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Factors Influencing Adoption of Improved Cowpea Production Technologies in Nigeria Dr. A. E. Agwu Department of Agricultural Extension University of Nigeria, Nsukka Enugu State NIGERIA [email protected] Abstract The paper investigated the socio-economic characteristics and technology-related factors influencing adoption of improved cowpea production technologies among farmers in Bauchi and Gombe States of Nigeria. Data for the study were collected through the use of structured interview schedule from a randomly selected sample of 130 farmers. Descriptive statistics and step-wise multiple regression were used to analyze the data. The findings indicated that majority (69.3%) of the farmers were between 30 – 49 years with a mean family size of seven persons. Seventy percent of them were literate and 57.7 % belonged to one farmer/cooperative organization. The use of insecticides to control pests on cowpea farms had the highest adoption score (4.63). Only farm size and level of formal education positively and significantly influenced adoption of improved cowpea technologies, while three technologies namely, use of tractor for preparing cowpea farmlands, application of inorganic fertilizers at 200 kgha-1 and use of recommended spacing distances on cowpea farms made the highest contribution in explaining variations in the differential adoption of cowpea technologies among the farmers. In view of the low adoption scores recorded for most of the technologies in the improved cowpea technology package, there is need to study the socio-economic environment of the cowpea farmers in order for research and extension to take adequate advantage of their cultural diversities and uniqueness in promoting adoption. Also, efforts should be made to intensify campaigns on these technologies by extension staff to enable farmers benefit from their usage. Keywords: Technology Adoption, Cowpea, Socio-economic Characteristics, Nigeria Introduction Cowpea (Vigna unguiculata (L.) Walp) is an annual grain legume indigenous to tropical Africa (Padulosi and Ng, 1997). It is the most commonly cultivated grain legume in Africa. In West Africa legumes especially cowpea, are of major importance in the livelihood of millions of relatively poor people and account for up to 80% of the total dietary protein intake for adults and are virtually the only source of protein for many children ( Anazonwu-Bello, 1976). In Nigeria, cowpea is the most important indigenous grain legume extensively grown in most areas north of the confluence of the River Niger and Benue, though consumption is distributed all over the country (Singh et al, 1997). Spring 2004

However, low yields are a significant attribute of the country’s cowpea production estimates, with a range of < 100 to 330 kg ha-1 (Mortimore et al, 1997). The major reasons for low productivity include heavy biotic pressures, particularly from insects and other pests which often affect the plant throughout its life cycle and the seeds in storage, sub-optimal planting dates, low plant population, poor weed control, mixed cropping and low soil fertility status. The research efforts of the Institute for Agricultural Research (IAR), Zaria, Institute of Agricultural Research and Training (IAR&T), Ibaban, the International Institute of Tropical Agriculture (IITA) and other scientists in the country using the concept of the Nationally 81

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Coordinated Research Project (NCRP) have led to the development of improved cowpea production practices designed for a broad range of growing conditions (IITA, 1993; Olufajo, 1997). The Agricultural Extension Services of the Institute for Agricultural Research (IAR) and the States’ Agricultural Development Programmes (ADPs) in-charge of disseminating agricultural information to farmers on a nationwide basis, have since 1988 been disseminating research results on these innovations to cowpea farmers (Fadiji et al, 1996). However, despite the comparative advantages offered by the use of these improved cowpea technologies, acceptance and use of the technologies by farmers to boost cowpea production vary and have been far from encouraging (Agwu, 2001). Theoretical Framework Rogers and Shoemaker (1971) and McEwen (1975) conceptualized the innovation decision process to consist of these four functions: knowledge, persuasion, decision and confirmation. A synthesis of this four-stage adoption paradigm shows that for a farmer to adopt an innovation, there are variables pertaining not only to the farmer but also related to the innovation and method of information dissemination that influence farmers’ response. They further observed that agricultural innovations vary tremendously in their inherent characteristics, which to a large extent influence the decision of the farmers to participate. As a result the farmer is more inclined to accept (and participate in) a recommended practice if the practice is profitable, compatible with existing farming system, divisible, simple to use, has relevance for his labour use, farm inputs, marketing, credit, community values and crop situation. Purcell and Anderson (1997) observed that farmers would adopt new technologies and modify their resource use when they believe that the proposed change is relevant to their circumstances and can help them achieve their objectives. They further stated that the rate of adoption of a technology (using technology adoption as a proxy for any desirable change in resource use) by a farming population would depend on the characteristics of individual’s production circumstances, characteristics of the technology itself, socio-cultural characteristics of individual farmers and the speed with which 82

