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...

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Autores principales: Jiménez, Daniel, Delerce, Sylvain Jean, Dorado, Hugo Andres, Cock, James H., Muñoz, Luis Armando, Agamez, Alejandro, Jarvis, Andy
Formato: Journal Article
Lenguaje:Inglés
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://hdl.handle.net/10568/103626
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author Jiménez, Daniel
Delerce, Sylvain Jean
Dorado, Hugo Andres
Cock, James H.
Muñoz, Luis Armando
Agamez, Alejandro
Jarvis, Andy
author_browse Agamez, Alejandro
Cock, James H.
Delerce, Sylvain Jean
Dorado, Hugo Andres
Jarvis, Andy
Jiménez, Daniel
Muñoz, Luis Armando
author_facet Jiménez, Daniel
Delerce, Sylvain Jean
Dorado, Hugo Andres
Cock, James H.
Muñoz, Luis Armando
Agamez, Alejandro
Jarvis, Andy
author_sort Jiménez, Daniel
collection Repository of Agricultural Research Outputs (CGSpace)
description 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.
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publishDate 2019
publishDateRange 2019
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spelling CGSpace1036262025-03-13T09:44:11Z A scalable scheme to implement data-driven agriculture for small-scale farmers Jiménez, Daniel Delerce, Sylvain Jean Dorado, Hugo Andres Cock, James H. Muñoz, Luis Armando Agamez, Alejandro Jarvis, Andy agriculture data machine learning aprendizaje electrónico colombia small scale farming pequeñas explotaciones 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. 2019-12 2019-09-11T19:26:03Z 2019-09-11T19:26:03Z Journal Article https://hdl.handle.net/10568/103626 en Open Access Elsevier 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
spellingShingle agriculture
data
machine learning
aprendizaje electrónico
colombia
small scale farming
pequeñas explotaciones
Jiménez, Daniel
Delerce, Sylvain Jean
Dorado, Hugo Andres
Cock, James H.
Muñoz, Luis Armando
Agamez, Alejandro
Jarvis, Andy
A scalable scheme to implement data-driven agriculture for small-scale farmers
title A scalable scheme to implement data-driven agriculture for small-scale farmers
title_full A scalable scheme to implement data-driven agriculture for small-scale farmers
title_fullStr A scalable scheme to implement data-driven agriculture for small-scale farmers
title_full_unstemmed A scalable scheme to implement data-driven agriculture for small-scale farmers
title_short A scalable scheme to implement data-driven agriculture for small-scale farmers
title_sort scalable scheme to implement data driven agriculture for small scale farmers
topic agriculture
data
machine learning
aprendizaje electrónico
colombia
small scale farming
pequeñas explotaciones
url https://hdl.handle.net/10568/103626
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