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

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  • Additional Information
    • Publication Information:
      Elsevier
    • Publication Date:
      2019
    • Collection:
      CGIAR CGSpace (Consultative Group on International Agricultural Research)
    • Abstract:
      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.
    • File Description:
      p. 256-266
    • ISSN:
      2211-9124
    • Relation:
      Jiménez, Daniel; Delerce, Sylvain; Dorado, Hugo; Cock, James; Muñoz, Luis Armando; Agamez, Alejandro & Jarvis, Andy (2019). A scalable scheme to implement data-driven agriculture for small-scale farmers. Global Food Security. 23: 256-266; https://hdl.handle.net/10568/103626; https://doi.org/10.1016/j.gfs.2019.08.004; PII-LAM_ASACDIGITAL
    • Accession Number:
      10.1016/j.gfs.2019.08.004
    • Online Access:
      https://doi.org/10.1016/j.gfs.2019.08.004
      https://hdl.handle.net/10568/103626
    • Rights:
      CC-BY-NC-ND-4.0 ; Open Access
    • Accession Number:
      edsbas.DE442ECB