.04 SD 1.51 1.36 0.30 0.05 0.33 0.01 Reference 60.00 10.00 1.30 10.00 2.00 1.00

Table 7. FAO/WHO guidelines for metals in foods and vegetables (mg/kg dry weight).

Metal Cd Cu Pb Zn Cr Ni

WHO/FAO Limits 1 10 2 60 1.3 10

Normal Range in Plants < 2.4 2.5 0.5-30 20-100 - 0.002-50

Source: Opaluwa et al., 2012; Nazir et al., 2015.

However, when individual sampled points were considered, the ranges observed in heavy metal concentration were much greater than those observed from the clustered locations. For instance, Zn ranged from a minimum of 8.50 mg/kg to a maximum of 180 mg/kg while Pb ranged from a minimum of 10 mg/kg to a maximum of 136 mg/kg (Table 6). The overall means of heavy metals across all sites is in the order Zn>Pb>Cu>Cr>Ni>Cd. This sequence is different from that observed in Nigeria by Opaluwa et al. (2012) in which the occurrence was Cu > Cd > As > Fe > Co > Pd > Zn > Ni in soil samples from one site and Cd > Cu > Fe > Co > As > Pb > Ni > Zn in soil sample from another

site. With the exception of Cr, the maximum values for all other heavy metals studied were higher than the reference value (Table 6), an indication of potential heavy metal toxicity in some of these sites.

Although the plants (Table 6) took up some heavy metals, the quantities in most cases appear to be less than the reference values given by the WHO/FAO guidelines (Table 7). As was observed with the heavy metal content in soils, the trend in heavy metal uptake in plants tends to increase from Bo to Freetown, with Zn and Cu appearing to have the greatest uptake levels especially in the western urban and western rural locations (Figure 2).


Figure 2. Heavy metal content in plant samples from all locations.

Table 8. Maximum Allowable Limits for Heavy Metals in Soils for Different Countries (mg/kg).

Element Austria Canada Poland Japan UK Germany

Zn 300 400 300 250 300 300

Cu 100 100 100 125 100 50

Cr 100 75 100 - 50 200

Ni 100 100 100 100 50 100

Pb 100 200 100 400 100 500

Cd 5 8 3 - 3 2

Source: Lacatusu, 2000; Fagbote and Olanipekun, 2010.

Sierra Leone has not established limits for heavy metal concentration in soils or plants. However, it can be seen that values obtained for our samples fall below those values established in other countries (Table 8). Across all sites and for all plant samples, the heavy metal contents were below the standards given by the FAO/WHO as shown in Table 6.

The soil contamination index showed some mild risk of heavy metal toxicity in selected locations (Table 10). Soil samples collected from Western Urban 4 (WU4) are particularly at a mild risk of toxicity from copper and lead. Western Urban 5 (WU5) shows light risk of pollution by copper, lead and cadmium (Table 10). This area is a major dump site in Freetown with lots of urban gardening taking place around this site. Despite the very low quantities of Cd observed in all sites, a risk of contamination by Cd occurs in more sites than any of the other metals examined. This is mostly due to the high toxicity factor of Cd (Table 3). As stated earlier in this report, the toxic-response factor for the given element mainly reflects the potential hazard of heavy metal contamination by indicating the toxicity of particular heavy metals and the environmental sensitivity to contamination.

The corresponding degrees of contamination and the

grading standards for the levels of potential ecological risk in Cf and ER are shown in Table 11. As can be seen from the degree of contamination for particular heavy metals and the corresponding grading standards for potential ecological risk (Table 11), and the variability in soil contamination factor and ecological risk factor across all sites (Table 9), mean values for contamination factor of all heavy metals, except Cd, are below 1.0. This means that no major risk of contamination exist at this moment for these metals, except for Cd which shows a mean contamination factor greater than 1.0 (Table 9).

According to the calculated accumulating coefficients (Tables 10 and 12), cadmium appears to be the main heavy metal posing serious toxicity risks in the areas studied. The potential ecological risk tends to increase towards the major urban centers. In a nutshell, the heavy metals under investigation in soils and plants reflected a low ecological risk (Table 12) with the exception of cadmium, which posed a moderate ecological risk (Table 10) in the western area. In the densely populated areas of the western area where intense dumping of garbage occurs, some potential contamination risk for copper and lead was detected (Table 10).

