This paper presents a case study of the Honey Bee Network’s decentralized model for collecting, verifying and disseminating grassroots innovations and provides a roadmap for its replication in Africa. The Honey Bee Network brings together governmental and non‐governmental institutions, members of academia, scholars and a large number of volunteers.

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.

In Yatta sub-County, a semi-arid land, there is scanty information on the causes and effects of climate change, as well as agricultural adaptation strategies. This scanty information assessment of climate related risks, and decision making about appropriate adaptation measures. A survey was conducted in two wards of Yatta, Kenya, to identify opportunities for building farmer capacity in dealing with climate variability.

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

The objective of this paper is to show how Value Chain Analysis for Development (VCA4D) applied sustainable development concept for value chain analysis to establish a manageable set of criteria allowing to provide quantitative information, which is desperately lacking in many situations in developing economies, usable by decision makers and in line with policymakers concerns and strategies (the “international development agenda”).

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.