Determinants of Technology Adoption and Intensity of Adoption among Rice Farming Households in Ogun State, Nigeria.
DOI:
https://doi.org/10.47672/ejt.1187Keywords:
Adoption, Rice, Farming, Technology, TobitAbstract
Purpose: Production and productivity of the agricultural sector in SSA is low due to low technological adoption and techniques among others. One of the major goals of Nigerian agriculture development programs and policies is transition from low productivity subsistence agriculture to a high productivity agro-industrial economy through improved technology adoption.
Methodology: A multi-stage sampling technique was used in this study to select 158 rice farming households The first stage involved the purposive selection of two Agricultural Development programme zones (Ikenne and Abeokuta zones) in the state. The second stage was purposive selection of two blocks per zone based on the concentration of rice farmers. Six farming cells were randomly selected from each block making a total of twenty-four (24) farming community, seven rice farmers were randomly selected from each farming cell giving a sample size of 168 rice farmers. A set of structured questionnaires were used to collect data. Out of the 168-questionnaire administered 158 of it were gotten and used for the study. The data were analysed using descriptive statistics, adoption index, tobit regression model.
Findings: Technologies adoption was high among the young farmers than the older farmers. The household size was also a determinant factor of technology adoption. As the household increases in size, there is high probability that all the production technologies will be adopted. Access to credit facility was found to be positive and significant in all the production technologies available to the rice farmers.
Recommendations: It was recommended that the young people should be encouraged to modern technologies available for rice production, the farmers should be educated on modern technologies in the production of rice. Credit facilities should be made available for the farm household.
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Abraham B, Araya H, Berhe T, Edwards S, Gujja B, Khadka R, Sen D, Koma Y, Sharif A, Styger E, Uphoff N, Verma A. (2014) The system of crop intensification: Reports from the field on improving agricultural production, food security, and resilience to climate change for multiple crops. Addis Ababa, Ethiopia. Available at http://www.agriculture and food security.com/content/3/1/4.
Adebayo, O. O. (2012): Effects of family size on household food security in Osun State, Nigeria. Asian journal of agriculture and rural development,. 2(2): 136-14.
AfDB. African Development Group. Tracking Africa‟s Progress in Figures. 2014. Analysis study. Addis Ababa, Ethiopia. 2012.
Augustine, L. & Mulugeta M. (2005): Modeling agricultural technology adoption using the software STATA, training manual presented at a training course organized by CIMMYT-ALP Harare Zimbabwe.
Babalola, DA, Makinde Y O and Afodu, J O. (2010): ‘Nutrition Transition and Indicators of Hypertension among Farming Households in Nigeria: Evidence From Ikenne Local Government Area of Ogun State’. Canadian Journal of Pure and Applied Science. 5(1), 1349-1353.
Barla, M. (2013): The impact of new agricultural technology on tribal farming: a study of Ranchi District of Jharkhand State. Journal of Economic & Social Development. 9; 121-131.
Beke T.E. (2011): Institutional Constraints and Adoption of Improved Rice Varieties: Econometrics Evidence from Ivory Coast. Rev. Agric. Environ. Stud. 92(2): 117-141
Berihun KH, Bihon KA, Kibrom AW. (2014): Adoption and impact of agricultural technologies on farm income: evidence from Southern Tigary, Northern Ethiopia.Int. J. Food Agric. Econ. 2(4):91-106
Faturoti B.O., Agwu A. E., Igbokwe E. M. and Tenkouano A. (2008): ‘International Institute of Tropical Agriculture plantain and banana programme: An insight into the contributions of farmer-to- farmer extension paradigm.’ African Journal of Biotechnology. 7 (13), 2137-2146.
Gashaw T, Alan B, Nicholas M, Tanguy B. (2014): The impact of the use of new technologies on farmers wheat yield in Ethiopia. International Food Policy Research Institute (IFPRI).. Washington, DC
Jensen K., Clark C.D., Ellis P., English B., Menard J., Walsh M., de la Torre U.D. (2007): Farmer Willingness to Grow Switch Grass for Energy Production. Bioma. Bioener. 31 (11-12): 773-781
Lulit M, Ermias E, Zelalem H. (2012): Public investment in irrigation and training for an agriculture-led development: a CGE approach for Ethiopia. Addis Ababa, Ethiopia. .
Meena, G. L. & Punjabi N. K. (2012). Farmer’s perception towards agriculture technology in tribal region of Rajasthan. Rajasthan Journal of Extension Education, 2012; 20: 92-96.
National Population Commission. (2006): National Census Report, National Population Commission, Abuja, Nigeria.
Olumba, C.C. and Rahji, M. A.Y. (2014): ‘An Analysis of the Determinants of the Adoption of Improved Plantain Technologies in Anambra State, Nigeria.’ Journal of Agriculture and Sustainability. (2): 232-245.
Oni, O.A., K. K. Salman and B.O. Idowu. (2011). “Social capital dimension and food security of farming households in Ogun State, Nigeria.” Journal of American Science, 7(8): 776-783.
Pankomera P, Houssou N, Zeller M. (2009): Household food security in Malawi: measurements, determinants and policy review. Conference on International Research on Food Security, Natural Resource Management and Rural Development, University of Hamburg, Tropentag, Hamburg.
Paudel P. and Matsuoka A. (2008): Factors Influencing Adoption of Improved Maize Varieties in Nepal: A case study of Chitwan District. Aust. J. Bas. Appl. Sci. 2(4): 823-834.
Ramo A.K., Jarvinen E., Latvala T., Toivonen R. and Silvennoienen H. (2009): Interest in Energy Wood and Energy Crop Production Among Finnish Non-Industrial Private Forest Owners. Bioma. Bioener. 33(9): 1251-1257
Shaikh, F. M. (2007): Determinants of Household Food Security and Consumption Pattern in Rural Sindh: Non-Separable Agriculture Household Model. IUB Journal of Social Sciences and Humanities. 5(2): 18-39.
Simtowe, F., and Zeller, M. (2006): The Impact of Access to Credit on the Adoption of hybrid maize in Malawi: An Empirical test of an Agricultural Household Model under credit market failure.
Sultana Anila and Adiqa Kiani. (2011): Determinants of food security at household level in Pakistan. African Journal of Business Management. 5(34): 12972- 12979,
Thomas Bilaliib Udimal Zhuang Jincai, Owusu Samuel Mensah and Ayamba Emmanuel Caesar. (2017): ‘Factors Influencing the Agricultural Technology Adoption: The Case of Improved Rice Varieties (Nerica) in the Northern Region, Ghana.’ Journal Economics and Sustainable Development. 2017; 8(8).
Tsegaye, M. (2012): Vulnerability, Land, Livelihoods and Migration Nexus in Rural Ethiopia: A Case Study in South Gondar Zone of Amhara Regional State. International institute of social studies, Hague, Netherlands.
Uaiene, R. N., Arndt, C., and Masters, W. (2009): Determinants of agricultural technology adoption in Mozambique. Discussion papers, 67.
Viatte G. (2001): Adopting technologies for sustainable farming systems: an OECD perspective. In Proceedings of Adoption of Technologies for Sustainable Farming Systems Wageningen Workshop. 21p. OECD Publications, Paris Cedex.
World Bank Group (2014). Ethiopia poverty assessment. Document of the WB for official use only.
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Copyright (c) 2022 Afodu Osagie John, Akinboye Olufunso Emmanuel, Akintunde Adeyinka Oye, Ndubuisi-Ogbonna Lois Chidinma, Shobo Bolatito Adenike, Oyewumi Samson Oyewole
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