DETERMINANTS OF FARMERS’ PERCEPTION AND ADOPTION OF IMPROVED LEGUME VARIETIES AMONG FARMING HOUSEHOLDS IN NORTHERN NIGERIA

Authors

  • H EGWUMA
  • F. SIEWE
  • A.B. MOHAMMED
  • U.A. ANGARA

DOI:

https://doi.org/10.33003/jaat.2022.0802.13

Keywords:

Perception, improved legume variety, ordered probit, sample selection

Abstract

Limited understanding of farmers’ perception and consideration during the development of improved seed varieties have usually resulted to their low rate of adoption. In light of this, the present study fitted an ordered probit sample-selection model using a sample of 400 legume farming households (LFHs) - 212 adopters and 188 non-adopters - in Northern Nigeria. The results showed that male-headed households (97%) dominated the sampled data with the majority being soybean farmers (81%) and whose standard of living was low. Household heads were adults (43 years old) and married (94%) in most cases with about a junior level of education (9 years). Key determinants of adoption of improved legume varieties (ILV) included education, household size, level of living, and soil conservation practices. Farmers’ perception was confirmed to be endogenously determined within the adoption system as being a function of socioeconomic characteristics, farm enterprises and agricultural practices. We recommend that farmers’ educational level be improved by increasing their knowledge of relevant agricultural practices such as minimum tillage and alley cropping that will aid the adoption of the ILV through positive perception among farmers. Policies that will enable both male- and female-headed households to have more access to land should be engaged in order to boost the adoption of ILV. Interventions that will aid rural areas in northern Nigeria to have improved standard of living such as better access to light, water, and healthcare facilities should be pursued since this will facilitate the sustainability of ILV adoption.

References

Adetomiwa, K., Mayowa, O. O., Adebayo, A. I. & Victor, O. O. (2020). Impact assessment of Fadama III Group Participation on food security status of rural households in South West, Nigeria. Journal of Agriculture and Sustainability, 13.

Ahmed, B., Echekwu, C. A., Mohammed, S. G., Ojiewo, C., Ajeigbe, H., Vabi, M. B., ... & Nwahia, O. C. (2020). Analysis of Adoption of Improved Groundnut Varieties in the Tropical Legume Project (TL III) States in Nigeria. Agricultural Sciences, 11(02), 143-156.

Ambali, O. I., Areal, F. J., & Georgantzis, N. (2021). Improved rice technology adoption: The role of spatially-dependent risk preference. Agriculture, 11(8), 691.

Awotide, B. A., Karimov, A. A., & Diagne, A. (2016). Agricultural technology adoption, commercialization and smallholder rice farmers’ welfare in rural Nigeria. Agricultural and Food Economics, 4(1), 1-24.

Bannor, R. K., Kumar, G. A. K., Oppong-Kyeremeh, H., & Wongnaa, C. A. (2020). Adoption and impact of modern rice varieties on poverty in Eastern India. Rice Science, 27(1), 56-66.

Borah, M., & Deb, B. (2020). A Review on Symptomatology, Epidemiology and Integrated Management Strategies of Some Economically Important Fungal Diseases of Soybean (Glycine max). Int. J. Curr. Microbiol. App. Sci, 9(11), 1247-1267.

Chase, P.; Singh, O.P. (2014). Soil Nutrients and Fertility in Three Traditional Land Use Systems of Khonoma, Nagaland, India. Resource Environment, 4, 181–189.

Chatterjee, S., & Kar, A. K. (2017). Effects of successful adoption of information technology enabled services in proposed smart cities of India: From user experience perspective. Journal of Science and Technology Policy Management.

Desmae, H., Sako, D. & Konate, D. (2022). Optimum plant density for increased groundnut pod yield and economic benefits in the semi-arid tropics of West Africa. Agronomy, 12(1474): 1-19. doi.org/10.3390/agronomy12061474

Dessalegn, B., Asnake, W., Tigabie, A., & Le, Q. B. (2022). Challenges to Adoption of Improved Legume Varieties: A Gendered Perspective. Sustainability, 14(4), 2150.

Dontsop-Nguezet, P.M., Diagne, A., Okoruwa, V.O & Ojehomon, V. (2011). Impact of improved rice technology (NERICA varieties) on income and poverty among rice farming households in Nigeria: a local average treatment effect (LATE) approach. Quarterly Journal of International Agriculture 50(3): 267-291.

Egwuma, H., Ojeleye, O.A., Siéwé, F., Oladimeji, Y.U, Mukhtar, U. (2021). Impact of Participation in Cassava Processing on Farm Households Income in Kaduna State, Nigeria. Nigerian Association of Agricultural Economists, National Conference, Lafia 2021.

FAOSTAT (2021). Statistical Data Base of Food and Agricultural Organizations of the United Nations: Rome, Italy. Visited on 29/05/2021

Folorunso, S. T. (2015). Impact of Fadama III on Productivity, food security and poverty status of tuber farmers in central states of Nigeria. Unpublished PhD Thesis, Depatment of Agricultural Economics Ahmadu Bello University, Zaria, Kaduna State, Nigeria.

