This report aims to o estimate the current use of machinery in rice and bananas value chains; To establish determinants of mechanization in rice and bananas along the entire value chains; and estimate the effects of the determinants on mechanization levels. This study therefore seeks to identify factors that influence
mechanization levels for rice and bananas value chains. The findings from this study will help provide technical and policy recommendations for the improvement of not only the rice and banana value chains but the entire agriculture sector
The study was conducted in Kirinyaga County on rice and bananas and in Kisumu County on rice. Was used qualitative and quantitative methods and interviewed 247 farmers comprising 182 rice and 60 banana farmers respectively. Ten key informant interviews were conducted in Ahero and nine in Mwea Rice Schemes and the surrounding areas. One focus group discussion was held with Mwea Jua Kali/Valley bottom farmers. The data were analysed using descriptive statistics, frequency analysis and cross tabulations.
Many developing countries are experiencing a rapid expansion of supermarkets. New supermarket procurement systems could affect farming patterns and wider rural development. While previous studies have analyzed farm productivity and income effects, possible employment effects have received much less attention. Special supermarket requirements may entail intensified farm production and post-harvest handling, thus potentially increasing demand for hired labor. This could also have important gender implications, because female and male workers are often hired for distinct farm operations.
Supermarkets and high-value exports are currently gaining ground in the agri-food systems of many developing countries. While recent research has analyzed income effects in the small farm sector, impacts on farming efficiency have hardly been studied. Using a survey of Kenyan vegetable growers and a stochastic frontier approach, we show that participation in supermarket channels increases mean technical efficiency by 19%. This gain is bigger at lower levels of efficiency, suggesting the potential for positive income distribution effects.