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A scalable scheme to implement data-driven agriculture for small-scale farmers


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.

Global Food Security 23(2019):256-266

Document author: Daniel Jiménez, Sylvain Delerce, Hugo Dorado, James Cock, Luis Armando Muñoz, Alejandro Agamez, Andy Jarvis
IISBN/ISSN: 2211-9124
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