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.
This presentations describes the Perspectives on innovation adoption in Poutry systems. Was presented at he Technology for African Agricultural Transformation (TAAT) poultry value chain inception meeting, ILRI, Addis Ababa, 21 June 2018. Nairobi, Kenya. It is divided in: Diverse Innovations in Livestock Value Chains, Innovation adoption Theory, Approaches to adoption and Conclusions
This study investigated how value chain governance influences farmer participation in vegetable markets and food security in Kenya. This study employed exploratory case study design to provide chain architecture, isolate primary actors, their roles, relations, constraints and opportunities for upgrading by smallholders.
Within the context of the European-funded JOLISAA FP7 project (JOint Learning in Innovation Systems in African Agriculture), several agricultural innovation experiences focused on smallholders were assessed in Benin, Kenya and South Africa. Fifty-six cases were characterised through review of grey literature and interviews with resource persons according to a common analytical framework inspired by the innovation systems perspective. Of these, 13 were assessed in greater depth through semistructured interviews, focus-group discussions and multistakeholder workshops.
The study analyzes the current state of Agricultural Technical and Vocational Education and Training (ATVET) in Africa and presents its challenges and opportunities. A review of the ATVET in selected Sub-Saharan Africa countries shows that there are far too few training opportunities for young people and that often, the training offered does not match the needs of the private sector and of local administrations. ATVET trainings focus primarily on production skills and on producers themselves with
This report is a summary of the several activities pursued within the Program of Accompanying Research for Agricultural Innovation (PARI) to contribute to sustainable agricultural growth, food and nutrition security in Africa and India. The Institute of Agricultural Engineering, Tropics and Subtropics worked in the identification of technological innovations and further intervention in the dairy value chain, offering a potential solution for cooling milk from the earliest stage of milk production and
This study analyzed the determinants of ICT usage in agricultural value chains among rural youth in Busia County, Kenya. A total of 213 young farmers were randomly selected and interviewed using semi-structured questionnaires. Descriptive statistics and Poisson regression model were applied in data analysis. Findings showed youth participation using ICTs was concentrated at the marketing level of the agricultural chain activities.
This paper comparatively analyzes the structure of agricultural policy development networks that connect organizations working on agricultural development, climate change and food security in fourteen smallholder farming communities across East Africa, West Africa and South Asia.
The objective of the study was to identify a viable trade-off between low data requirements and useful household-specific prioritizations of advisory messages. At three sites in Ethiopia, Kenya, and Tanzania independently, we collected experimental preference rankings from smallholder farmers for receiving information about different agricultural and livelihood practices. At each site, was identified socio-economic household variables that improved model-based predictions of individual farmers’ information preferences.