the population is made aware of the technology and its application to local production systems. Purpose and Objectives The purpose of this study was to determine which aspects of the cowpea technology package and farmers’ socioeconomic characteristics were responsible for the variations in the adoption behaviour of the cowpea farmers in Bauchi and Gombe States of Nigeria. The specific objectives were to: 1. describe the socio-economic characteristics of the cowpea farmers; 2. determine the level of adoption of the cowpea technologies disseminated to the farmers; 3. examine socio-economic characteristics of the farmers influencing the use of the technologies; and 4. determine technology-related factors influencing the use (adoption) of the improved cowpea technology package. Methodology The study was conducted in Bauchi and Gombe States of Nigeria. The two states have a combined population of 4.2 million (Federal Office of Statistics, 1996) and a combined land area of 64,605 km2. Average population density is 65 persons per km2. The mean annual rainfall ranges between 1000mm and 1500mm (Shaib et al, 1997). The two states have similar ecological features and fall within the sub-humid sub-zone of the northeast savanna zone of Nigeria. The Bauchi State Agricultural Development Programme (BSADP) divided Bauchi state into fifty-seven (57) extension blocks, while the Gombe State Agricultural Development Programme (GSADP) divided Gombe state into fifty-two extension blocks. Using the delineation by the BSADP and GSADP, seven and six extension blocks were randomly selected from Bauchi and Gombe States, respectively. From each block 10 to 12 farmers were selected for interview using a simple random sampling technique. In all 145 cowpea farmers were sampled using structured interview schedule. However, only 130 completed interview schedules were used for analysis. Generally, the interview schedule was designed to generate information in the following areas: bio-data and farm characteristics of the farmers as well as, technology-related variables. Four trained Journal of International Agricultural and Extension Education

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interviewers under close supervision of the researcher administered copies of the interview schedule. In some cases the interviewers had to interpret the questions in Hausa language for the illiterate farmers. To determine individual adoption scores of farmers, they were asked to indicate their adoption stages for the various cowpea technologies, using the seven steps (not aware to rejection) adoption model (Madukwe et al, 2000). Items included in the package of improved cowpea production technology were: use of improved cowpea varieties; hiring/use of tractor for land preparation; use of recommended spacing (inter-row 75cm and within-row 20 – 30 cm); application of single super phosphate before planting; application of fertilizer at 200 kgha-1 of cowpea farmland; use of herbicides for weed control; spraying with fungicides 5 weeks after sowing to control diseases and spraying with insecticides during the post-flowering period to control pests (Fadiji et al., 1996). However, in view of the variations in technology recommendations, specifically for planting distances, application of single super phosphate before planting and application of fertilizers at 200 kgha-1 between sole crops and mixtures, data for these technologies were derived only for sole- cropped cowpeas. Data relating to socio-economic variables of the farmers were analyzed using means, frequency counts and percentages. Multiple regression analysis with stepwise selection was used to determine the socioeconomic characteristics of farmers and technology related variables influencing the adoption of improved cowpea technologies among farmers.

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Results and Discussion Socio-Economic Characteristics of the Farmers Entries in Table 1 show that 2.3% of the farmers were below 30 years of age. Those that fell within the age range of 30 – 49 years accounted for 69.3 %, about 18% of the respondents were of the age range of 50 - 59 years, while about 11% of the respondents were either 60 years of age or more. The average age of the respondents was about 45 years. The implication of these findings is that majority of the respondents belong to the young and middleaged group. This is an advantage since they are supposed to be physically able and more mentally alert in learning new technologies than the older farmers. Table 1 further shows that those who had between zero and four people in the family consisted 36.2% of the respondents. About 37% of the respondents had between five and nine people in the family, while about 30% had over nine people in the family. The average family size of the respondents was approximately seven. One of the most important factors conditioning the level of production and productivity of small-scale farmers is the composition and size of the family. Hence the relatively large family size of the farmers is an obvious advantage, since it may likely enable the farmers to use family labour, thereby reducing labour cost required in cowpea production. It is also evident from Table 1 that 30% of the farmers had no formal education. About 39% of the respondents attended primary school, 12% had secondary school education and the remaining 20% attended post-secondary school. Education has been shown to be a factor in the adoption of yields increasing modern farm practices. The low proportion of illiterates in the respondents’ group implies that the majority of them are in a better position to be aware of, understand and adopt improved cowpea technologies.

