Research Article of American Journal of Agricultural Research
Assessment of socio-economic factors affecting the utilization of manual screw press for gari production in Kwara state, Nigeria
Adegbola Adetayo Jacob1, Wegh Francis Shagbaor2, Ikwuba Agnes Agbanugo3, Nwafor Solomon Chimela4
1Extension Department, Nigerian Stored Product Research Institute, Nigeria
2 Department of Sociology, Benue State University, Nigeria
3 Department of Sociology, Benue State University, Nigeria
4 Extension Department, National Root Crops Research Institute, Nigeria
This study investigated socio-economic determinants of utilization of manual screw press for cassava mash dehydration for gari production in four local government areas across the ADP zones in Kwara state, Nigeria. Using random sampling technique and a semi-structured questionnaire as research instrument, data for the study were collected from a sample of three hundred and eighty four (384) gari processors who use the screw press in the state. Multiple regression analysis show that a correlation (R=0.678) exist between utilization of the screw press and the independent variables which include age, household size, level of education, years of processing experience, extension visits, and income from gari processing. R2 value of 0.460 indicates that about 46% of the variation in utilization was explained by socio-economic variables included in the regression model. Three variables significantly influenced the decision of the respondents to utilize the manual screw press: age, level of experience, and income; the most important predicator being income with a Beta value of 0.699. Conclusively, it was recommended among others that research, extension, and policy makers consider the significant determinants identified in the study seriously if increased utilization is to be achieved by gari processors and others similar to them in the study area and the region.
Keywords: Improved technology, Manual screw press, Socio-economic factors, Utilization,
How to cite this article:
Adegbola Adetayo Jacob, Wegh Francis Shagbaor, Ikwuba Agnes Agbanugo, Nwafor Solomon Chimela. Assessment of socio-economic factors affecting the utilization of manual screw press for gari production in Kwara state, Nigeria. American Journal of Agricultural Research, 2019,4:53. DOI: 10.28933/ajar-2019-01-2903
1. Adam, H., & Boateng, S. (2012) Adoption of Innovation by Small Ruminant Farmers in Northern Ghana: the Case of Tolon-Kunbunga Districts. Journal of Biology, Agriculture and Healthcare 2(11):10-20
2. Ainembabazi, J.H., & Mugisha, J. (2014) The Role of Farming Experience on the Adoption of Agricultural Technologies: Evidence from Smallholder Farmers in Uganda. The Journal of Development Studies, 50(5): 666-679
3. Anaglo, J.W., Asare, C.J., Manteaw, S.A., & Boateng, S.D. (2017) Influence of Improved Technology Adoption on Livelihoods of Small Ruminant Farmers in Ghana. American-Eurasia Journal of Agriculture and Environmental Sciences, 17(1): 78-84
4. Bonabana – Wabbi, J (2002). Assessing Factors Affecting Adoption of Agricultural Technologies. The Case of Integrated Pest Management (IPM) in Kumi District, Eastern Uganda. Unpublished Msc Thesis Virgina Polytechnic Institute and State University USA.
5. Chilot, Y., Shampiro, B.I & Demeke, M. (1996). “Factors Influencing Adoption of New Wheat Technologies in Wolmera and Addis Alem Areas of Ethiopia”. Ethiopian Journal of Agricultural Economics, (1): 63-83
6. Chinaka C. C, Ogbuokiri L. C and Chinaka E. C. (2007). Adoption of Improved Agricultural Technologies by Farmers in Aba Agricultural zone of Abia State. Proceedings of the 41st Conference Held at Institute for Agricultural Research, Samaru, ABU Zaria 22 – 26 October, Pp. 531-534.
7. Doward, A., Kydd, J., Morrison, J., & Urey, L. (2003) A Policy Agenda for Pro-poor Agriculture Growth. World Development, 32(1): 73-89
8. Eicher, C. (1995) ‘Zimbabwe’s Maize-based Green Revolution: Preconditions for Replication’ World Development 23 (5): 805-818.
9. Federal Government of Nigeria (2007) Federal Republic of Nigeria Official Gazette, 94(24): 190-191. Printed and Published by The Federal Government Printer, Lagos, Nigeria.