To analyze the relationships among metal concentra-tions, a Pearson’s correlation analysis was applied

0.0

1.0

2.0

3.0

4.0

5.0

6.0

Bo1 Bo2 Bo3 Bo4 WR1 WR2 WR3 WU1 WU2 WU3 WU4 WU5

Hea

vy M

etal

in P

lan

ts (

mg

/kg

)

Zn Cu Cr Ni Pb Cd

Figure 2: Heavy metal content in plant samples from all locations

Conteh et al. 81

Table 9. Variability in soil contamination factor and ecological risk factor across all sites.

Parameters Zn Cu Cr Ni Pb Cd

Soil Contamination factor (Cf)

Min 0.19 0.20 0.25 0.21 0.14 0.59

Max 0.85 1.54 0.66 0.92 1.95 1.21

Mean 0.52 0.71 0.43 0.63 0.55 1.01

SD 0.26 0.41 0.17 0.14 0.29 0.18

Ecological Risk Factor factor (Er)

Min 0.19 1.55 0.51 1.04 1.06 17.63

Max 0.85 7.71 1.33 4.60 5.31 36.30

Mean 0.52 3.53 0.86 3.13 2.75 30.34

SD 0.26 1.55 0.24 1.08 1.95 8.52

Table 10. Soil Contamination Index across all locations.

Locations Soil Contamination factor (Cf)

∑Cf Zn Cu Cr Ni Pb Cd

Bo1 0.33 0.31 0.25 0.21 0.30 0.85 2.25

Bo2 0.24 0.43 0.26 0.43 0.21 0.59 2.16

Bo3 0.19 0.38 0.27 0.43 0.25 0.77 2.30

Bo4 0.21 0.34 0.41 0.30 0.31 0.91 2.49

WR1 0.51 0.65 0.50 0.57 0.37 1.17 3.77

WR2 0.41 0.42 0.42 0.51 0.46 1.09 3.31

WR3 0.49 0.61 0.36 0.58 0.37 1.21 3.61

WU1 0.74 0.82 0.45 0.79 0.64 1.05 4.49

WU2 0.51 0.61 0.45 0.75 0.52 0.96 3.80

WU3 0.63 0.81 0.47 0.71 0.72 1.09 4.43

WU4 0.85 1.54 0.66 0.92 1.06 0.96 6.00

WU5 0.81 1.08 0.47 0.91 1.00 1.21 5.47

No Risk Light Risk

Table 11. Degree of contamination for particular heavy metals and the corresponding grading standards for potential ecological risk.

Risk Index Ranges and Level of Toxicity/Pollution Risk

Cf < 1; None 1 – 2; light 2 – 3; moderate >3; heavy ERi <40; low 40-80: moderate 80-100; strong 100-320; very strong >320; extremely strong

Source: Hakanson., 1980; Mugoša et al., 2016.

(Table 13). Based on data shown in Table 13, Zn, Cu, Cr, Ni and Pb were all strongly correlated with each other, while Cd is only weakly correlated with Zn. It was interesting to note that Cd did not have any significant correlation with any of Cu, Cr, Ni, or Pb. Reasons for this observation are not immediately clear, but very likely due to different origins of Cd compared to the other metals studied.

It was also interesting to note that for all locations, the heavy metal accumulation in plants was well below the limit set by the FAO/WHO. This observation was particularly relevant for Cd which appears to be higher in most of the western area than the reference values used. Despite this potential risk, Cd values in all plant samples were way below the FAO/WHO limits. This means that Cd uptake by plants was low.


Table 12. Ecological Risk Factor (Er) of Soils.

