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. This knowledge was then used to provide guidelines on management practices likely to produce high, stable yields. The effectiveness of the practices was confirmed in on-farm trials. The principles established can be applied to rainfed crops produced by small-scale farmers to better manage their crops with less risk of failure.
African agriculture is currently at a crossroads, at which persistent food shortages are compounded by threats from climate change. But, as this book argues, Africa can feed itself in a generation and help contribute to global food security. To achieve...
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...
Providing smallholder farmers with support through conventional government extension approaches is challenging as the number of extension agents is decreasing. At the same time, new information and communication technologies (ICTs), such as short message services (SMS) sent via mobile phones,...
Cette publication offre de nombreux exemples concrets détaillant différentes manières de réengager les jeunes dans le secteur agricole. Elle montre à quel point des programmes éducationnels sur mesure peuvent offrir aux jeunes les compétences et la perspicacité nécessaires pour se...
This paper examines how the different institutional innovations arising from various permutations of linkages and interactions of ARD organizations (national, international advanced agricultural research centres and universities) influenced the different outcomes in addressing identified ARD problems. A multi-institutional, multi-disciplinary phased...