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Table 1 Percentage Distribution of the Cowpea Farmers by Socio-Economic Characteristics (n = 130) Socio-Economic Characteristics Percentage Age Range 20 – 29 years 2.3 30 – 39 years 26.2 40 – 49 years 43.1 50 – 59 years 17.7 60 years and above 10.8 M = 45.3 years Family Size 0 – 4 people 36.2 5 – 9 people 36.9 10 people and above 29.9 M = 7 people Educational Qualification No formal Education 30.0 Primary School Education 38.5 Secondary School Education 11.5 Post-Secondary School Education 28.5 Farming Experience 0 – 9 years 7.7 10 – 19 years 31.5 20 – 29 years 32.3 30 years and above 28.5 M = 22.6 years Membership of Farmer/Cooperative Organization None 11.5 1 Farmer/Cooperative Organization 57.7 2 Farmer/Cooperative Organizations 22.3 3 Farmer/Cooperative Organizations 7.7 4 Farmer/Cooperative Organizations and above 0.8 Farm Size 8.5 ≤ 1.9 Hectares 2.0 – 3.99 Hectares 18.5 4.0 – 5.99 Hectares 30.8 6.0 – 9.99 Hectares 22.3 10 Hectares and above 20.0

About 8% of the respondents had below nine years of farming experience (Table 1). Thirty-two percent had between 10 and 19 years of farming experience, while about 61% had 20 years of farming experience and above. The average number of years of farming experience of the farmers was 22.6 years. This implies that majority of the cowpea farmers had long period of farming experience and therefore would be conversant with constraints to increased cowpea production. This could increase their level of acceptance of new ideas as a means of overcoming their production constraints and 84

hence could serve as an advantage for increased cowpea production. The findings further indicate that majority (57.7%) of the respondents belonged to one farmer/cooperative organization, 22.3% belonged to 2 farmer/cooperative organizations, while 7.7% belonged to 3 farmer/cooperative organizations. Only about 1% belonged to four or more farmer/cooperative organizations. However, 11.5% of the respondents did not belong to any farmer/cooperative organization. According to Peterson (1997), farmer organizations offer an effective channel for Journal of International Agricultural and Extension Education

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extension contact with large number of farmers, as well as, opportunities for participatory interaction with extension organizations. By the classification of Shaib et al., (1997), farm holdings in Nigeria fall into three broad categories, namely: small scale, medium scale and large scale. Small-scale farmers in this study comprise 57.8% of the respondents cultivating 0.10 to 5.99 hectares often in two or more separate parcels; medium-scale farmers (22.3%) cultivating 6.0 to 9.99 hectares; and large-scale farmers (20%) cultivating 10 hectares of land or more. These findings differ from the findings of a study carried out in southeastern Nigeria (Agwu and Anyanwu, 1996) where the number of hectares cultivated per farmer was found to be about 1.5 hectares. This implies that farmers in the northeast savanna zone of Nigeria cultivate relatively larger hectares of land than their counterparts in southeastern Nigeria. This is an advantage for adoption of innovative practices. Adoption of Technologies The adoption scores of the eight-cowpea production technologies disseminated to the farmers are presented in Table 2. Highest adoption score of 4.63 was recorded for the use of insecticides to control pests on cowpea farms. This is not surprising, as it is well known that

the yields of improved cowpea varieties are generally near zero without the use of insecticides. Hence, the high level of adoption associated with the use of this technology implies that farmers in the area were aware of the fact that spraying their cowpea farms with insecticides provides an attractive opportunity for them to make better economic gains. Planting of improved cowpea varieties and use of recommended planting distance (75 x 20 – 30 cm) recorded adoption scores of 3.18 and 2.69, respectively, while the use of tractors for land preparation and application of single super phosphate before planting had adoption scores of 2.67 and 2.55, respectively. Field practices show that the use of oxen for land preparation was more popular than the use of tractors among the farmers. This could be attributed to the fact that majority of the farmers own these work animals. Also, the cost of hiring these animals for land preparation was found to be cheaper than the cost of hiring a tractor for the same area of land. The low adoption scores for spraying with fungicides (5 weeks after sowing) (2.32), application of fertilizer at 200 kgha-1 (2.12) and use of herbicides for weed control (1.92) might be related to the low level of awareness of the three technologies among the farmers as well as high cost of the chemicals.