Locations Ecological Risk Factor (Er) of Soils

ER Zn Cu Cr Ni Pb Cd

Bo1 0.33 1.55 0.51 1.04 1.52 25.38 30.33

Bo2 0.24 2.17 0.51 2.15 1.06 17.63 23.76

Bo3 0.19 1.92 0.54 2.15 1.25 23.14 29.20

Bo4 0.21 1.72 0.82 1.52 1.54 27.43 33.24

WR1 0.51 3.23 1.00 2.87 1.87 35.06 44.54

WR2 0.41 2.08 0.85 2.54 2.32 32.80 40.99

WR3 0.49 3.03 0.73 2.91 1.83 36.21 45.19

WU1 0.74 4.11 0.90 3.95 3.18 31.63 44.51

WU2 0.51 3.03 0.89 3.76 2.61 28.66 39.47

WU3 0.63 4.03 0.95 3.54 3.62 32.70 45.47

WU4 0.85 7.71 1.33 4.60 5.31 28.71 48.52

WU5 0.81 5.40 0.93 4.53 4.99 36.30 52.95

No Risk Light Risk

Table 13. Correlation matrix between heavy metals in soil.

Parameters Zn Cu Cr Ni Pb

Zn - - - - - Cu 0.6495** - - - - Cr 0.4686** 0.6471** - - - Ni 0.5392** 0.6892** 0.4891** - - Pb 0.5596** 0.7922** 0.5656** 0.6956** - Cd 0.4134* 0.2193ns 0.2615ns 0.2711ns 0.1792ns

*Significant at P<0.05; **significant at P<0.01; ns not significant.

Absorption of heavy metals by roots is known to be controlled by the concentration of other elements and some interactions have often been reported. These interactions may be positive or negative; the uptake of a given element being improved or depressed by others present at high concentrations in the soil. Macronutrients interfere antagonistically with uptake of trace elements. For example, calcium controls the absorption of Cd, because of competition for available absorption sites at the root surface. Cd and Zn interact in the soil-plant system, causing the well-known Cd/Zn antagonism (Smilde et al., 1992). Zn depresses Cd uptake (Cataldo et al., 1983). The relatively high levels of on Zn measured in this study compared to the other metals could have inhibited the uptake of Cd.

The availability to plants of heavy metals from the soil is also controlled by plant micronutrient requirements and their ability to take up or exclude toxic elements. Some plants are well adapted for survival in stressful environ-mental conditions. They can hold in their tissues amounts higher than 1% of the metal and up to 25% on a dry matter basis. When grown in the same soil, accumulation of Cd by different plant species decreases in the order: leafy vegetables > root vegetables > grain crops (Morel, 1997). Therefore, screening of cultivars that exclude toxic

elements should be a priority to protect food quality. Given that many urban gardens are located on or close

to garbage dump site (Figure 3), this study also examined the heavy metal content of garbage found around urban gardens. This was done to determine the potential contribution of garbage applied to urban farms in contributing to heavy metal toxicity. Contamination factor was calculated using soil reference values due partly to the absence of reference values for garbage, the heterogeneity of garbage material, and the fact that the garbage is being applied to the soil. Risk posed by urban garbage in heavy metal toxicity ranged from none to heavy risk (Table 14).

With the exception of samples collected from Bo1 locations, all other garbage samples collected from other locations show varying degrees of toxicity. Heavy risk of Pb contamination was observed in samples from WU4 and WU5 (Table 14). All other heavy metals show light to moderate risk of soil contamination. This observation, however does not relate directly with observations made on soil samples (Table 10) where the greatest contamination risk was from the cadmium. Possibly the cadmium and other heavy metals in soils are from different origins as was seen with the poor correlation between cadmium and the other heavy metals.

Conteh et al. 83

Figure 3. A common urban garden in Freetown showing vegetables (sweet potato) growing on garbage dump.

Table 14. Contamination Factor (Cf) of Garbage across all locations.

