Financial Determinants of Adoption of Agricultural Technologies in Irish Potato Production in Ol Kalou Sub County, Kenya: Application of Multinomial Logistic Regression
Kihoro David Mwangi, Gathungu Geofrey Kingori, Mwirigi Rael Nkatha, Wairimu Vicky Nyambura
Asian Journal of Research in Crop Science · pp. 161–175 · Published 28 Oct 2024
10.9734/ajrcs/2024/v9i4308Abstract
Irish potato is a significant source of food and income for many households worldwide. The demand for the crop has steadily increased around the globe. Kenyan Irish potato farmers have the potential to produce about 30 tonnes per Ha. However, small-scale Irish farmers in the country realize low output ranging from 4-8 tonnes per Ha due to limited uptake of agricultural technologies. This study aimed to analyze the financial factors influencing the uptake of agricultural technologies in Irish potato production in Ol Kalou Sub County. The agricultural technologies under investigation were chemical fertilizer, certified seeds, fungicides, and farm machinery. Production and innovation diffusion theories guided the study. Descriptive cross-sectional research design was used to obtain data from a study population of 21,942 smallholder Irish potato farmers in Ol Kalou Sub County. A multiple-stage sampling technique was employed to give a sample size of 385 respondents small scale Irish potato farmers, where data was collected through a semi-structured questionnaire. Data collected was analyzed using multinomial logistic regression through SPSS version 28 and STATA version 17. The model indicated that off-farm income, access to credit, and production risk had a positive and significant influence on adopting agricultural technologies. Conversely, production cost had a negative and significant influence on the adoption of agricultural technologies, while the availability of subsidies had no significant influence. The Marginal effect analysis showed that the availability of off-farm income increased adoption by 22.00%, the increase in credit increased adoption by 2.00%, the availability of mitigation measures of production risk increased adoption by 19.00%, while the increase in production cost decreased adoption by 7.00%. The study concluded that off-farm income, credit facilities, production risk and cost of production influence the adoption of agricultural technologies. The study recommended that the government should develop policy regulations such as diversification of income, grants that reduce production costs, credit incentives, and crop insurance.
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