This paper has been prepared under the guidelines provided by the TAP Secretariat at the FAO, as a contribution to the G20 initiative TAP, which includes near 40 partners and is facilitated by FAO. Its purpose is to provide a Regional synthesis report on capacity needs assessment for agricultural innovation, with capacity gaps identified and analyzed, including recommendations to strengthen agricultural innovation systems (AIS) and draft policy recommendations to address the capacity gaps.
TAP and its partners carried out regional surveys in Asia, Africa and Central America to assess priorities, capacities and needs in national agricultural innovation systems. This document provides a Regional synthesis report on capacity needs assessment for agricultural innovation in Africa. FARA was selected as Recipient Organization by FAO to facilitate TAP implementation in Africa. This is mainly due to its position as the umbrella organization bringing together and forming coalitions of major regional stakeholders in agricultural research and development.
Traditional approaches to innovation systems policymaking and governance often focus exclusively on the central provision of services, regulations, fiscal measures, and subsidies.
This book discusses innovation problems and opportunities for family farming in the different regions of the American continent, as well as the role of hemispheric, regional and national agrifood research systems. Likewise, it provides a description of the main innovation actions and projects promoted by IICA, and the main success cases over recent years.
The gender strategy of the CGIAR Research Program on Livestock and Fish highlights the key role of gender analysis in livestock value chain research and guides the integration and implementation of related research activities. The Program’s gender team has produced a gender capacity assessment tool to evaluate existing skills and gaps in partners’ gender capacities and identify measures to address them. In 2015, the tool was implemented in four L&F value chain countries (Ethiopia, Nicaragua, Tanzania and Uganda).
The capacities of twenty-four Livestock and Fish CGIAR Research Programme partners in four countries (Ethiopia, Uganda, Tanzania and Nicaragua), representing two partner types (development and research), have been assessed during the period December 2014 – September 2015. This report aims to summarize these four assessments, analyze the differences and similarities, and present recommendations for the design of capacity development interventions.
This presentation describes the process of the capacity needs assesment carried out by a consortium of organizations in Ethiopia, Nicaragua, Tanzania, Tunisia and Uganda. Starts describing the the methodology used for the assesment, then present the key finds and in the end gives some recommendations
This article presents a multi-stakeholder framework for intervening in root, tuber, and banana seed systems and in other VPCs. These crops are reproduced not with true seed but with vegetative planting material (e.g., roots,tubers, vines, stems, and suckers), called “seed” in this article. Seed systems for VPCs need to be designed differently than those for true seed, and coordination among stakeholders in seed systems is crucial
This publication contains twelve modules which cover a selection of major reform measures in agricultural extension being promulgated and implemented internationally, such as linking farmers to markets, making advisory services more demand-driven, promoting pluralistic advisory systems, and enhancing the role of advisory services within agricultural innovation systems.
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.