Greene, W. H & Hensher, D. A. (2010). Ordered choices and heterogeneity in attribute processing. Journal of Transport Economics and Policy (JTEP) 44(3): 331-364.

Heckman, J. J. (1979). Sample selection bias as a specification error. Econometrica: Journal of the Econometric Society 47(1): 153-161.

Herath, M. M., Ahmad, N. & Mujaheed, M. (2021). A Review on Empowering Farmers through Technology Adoption towards Poverty Alleviation in Developing Countries. International Journal of Academic Research in Business and Social Sciences, 11(11), 1785-1805.

Iticha, M. D. & Taresa, B. (2020). Factors affecting adoption of soybean production technologies in Ethiopia. Journal of Biology, Agriculture and Healthcare, 10 (5): 24-32. https://doi. org, 10.

Jirgi, A. J., Ogundare, T., Ojo, M. A. & Adewumi, A. (2019). Effects of Fadama III AF sorghum production development programme on women and youths in Niger state, Nigeria. In 3rd International Conference on Food and Agricultural Economics, 25-26 April 2019, Alanya, Turkey.

Jones-Garcia, E. & Krishna, V. V. (2021). Farmer adoption of sustainable intensification technologies in the maize systems of the Global South. A review. Agronomy for Sustainable Development, 41(1), 1-20.

Kamara, A. Y., Ewansiha, S. U. & Menkir, A. (2014). Assessment of nitrogen uptake and utilization in drought tolerant and Striga resistant tropical maize varieties. Archives of Agronomy and Soil Science, 60(2), 195–207. doi.org/10.1080/03650340.2013.783204

Kamara, A. Y., Oyinbo, O., Manda, J., Kamsang, L. S. & Kamai, N. (2022). Adoption of improved soybean and gender differential productivity and revenue impacts: Evidence from Nigeria. Food and Energy Security, 11, e385. doi.org/10.1002/fes3.385

Kassie, G.T., Abdulai, A., Greene, W.H., Shiferaw, B., Abate, T., Tarekegne, A. & Sutcliffe, C. (2017). Modeling preference and willingness to pay for drought tolerance (DT) in maize in rural Zimbabwe. World Development, 94: 465–477.

Khojely, D. M., Ibrahim, S. E., Sapey, E. & Han, T. (2018). History, current status, and prospects of soybean production and research in sub-Saharan Africa. The Crop Journal, 6(3), 226–235. doi.org/10.1016/j.cj.2018.03.006

Love, A., Magnan, N. & Colson, G. J. (2014). Male and female risk preferences and maize technology adoption in Kenya (No. 329-2016-13223).

Luca, G. D. & Perotti, V. (2011). Estimation of ordered response models with sample selection. Stata Journal 11(2): 213–239.

Mahama, A., Awuni, J. A., Mabe, F. N. & Azumah, S. B. (2020). Modelling adoption intensity of improved soybean production technologies in Ghana: A generalized Poisson approach. Heliyon, 6(3), e03543. doi.org/10.1016/j.heliy on.2020. e03543

Mekonnen, T. (2017). Productivity and household welfare impact of technology adoption: Micro-level evidence from rural Ethiopia. UNU-MERIT Working Paper Series, (2017-007).

Mignouna, D. B., Manyong, V. M. & Rusike, J. (2011). Determinants of Adopting Imazapyr-Resistant Maize Technologies and its Impact on Household Income in Western Kenya. AgBioForum 14(3): 158-163.

Moges, D. M. & Taye, A. A. (2017). Determinants of farmers’ perception to invest in soil and water conservation technologies in the North-Western Highlands of Ethiopia. International Soil and Water Conservation Research, 5(1), 56-61.

Moremedi, G., Hulela, K. & Maruatona, T. L. (2019). Factors perceived to influence the adoption of improved technologies in arable farming in the southern district of Botswana. International Journal of Agricultural Extension, 6(3), 193-202.

Moses, J. D. (2017). The impact of Fadama III on the poverty status of food crop farmers in Yobe State, Nigeria. Sky Journal of Agricultural Research, 6(4), 78-84.

Mutegi, J. & Zingore, S. (2014). Boosting soybean production for improved food security and incomes in Africa. Nairobi: The International Plant Nutrition Institute (IPNI), Sub-Saharan Africa Program Google Scholar.

Mwakatwila, A. & Mishili, F. J. (2019). Extent of adopting improved maize varieties in northern and eastern zones of Tanzania. Invited paper presented at the 6th African Conference of Agricultural Economists, September 23-26, 2019, Abuja, Nigeria.

Nakazi, F., Njuki, J., Ugen, M. A., Aseete, P., Katungi, E., Birachi, E. & Nanyonjo, G. (2017). Is bean really a women’s crop? Men and women’s participation in bean production in Uganda. Agriculture & Food Security, 6(1), 22.

