Crowdsourcing Farmers' Data: Agri-Support and CIMMYT Collaboration Projects

Currently, there is a growing need for an accurate and up-to-date information system on crop condition and diseases for monitoring agricultural production. The Agri-Support project aims at addressing the issue through an app that enables to collect, analyze and disseminate valuable information in the field.

The Agri-Support app allows farmers to record field information used to analyze spatial distribution of different types of food crops in local conditions, as well as to validate and calibrate crop and land use maps. As feedback, Agri-Support allows farmers to receive warnings of impending risks and events. The app is available globally and currently being tested in Brazil.

The Agri-Support app is being further developed in cooperation with CIMMYT (International Maize and Wheat Improvement Center) to promote sustainable agricultural intensification in Mexico. The CIMMYT collaboration project ‘’Technological Portfolios and Modeling Techniques for Sustainable Intensification’’ aims to provide farmers and extension workers with relevant cropping information in an easily available and timely manner through the app. Offering a two-way communication platform, the app will allow farmers to provide crop information and in return obtain recommendations such as windows of opportunity for fertilization, potential yield compared to similar agro-ecological zones as well as weather forecasts and historical weather data. The latter will be based on local and national databases, weather stations and forecasts.

The agronomical suggestions will be based on CIMMYT’s portfolio of techniques as well as IIASA’s applied crop modeling techniques, both aiming to increase productivity and yield, as well as reducing risks and quantifying costs. All the recommendations will be available through the app and much of this information could also be stored offline updating its content when the user has internet access.

At the second stage of the project, results from IIASA’s EPIC model produced using detailed soil and agronomical data collected by farmers themselves will be incorporated to the portfolio of available information. These feedback mechanisms aim to make the collection of field information an attractive and important task for the farmers, since the information received in return would allow them to take actions in order to improve their harvests and optimize their costs.

Last edited: 09 December 2016