During May 2010 the International Centre for Tropical Agriculture (CIAT) hosted two events related to knowledge management (KM): The Knowledge Share Fair for Latin America and the Caribbean, funded by the Food and Agriculture Organization of the United Nations (FAO), and a regional meeting of the Knowledge Management for Development (KM4Dev) community. The Fair was attended by 200 professionals from more than 70 organizations and 18 countries and showcased more than 40 experiences related to KM in agriculture, development and food security.
The purpose of this methodological guide is to outline how to conduct an empirical assessment of the current landscape of women’s small-scale fishery (SSF) organizations. Applying this methodology will enhance understanding of where women are organized in SSFs (both geographically and within the value chain); what their present organizational characteristics and capacities are; and their primary needs.
This guide is the second in a series of documents designed to support agencies implementing participatory agroenterprise development program operating within defined geographical areas.
This note is a preview on the agricultural innovation systems (AIS) assessment methdology which is being tested in the nine countries of the European Union-funded TAP-AIS DeSIRA project. It presents the rationale, the steps, ethe expected outputs and outcomes.
ICT-driven digital tools to support smallholder farmers are arguably inevitable for agricultural development, and they are gradually evolving with promising outlook. Yet, the development and delivery of these tools to target users are often fraught with non-trivial, and sometimes unanticipated, contextual realities that can make or mar their adoption and sustainability. This article unfolds the experiential learnings from a digital innovation project focusing on surveillance and control of a major banana disease in East Africa which is being piloted in Rwanda.
The Colombian Ministry of Agriculture Colombia, an international research center and a national farmers’ organization developed a data-driven agricultural program that: (i) compiles information from multiple sources; (ii) interprets that data; and (iii) presents the knowledge to farmers through the local advisory services. Data was collected from multiple sources, including small-scale farmers. Machine learning algorithms combined with expert opinion defined how variation in weather, soils and management practices interact and affect maize yield of small-scale farmers.
The Farmer Field School (FFS) approach has been very successful and witnessed a strong expansion in many areas beyond crop production. Notwithstanding this success, the adoption of FFS in national extension often remains problematic and FFS activities have often been implemented in the margin of national institutions with strong reliance on donor funding. The creation of an enabling environment for institutional support is essential for expanding the effort, improving quality, and strengthening impact and continuity of the FFSs.
WhatsApp sends real-time messages and is one of the world’s most popular communication applications in the 21st century. The present study highlights and examines the domestication of WhatsApp among farmers. An exhaustive whatsapp user list was prepared from each village and 3 farmers were selected with the help of systematic sampling technique. Thus, 90 farmers from the 3 blocks of the district using whatsapp were purposively selected and grouped for sending the messages of agricultural aspects. The study was conducted at Krishi Vigyan Kendra, Neemuch during 2016-17.
This research aims to add to the literature new insights about the interaction processes, which are implemented in different interactive extension approaches, by analysing how farmers attending different extension events shape a network of indirect interactions
This report introduces the reader to the concept of agricultural innovation systems (AIS) and the TAP-AIS project being implemented by FAO in nine countries, including Lao People's Democratic Republic (Lao PDR). The results of the AIS assessment for Lao PDR are presented, highlighting key barriers and opportunities for agricultural innovation in the country.