Data-driven agronomy

Data-driven agronomy allows research teams to explain historical events or predict relationships to provide partners, extension service providers, researchers, and farmers with new information and best practices about the relationships between different crop, environmental, and socioeconomic conditions. Simply put, these approaches allow researchers and agronomists to analyze different types of data from different sources to make tailored, site-specific recommendations to help farmers know what to plant, if they should plant, and when to plant.

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In what context is this tool useful?

Data-driven agronomy is useful when government and growers’ associations need to make targeted recommendations to maximize their resources.

Results achieved

The Alliance Bioversity - CIAT has developed tools to improve the yields and decision-making of more than 100,000 farmers through the development of tools for the collection, analysis of data and dissemination of information in a timely, practical and site-specific manner, with the objective of facilitating decision-making by producers and technicians on what, where, when and which agronomic practices to apply to obtain a sustainable production adapted to the climate.

The Alliance Bioversity - CIAT works within the Data Driven Agronomy Community of Practice to continue their exploration of using modern big data techniques to advance agricultural practices, in relation to particular socio-economic and environmental contexts in a way that promotes the democratization and transparency of agricultural information.

Contact people

Daniel Jiménez - D.Jimenez@cgiar.org