Garbage Contamination factor (Cf)

Locations Zn Cu Cr Ni Pb Cd

Bo1 0.25 0.89 0.54 0.45 0.98 0.68

Bo2 No Sample Collected

Bo3 0.41 1.06 0.56 1.03 0.63 0.81

Bo4 0.76 1.44 0.85 0.75 1.20 1.35

WR1 1.56 1.56 0.92 1.13 1.89 1.43

WR2 No Sample Collected

WR3 1.44 2.02 0.63 1.39 1.38 1.46

WU1 1.50 1.95 0.82 1.66 1.98 1.28

WU2 1.50 1.89 1.21 1.65 1.92 1.43

WU3 No Sample Collected

WU4 3.12 6.68 1.54 2.36 4.69 1.58

WU5 2.22 2.48 1.02 2.08 3.18 1.84

None Light Risk Moderate Risk Heavy Risk

Conclusions and recommendations Values obtained were mostly below the reference values for both soil and plant samples. Some mild risk of toxicity by Cd was observed in densely populated areas of Freetown, but this was not reflected in the plant uptake of Cd. For future outlook, the following recommendations are necessary. 1. Collaborate with the Environmental Protection

Agency for database of Heavy Metals.

2. Development of Threshold Values and periodic monitoring for trends.

3. Further research and possible ways of site remediation should be considered where contamination has been observed.

4. Calculation of pollution indices should be recognized as a useful tool to reduce pollutant emission and minimize the hazard risks to human health.

5. A legal framework for environmental management and urban planning that includes the management of household waste should be advocated.

84 J. Agric. Sci. Pract. 6. Promote environmental education to increase the

level of public participation and to develop appropriate mitigation technologies.

7. Create micro-enterprises for recycling operations as a way of achieving financial sustainability.

ACKNOWLEDGEMENT The authors are most grateful to West and Central African Council for Agricultural Research and Development (CORAF/WECARD) which funded this work under the project titled: "Negative Externalities of Intensification of land cultivated in peri-urban areas: methods and assessment tools and alternative practices”. REFERENCES Akinola, M. O., Njoku, K. L., & Ekeifo, B. E. (2008).

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Journal of Agricultural Science and Practice Volume 2. Page 86-89. Published 30th September, 2017



Proximate composition of rumen digesta from sheep slaughtered in Zuru Abattoir, Kebbi State, Nigeria

A. M. Sakaba1*, A. U. Hassan1, I. S. Harande1, M. S. Isgogo1, F.A. Maiyama2 and B. M. Danbare3

1Department of Animal Health and Production, Kebbi State College of Agriculture, PMB 1018, Zuru, Kebbi State,

Nigeria. 2Department of Entrepreneurship Education, Kebbi State College of Agriculture, PMB 1018, Zuru, Kebbi State, Nigeria.

3Department of Agricultural Technology, Kebbi State College of Agriculture, PMB 1018, Zuru, Kebbi State, Nigeria.

*Corresponding author. Email: [email protected]. Tel: +2348032917303.

Copyright © 2017 Sakaba et al. This article remains permanently open access under the terms of the Creative Commons Attribution License 4.0,

which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Received 9th August, 2017; Accepted 5th September, 2017

ABSTRACT: Biochemical studies with a view to assess the proximate and essential mineral content of sun-dried rumen digesta were carried out. The values for each of the nutrients were collected in triplicates according to the samples analyzed. The results of mean percentages showed the samples contained moisture (5.83±0.17), crude protein (15.52±0.20), lipids (5.17±0.17), fiber (48.73±0.72), ash (11.00±0.29) and carbohydrates (19.98±0.32). The essential minerals were sodium (19.98±0.32), potassium (4.73±0.18), magnesium (0.42±0.03), calcium (0.45±0.03) and phosphorous (4.73±0.03). The results indicated that rumen digesta from sheep slaughtered in Zuru metropolitan abattoir has nutritional qualities that could provide livestock producers with additional nutrients for enhanced animal nutrition. It is therefore recommended for livestock feeding trials in small ruminant production. Key words: Abattoir, proximate composition, rumen digesta, sheep, waste. INTRODUCTION The slaughtering of animals produce essential animal protein in the form of meat for human consumption, this operation is usually carried out in the abattoir. An abattoir is an approved and registered place for hygienic slaughtering, processing, effective preservation, storage and distribution of meat products for human consumption and other industrial uses (Akinro et al., 2009).

The increase in population, urbanization and high demand for animal protein are in direct relationship. The drive to increase meat production for human consumption is attributed to various types of environmental pollutions due to improper practices and hygiene. Considerations are hardly given to safety practices during transportation, slaughtering and processing as such enormous wastes that impact negatively on the environment are produced (Adesemoye et al., 2006).