Table 2 Adoption of Cowpea Production Technologies by Farmers (n = 130)

Cowpea Production Technologies Planting of improved cowpea varieties Hiring/use of tractors for land preparation Use of recommended spacing distance (75cm x 20 – 30 cm) Application of single super phosphate before planting Application of fertilizer at 200 kg/ha-1 Use of herbicides for weed control Spraying with fungicides (5 weeks after sowing to control diseases) Spraying of insecticides (during the post-flowering period to control pests) Socio-Economic Characteristics of Farmers influencing Adoption To examine the farmers’ characteristics that influence adoption of improved cowpea technologies, adoption scores of the farmers were regressed stepwise on the selected characteristics. Table 3 summarizes the order in Spring 2004

f 73 39 51 39 31 19 35 110

Percentage 56.2 30.0 39.2 30.0 23.8 14.6 26.9 84.6

Adoption score 3.41 2.67 2.69 2.55 1.92 2.32 2.12 4.63

which the variables entered into the regression equation. The result indicates that only two variables (farm size and level of formal education) out of the six selected variables (age, family size, level of formal education, farming experience, membership of farmer/cooperative organizations and farm size) positively and 85

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significantly influenced adoption of improved cowpea technologies (p < 0.05) and hence were important in predicting adoption behaviors. Farm size contributed 7.58% to the explained variation in adoption, while level of formal education contributed 3.22%. The two variables jointly explained 10.8% of the variation in adoption of cowpea technologies and by implication; increases in farm size and level of formal education would increase the adoption of improved cowpea technologies.

The result also shows that age, membership in farmer/cooperative organizations, farming experience and family size had no significant influence on the adoption of improved cowpea technologies. However the studies of Ajala (1992) and Ikani et al. (1998) show that farmers’ age, farming experience and organizational participation significantly influenced adoption. The difference might be the type of technologies studied among other factors.

Table 3 Summary Result of Stepwise Multiple Regression Analysis of the Influence of Socio-Economic Characteristics on Adoption of Improved Cowpea Technologies Socio-Economic Characteristics R2 Change Regression Coefficient F Farm Size 0.07580 0.291679 (0.079159) 13.577 Level of Formal Education 0.03223 0.204343 (0.096383) 4.590 (Constant) 21.00691 (1.143896) Note. Figures in parentheses are standard errors. R2 =0.10803 (6.20466); R2 Adjusted = 0.09399; F = 7.69089; [p < 0.05]

Influence of the Various Improved Cowpea Technologies on Adoption To determine the magnitude of each cowpea technology in explaining the variation in total adoption, the total adoption scores of the respondents were regressed on their adoption scores for various cowpea technologies. The order in which the technologies were selected gives valuable information on the contribution of each technology in explaining the differences in total adoption of the farmers. Table 4 summarizes the order in which the variables entered into the regression equation. The result indicates that all the technologies significantly contributed to variations in total adoption (P < 0.05). The first technology to enter the regression equation was the use of tractor for preparing cowpea farmlands. It explained 39.78% of the variation in adoption of improved cowpea technologies. This was followed by application of fertilizer at 200 kgha-1 (19.13%) and use of recommended spacing on cowpea farms (8.96%). Others include use of herbicides for weed control on cowpea farms (5.66%), application of inorganic fertilizers before planting (5.04%), use of improved cowpea varieties (3.49%) and use of insecticides to control pests (2.15%). The technologies could be grouped into three based on the additional percentage (R2 86