10. Kinuthia, B.K., & Mbaya, E. (2017) The Impact of Agriculture Technology Adoption on Farmers’ Welfare in Uganda and Tanzania. Partnership for Economic Policy, number 163, February 2017
11. Lanjouw, P., & Stern, N. (1998) Economic Development in Palanpur over Five Decades. Oxford, UK: Clarendon Press.
12. Mittal, S., Gandhi, G., & Tripathi, G. (2010) Socio Economic Impact of Mobile Phones on Indian Agriculture. ICRIER Working Paper 246. New Delhi: International Council for Research on International Economic Relations.
13. Mulaudzi, S.V., & Oyeleke, S.A. (2015) Smallholder Farmers Adoption Intensity of Genetically Modified maize Varieties in Thulamela Municipallity, Limpopo Province, South Africa. Environmental Economics, 6(110: 104-112
14. National Bureau of Statistics (2012) Annual Abstract of statistics. Federal republic of Nigeria
15. Olaniyan, O.F. (1998). Adoption of Improved Cassava Varieties by Women Farmers in Rural Areas of Oke-Ogun, Oyo State, Unpublished M.Sc. Thesis, Department of Agricultural Extension, Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria.
16. Omonona, B., Oni, O., & Uwagboe, O. (2005) Adoption of Improved Cassava Varieties and its Impact on Rural Farming Households in Edo State, Nigeria. Journal of Agriculture and Food Information 7(1): 40-45
17. Oyebanji, J.O. (2000) Kwara State. In A.B. Mamman, J.O. Oyebanji, S.W. Petters (Edt), Nigeria: A People United, A Future Assured, Volume 2, Survey of States. Federal Ministry of Information, Abuja, 2000.
18. Ravallion, M., & Chen, S. (2004) “How have the World’s Poorest Fared since the early 1980s?” World Bank research Observer, 19(2):141-170
19. Sasore, G.M. (2005) “Nigerian’s Export Trade of Agricultural Commodities; Quality Control and Standards”. A Paper presented at Nigeria National Crop Outlook Conference held at Durbar Hotel Kano, 26th – 27th May, 2005 pp26.
20. Smith, C. (2013) Determining sample size: How to Ensure you get the Correct Sample Size. qualtrics.com/experience-management/research/determine-sample-size
21. Solomon, A. (2010) Estimating Welfare Effect of Modern Agricultural Technologies: A Micro-Perspective from Tanzania and Ethiopia. International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Nairobi
22. Suleman, A. (2012) Factors Influencing Adoption of Improved Cassava Processing Technologies by Women Processors in Akoko-Edo Local Government Area, Edo state, Nigeria. Unpublished thesis, Ahmadu Bello Universitity, Zaria, in partial fulfilment of the requirements for the award of Msc degree in Agricultural Extension and Rural sociology.
23. Tijjani, A.R. (2010). Factors Influencing Adoption of Recommended Cowpea Production Practices in Rimi L.G.A. Katsina state. M.Sc. Agric. Ext. Thesis, ABU, Zaria.
24. Unamma, R.P.A. (2004). Agricultural Technology Generation and Transfer Strategies for Food Security. Proceedings of the 6th Annual Zonal Research and Extension Farmers Input Linkage Systems (REFILS) Workshop South and South/South Zone of Nigeria 12 – 13 November.
25. Vilane, B.R.T., Shongwe,M.I., Motsa, N.M., & Shongwe, V.D. (2012) Adoption of Postharvest Technologies Used by Smallholder Farmers in Swaziland. African Journal of Agricultural Research, 7(35): 4983-4995
26. Wasula, S. L., (2000). Influence of Socio-economic Factors on Adoption of Agro-forestry Related Technology. he Case of Njoro and Rongai Districts, Kenya. (Unpublished M. Sc. Thesis). Njoro, Kenya: Egerton University.
27. Zhang, X., Fan, S., & Cai X. (2002): The Path of Technology Diffusion: Which Neighbours to Learn From? Contemporary Economic Policy, 20: 470–479
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