The wastes produced as a result of abattoir operations are generally termed as abattoir wastes that are either in solid or liquid form (Ayodele and Olufunmilayo, 2012). The solid among them include the condemned carcass, bones, horns, hair, aborted fetuses, faeces and digesta

while the liquid are usually consisted of the dissolved solids, blood, gut content, urine and water. Improper disposal of these wastes products poses a serious problem to human health and environment (Amisu et al., 2003; Fearon et al., 2014).

Animal feed is an essential source of livestock production system which has great effect in the growth of livestock and quality of their products (Okoli et al., 2003). In the developing countries, the feed ingredients are in competition with man for food, this necessitates the search for locally available wastes or by-products to be recycled as livestock feed in order to arrest the situation. Recycling of abattoir wastes as feed stuff for livestock have been a continuous investigation due to global emphases on the use of non-conventional feedstuff in solving inadequate animal protein intake by humans (Agbabiaka et al., 2011). Feeding livestock with animal wastes result in reducing cost and makes possible the integration of livestock production which in turn reduces environmental pollution due proper disposal of abattoir wastes (Esonu et al., 2006).


Rumen digesta is an abattoir waste that is partially digested forage found in the rumen. It is fairly rich in nutrients especially the crude protein that is essential for animal nutrition (Agbabiaka et al., 2011). The use of rumen digesta as feed supplementation could reduce cost, maximize profit and provide environmentally benign disposed of abattoir waste. Unfortunately, this useful practice has not been exploited in the study area. The use of rumen digesta as feed can only be achieved through a proximate analysis which is a biochemical assay chemical that gives an estimate of individual component of feedstuff (FAO, 2003).

Lack of information on the nutrients content of rumen digesta from small ruminants has limited its utilization as livestock feed in the study area. Therefore this study was designed to determine the nutrient composition of rumen digesta obtained from sheep slaughtered in Zuru metropolitan abattoir with a view to explore its potentials as an alternative feed resource.

METHODOGY

Experimental site

This study was conducted in the Department of Animal Health and Production, College of Agriculture Zuru, Kebbi State, Nigeria. Zuru is located within latitude 11

0 35’ and

110 55’ North and Longitude 4

0 45’ and 5

0 25’ East of the

equator. It is geographically located in the Northern Guinea Savannah of the South-Eastern part of Kebbi State (KBSG, 2003). Zuru is the emirate headquarters of zuru emirate. It is located in the extreme South-Eastern part of Kebbi State and covers an area of of approximately 9,000 square kilometers. It is located on the hilly terrain and bounded to the North by Gummi Local Government Area of Zamfara State, North-East by Koko Local Government Area, South-West by Yauri Local Government Area, North-East by Bukkuyum Local Government Area of Zamfara State and South by Rijau Local Government Area of Niger state (Girma, 2008).

Sample collection

A total of 90 samples of rumen digesta from sheep were collected from Zuru metropolitan abattoir between May and June 2015. The collection of these samples coincides with the beginning of the rainy season in the study area. It is also the period when farmers in the area sell their small ruminants for the purchase of farm input. This makes sheep available for slaughter. The samples were sundried for seven days, and then 12 samples were subjected to laboratory analysis.

Analytical procedure

The proximate composition of sundried rumen digesta from sheep was analyzed as described by AOAC (2005).

Sakaba et al. 87 Each sample was analyzed in triplicate. The crude protein was determined according to micro kjeldahl method using Macro Kjeldhal Digestion and Distillation Apparatus (Gerhardt, Germany) and by multiplying the nitrogen content with a factor 6.25. The crude fat was determined by soxhlet extraction method while soluble carbohydrates (NFE) by subtracting the sum of % ash, % crude fibre, % crude fat and % crude protein from 100. That is: NFE = 100 − (%ash + %crude fibre + %crude fat + % crude protein)

Determination of minerals The mineral content of the digesta were analyzed as described by AOAC (2005). Potassium and sodium were determined by Photometric method (FP 640, Jeumeay) while phosphorous was determined through Vonado molybdate Yellow method using spectrometer Jenway 1315 UK. (UV-visible), and calcium, magnesium, iron, cupper and manganese were determined using Atomic Absorption Spectrometer (Buck 210, AAS).