change) each technology contributed to the explained variation in total adoption. The first group consisted of those that contributed at least 10% to the explained variation and by implication made the highest contribution in explaining variations in differential adoption. These include the use of tractor for preparing cowpea farmlands, application of inorganic fertilizer at 200 kgha-1 and use of recommended planting distances on cowpea farms. The implication is that those who highly adopted the improved cowpea technology package adopted these technologies. However, these technologies have acceptance problems among the majority of farmers and therefore call for attention by extension to either change the transfer method and emphasis or that of research modifying or replacing the technologies. The second group of technologies consisted of those that contributed up to 5% but less than 10% of the observed variations in total adoption; these include use of fungicide, use of herbicides and application of inorganic fertilizers before planting, while, the third group included technologies that contributed less than 5% to the explained variation in total adoption. These include the use of improved cowpea varieties and the use of insecticides to control pests in cowpea farms.

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Table 4 Summary Result of Step-Wise Multiple Regression Analysis of Total Adoption on Improved Cowpea Technologies R2 Regression F Improved Cowpea Technologies (Eqn) Change Coefficients Use of Tractors for preparing Cowpea farmlands 0.3978 0.9593 (0.0368) 84.558 Application of fertilizer at 200 kgha-1 0.1913 0.9907 (0.0403) 91.053 Use of recommended spacing distances on cowpea farms 0.1458 0.8715 (0.0466) 116.432 Use of fungicides to control diseases on cowpea farms 0.0896 0.9833 (0.4171) 146.800 Use of herbicides to control weeds on cowpea farms 0.0566 0.9655 (0.4500) 173.429 Application of inorganic fertilizer before planting of cowpea 0.0504 1.0544 (0.0379) 278.895 Use of improved cowpea varieties 0.0349 1.0585 (0.0425) 500.825 Spraying of insecticides to control pests on cowpea farms 0.0215 1.1134 (0.0760) 1231.583 Constant - 0.0968 (0.3747) Note. Figures in parentheses are standard errors. R2 = 0.98787 (0.81350); R2 Adjusted = 0.98707; F = 1231.58275; [p < 0.05] Conclusion It has become evidently clear that the efforts of Agricultural Extension Services of the IAR and the different states’ ADPs at disseminating improved cowpea technologies to farmers had not made the desired impact, and as such most of the improved technologies had low adoption scores. Only the planting of improved cowpea varieties and use of insecticides to control pests on cowpea farms had high adoption scores. This calls for better information on user needs. Hence, determining farmers’ criteria for selection and using such as a basis for developing new cowpea technologies will save scare resources that would otherwise be wasted. The step-wise regression analysis postulates adoption as a function of some socioeconomic and technology related variables. The result reveals that among the six socio-economic variables considered; only farm size and level of formal education were the most significant factors that influence farmers’ adoption of improved cowpea technologies in the study area. While the use of tractors for preparing cowpea farmlands, application of inorganic fertilizers at 200 kgha-1 and use of recommended spacing distances on cowpea farms made the highest contribution in explaining the variations in differential adoption of cowpea technologies among the farmers. The relationship between education and adoption of cowpea technologies must be fully exploited. In this regard, extension agents should identify literate farmers who should be taught the technical skills involved in improved cowpea technologies and who should Spring 2004

be used to disseminate useful information to other farmers in the area. Again, appropriate extension publications such as guides, leaflets and posters (preferably in local languages) could be used. In conclusion, efforts at increasing the rate of improved cowpea technology adoption by farmers should include studying the socioeconomic environment of cowpea farmers in order for research and extension to take adequate advantage of their cultural diversities and uniqueness in promoting adoption. References Agwu, A. E., & Anyanwu, A. C. (1996). Sociocultural and environmental constraints in implementing the NALDA Programme in South eastern Nigeria: A case study of Abia and Enugu States, Journal of Agriculture, Technology and Education, 1(2), 68-72. Agwu, A. E. (2001) Adoption of improved cowpea production technologies by farmers in the North East Savannah Zone of Nigeria, Privatization and Commercialization of Agricultural Extension Services Delivery in Nigeria: Prospects and Problems, T.A. Olowu (Ed.) Proceedings of the seventh Annual National Conference of the Agricultural Extension Society of Nigeria 19th – 22nd August, 2001, pp 74 – 81. Ajala, A. A. (1992). Factors Associated with Adoption of Improved Practices by Goat Producers in Southeastern Nigeria. Research Monograph No. 5, Department 87

