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.
The presentation was given at the ILRI Policy, Trade and Value Chains Program (May–November 2014) Seminar, ILRI Nairobi, 21 November 2014. It included the introduction of Dairy Development Forum, background and purpose, literature review, methodology, results and discussions, and conclusions.
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
Linking farmers to markets is widely viewed as a milestone towards promoting economic growth and poverty reduction. However, market and institutional imperfections along the supply chain thwart perfect vertical and spatial price transmission and prevent farmers and market actors from getting access to information, identifying business opportunities and allocating their resources efficiently. This acts as a barrier to market-led rural development and poverty reduction.
Tanzania has tremendous potential to support a thriving agribusiness sector. Agriculture is diverse and extensive, employing more than 80 percent of the population, and contributing about 28 percent of Gross Domestic Product, or GDP and 30 percent of export earnings. A wide range of agricultural commodities are produced in Tanzania, including fiber (sisal, cotton), beverages (coffee, tea), sugar, grains (a diverse range of cereals and legumes), horticulture (temperate and tropical fruits, vegetables and flowers) and edible oils.
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 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.