Data collection and statistical analysis The various nutrients and minerals analyzed in the laboratory were observed and their values were analyzed for descriptive statistics (Means ± SE) using SPSS 20

th

version as described by Aliyu et al. (2009).

RESULT AND DISCUSSION The results for proximate and mineral analysis of sun-dried rumen digesta from sheep slaughtered in Zuru central abattoir are presented in Tables 1 and 2. The moisture content of the digesta was 5.83±0.17 (Table 1). This value is lower than 14.48, 16.1 and 7.17 reported by Agbabiaka et al. (2012), Abouheif et al. (1999) and Dairo et al. (2005) respectively. The lower moisture content could be attributed to the processing methods of the sample before laboratory analysis. It is however an indication that sun-dried rumen digesta from sheep can be stored for a long period of time without deterioration. The value for crude protein (15.52±0.2) from this study was the same with Abouheif et al. (1999). These values were however lower than 17.13 and 18.25 reported by Dairo et al. (2005) and Agbabiaka et al. (2012). Variation in the protein content could be attributed to the quality and diversity of the herbage material consumed by the animal, population and activity of the micro-organisms in the rumen in addition to the length of time the animal takes before slaughter after consumption of the forage material. The level of protein from this study indicated the potential of sun-dried rumen digesta from sheep as protein supplement in livestock nutrition. The crude fat


Table 1. Proximate composition of sun-dried rumen digesta from sheep.

Nutrients Mean composition (%)

Moisture 5.83±0.17

Crude protein 15.52±0.2

Lipids 5.17±0.17

Fiber 48.73±0.72

Ash 11.00±0.29

Carbohydrates 19.98±0.32

The values are presented in Mean ± S.E.

Table 2. Mineral composition of sun-dried rumen digesta from sheep.

Minerals Mean composition (%)

Sodium 19.98±0.32

Potassium 4.73±0.18

Magnesium 0.42±0.03

Calcium 0.45±0.03

Phosphorous 4.73±0.03

The values are presented in Mean ± S.E.

(5.17±0.17), fibre (48.73±0.72) and ash (11.00±0.29) were greater than 2.1, 2.8 and 3.57 reported by Abouheif et al. (1999), Dairo et al. (2005) and Agbabiaka et al. (2012) respectively. The higher values of these nutrients could be explained by the silica content of grasses which reduce the ability of the herbivores to digest fiber due to increased tooth wear. The carbohydrates content (19.98±0.32) was however lower than 40.8 and 38.13 reported by Dairo et al. (2005) and Agbabiaka et al. (2012) respectively. This is attributed to the sparing effect of carbohydrates. The values for these chemicals have indicated the ability of the sun-dried rumen digesta from sheep to provide the nutrients required for normal daily activities of livestock.

As shown in Table 2, the sodium (2.44±0.01) and potassium (4.73±0.18) obtained were greater than 3.92 and 0.21 reported by Basher et al. (2002) and Agbabiaka et al. (2012) respectively. The magnesium (0.42±0.03), calcium (0.45±0.03) and phosphorous (4.73±0.03) obtained were lower than 4.1, 8.2 and 7.6 reported by Agbabiaka et al. (2012). The lower levels of minerals was an indication that the sun-dried rumen digesta from sheep alone cannot provide the minerals required by the animals thus supplementation becomes necessary for proper feed utilization and normal physiological function of the body.

Conclusion and recommendations

The results obtained from this study revealed that the sun-dried rumen digesta from sheep slaughtered in Zuru

central abattoir contains vital nutrients that are required for livestock’s normal physiological activities .It is therefore recommended that farmers in the study area should use it for livestock feeding trials. Furthermore, farmers should seek for more knowledge on the processing methods that will aid better utilization of the digesta as feed material to increase productivity. This study also recommended the proximate analysis in large ruminants kept for dairy and fattening purpose. REFERENCES Abouheif, M. A. Kraidees, M. S., & Al-Sebood, B. A. (1999). The

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