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of Agricultural Extension, University of Nigeria, Nsukka. Anazonwu-Bello, J. N. (1976). Food and Nutrition in Practice. Macmillian Educational Limited London. Fadiji, T. O., Gefu, T. T., & Adeniji, O. B. (1996). This is the Institute for Agricultural Research (IAR), Third Edition, Publication and Information Unit, IAR Samaru, Zaria. Federal Office of Statistics. (1996). Annual Abstract of Statistics, (1996 Edition), Federal Office of Statistics Lagos, Nigeria. Ikani, E. I., Annatte, A. I., Umaru, M., & Jegede, O. C. (1998). Study of extent of adoption of cockerel exchange technology (CET) by rural farmers in Adamawa State of Nigeria. Proceedings of the Silver Anniversary Conference of the Nigeria Society for Animal Production (NSAP). 21-26 March 1998. International Institute of Tropical Agriculture. (1993). Grain Legume Improvement Program, Crop Improvement Division Activity Report and Work Plan, IITA, Ibadan Nigeria. Madukwe, M. C., Ayichi, D., & Okoli, E. C. (2000) Issues in Yam minisett Technology Transfer to farmers in Southeastern Nigeria. Africa Technology Policy Working paper No 21. African Technology Policy Studies (ATPS) Network, Nairobi. McEwen, J. W. (1975) Communication, innovation and change. In G. J. Hanneman and J. W. McEwen (eds.), Communication Behaviour, Massachusetts, London, Addison-Wesley Publishing Company, Inc. Mortimore, M. J., Singh, B. B., Harris, F., & Blade, S. F. (1997). Cowpea in traditional cropping systems, In B. B. Singh, D. R. Mohan Raj, K. E. Dashiell, and L. E. N. Jackai (eds.), Advances in Cowpea Research, Co-publication of International Institute of Tropical Agriculture (IITA) and Japan International Research Centre for Agricultural Sciences (JIRCAS), IITA, Ibadan, Nigeria.

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Olufajo, O. O. (1997). Cowpea. In Adedipe, N. O., Bakshi, J. S. and Aliyu, A. (eds.) The Nigerian Agricultural Research Strategy Plan and Extension Delivery: Policy Concept and Consensus to the 2010. Monograph No 7, 116-127. Padulosi, S., & Ng, NQ. (1997). Origin, Taxonomy, and Morphology of Vigna Unguiculata (L.) Walp. In B. B. Singh, D. R. Mohan Raj, K. E. Dashiell and L. E. N. Jackai (eds.), Advances in Cowpea Research. Co-publication of International Institute of Tropical Agriculture (IITA) and Japan International Research Centre for Agricultural Sciences (JIRCAS), IITA Ibadan, Nigeria. Peterson, W. (1997). The context of extension in agricultural and rural development. In B. E. Swanson, R. P. Bentz, and A. J. Sofranko (eds.), Improving Agricultural Extension: A Reference Manual, Food and Agriculture Organisation of the United Nations, Rome, 21-26. Purcell, D. L., & Anderson, J. R. (1997). Agricultural Extension and Research Achievements and Problems in National Systems, A World Bank Operations Evaluation Study, The World Bank, Washington, D.C. Rogers, E. M., & Shoemaker, F. F. (1971). Communication of Innovations: A crosscultural Approach, Second Edition, New York, The Free Press, Collier Macmillian Publishing Co. Inc. Shaib, B., Aliyu, A., & Bakshi, J. S. (eds.) (1997). Agricultural Zones. Nigeria: National Agricultural Research Strategy Plan 1996-2010. Department of Agricultural Sciences, Federal Ministry of Agriculture and Natural Resources, Abuja, Nigeria, Intec Printers Limited, Ibadan. Singh, B. B., Chambliss, O. L., & Sharma, B. (1997). Recent advances in cowpea breeding. In B. B. Singh, D.R. Mohan Raj. K.E. Dashiell and L.E.N. Jackai (eds.), Advances in Cowpea Research, Copublication of International Institute of Tropical Agriculture (IITA) and Japan International Research Centre for Agricultural Sciences (JIRCAS), IITA, Ibadan, Nigeria, 30-49.

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