Njuguna, I. M., Munyua, C. N. & Makal, S. K. (2015). Influence of Demographic Characteristics on Adoption of Improved Potato Varieties by Smallholder Farmers in Mumberes Division, Baringo County, Kenya. Journal of Agricultural Extension and Rural Development 7(4): 114-121.

Ntshangase, N. L., Muroyiwa, B. & Sibanda, M. (2018). Farmers’ perceptions and factors influencing the adoption of no-till conservation agriculture by small-scale farmers in Zashuke, KwaZulu-Natal Province. Sustainability, 10(2), 555.

Ovharhe, O. J. (2019). Determinants of the socioeconomic profile of Fadama III Project beneficiaries in three States of Niger Delta Area of Nigeria. International Journal of Agricultural Science, 4, 29-34.

Patel, S., Kokni, R., Dhonde, M. B. & Kamble, A. B. (2016). Integrated weed management for improved yield of soybean. Indian Journal of Weed Science, 48(1), 83-85.

Pickering, J. (2015). Top-down proposals for sharing the global climate policy effort fairly: lost in translation in a bottom-up world? Centre for Deliberative Democracy and Global Governance Working Paper Series Working Paper No. 6.

Rabbi, F., Ahamad, R., Ali, S., Chandio, A. A., Ahmad, W., Ilyas, A. & Din, I. U. (2019). Determinants of commercialization and its impact on the welfare of smallholder rice farmers by using Heckman’s two-stage approach. Journal of the Saudi Society of Agricultural Sciences, 18(2), 224-233.

Rahman, M.A., Thant, A.A., Win, M., Tun, M.S., Moet, P.M., Thu, A.M., Win, K.T., Myint, T., Myint, O., Tuntun, Y., Labios, R. V., Casimero, M. C., Gregorio, G.B., Johnson, D.E., Singleton, G. R. & Singh, R.K (2015). Participatory varietal selection (PVS): A “bottom-up” breeding approach helps rice farmers in the Ayeyarwady Delta, Myanmar. SABRAO Journal of Breeding & Genetics 47(3): 299-314.

Ronner, E., Franke, A. C., Vanlauwe, B., Dianda, M., Edeh, E., Ukem, … & Giller, K. E. (2016). Understanding variability in soybean yield and response to P-fertilizer and rhizobium inoculants on farmers’ fields in northern Nigeria. Field Crops Research, 186, 133–145. doi.org/10.1016/j.fcr.2015.10.023

Siri, B. N., Tchouamo, I. R. & Nchanji, E. B. (2020). Gender analysis of farmers’ perception of improved haricot bean (Phaseolus vulgaris L.) varieties in the West Region of Cameroon. International Journal of Agricultural Policy and Research, 8 (4):107-115 ISSN: 2350-1561.

Siyum, N., Giziew, A. & Abebe, A. (2022). Factors influencing adoption of improved bread wheat technologies in Ethiopia: empirical evidence from Meket district. Heliyon, 8(2), e08876.

Snapp, S. S., Cox, C. M. & Peter, B. G. (2019). Multipurpose legumes for smallholders in sub-Saharan Africa: Identification of promising ‘scale out’ options. Global Food Security, 23:22-32.

Sulaiman, S. M., Yahaya, A., Muhammad, M. A. & Muhammad, A. D. (2021). Evaluating Fadama III Development Project in Kano State, Nigeria: Using Difference in Difference Estimation with Propensity Score Matching Approach. International Journal of Economics, Management and Accounting, 499-517.

Sunny, F. A., Fu, L., Rahman, M. S., Karimanzira, T. T. P. & Zuhui, H. (2022). What influences Bangladeshi Boro rice farmers’ adoption decisions of recommended fertilizer doses: A case study on Dinajpur district. PloS one, 17(6), e0269611.

Sutar, A. U., Vaidya, P. H., Deshmukh, A. V., Lilhare, M. A. & Landge, R. B. (2019). Effect of foliar application of vermiwash, compost tea and panchagavya on yield and quality of soybean in inceptisol. Journal of Pharmacognosy and Phytochemistry, 8(5), 1228-1230.

Tesfay, M. G. (2020). Does fertilizer adoption enhance smallholders’ commercialization? An endogenous switching regression model from northern Ethiopia. Agriculture & Food Security, 9(1), 1-18.

Uematsu, H. & Mishra, A. K. (2010). Net effect of education on technology adoption by US farmers (No. 1370-2016-108720).

Vimefall, E. (2015). Income diversification among female-headed farming households (No. 11/2015). Working Paper.

Wandji, D.N., Pouomogne, V., Binam, J.N. & Nouaga, R.Y (2012). Farmer’s perception and adoption of new aquaculture technologies in the Western Highlands of Cameroon. Tropicultura 30(3):180-184.

Yokamo, S. (2020). Adoption of improved agricultural technologies in developing countries: Literature review. Int. J. Food Sci. Agric, 4, 25-36.

Downloads

Published

2022-12-31