The Tanga Dairy Platform, created in 2008, is an informal forum of different stakeholders involved in the dairy industry of Tanzania’s Northeastern Tanga region. The platform’s objective is to exchange knowledge and develop joint actions to common problems. Six years on, it is a sustainable example of a commodity association addressing the joint problems of the region’s dairy industry.
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 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
Africa RISING (AR) is a research-for-development program that aims to create opportunities for smallholder farmers to move out of hunger and poverty through sustainable intensification of their farming systems.
The report introduces 30 young innovators, 21 featured with full stories, and nine other "innovators to watch". They come from countries including Barbados, Botswana, Cameroon, Côte d'Ivoire, Kenya, Nigeria, Uganda, Jamaica, Senegal, Tanzania. The publication presents a multidimensional picture of the emerging field of ICT entrepreneurship in agriculture in developing countries. It describes challenges but also successes already achieved. It contains advice for aspiring agtech entrepreneurs as well as recommendations from youth on how to support their ventures.
This report describes the activities carried out by the Africa RISING-NAFAKA parnership. The Africa RISING-NAFAKA partnership project focuses on the delivery and scaling of promising interventions that enhance agricultural productivity in Tanzania. The key interventions are the promotion of climate-smart agricultural innovations, dissemination of best-bet crop management packages, rehabilitation and protection of natural resources, and reduction of food waste and spoilage.
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.