A team that´s bringing the Big Data revolution to agriculture
In search of better ways to achieve agricultural growth that helps reduce global hunger and poverty, the Big Data team of the Center´s Decision and Policy Analysis (DAPA) research area is exploring with farmer associations and government organizations how valuable information derived from massive amounts of data can better facilitate decision making.
“We focus on doing good work, delivering results, and ensuring that all members of our team are satisfied with the role they’re playing; good communication within the team is fundamental for success in the tasks that we give highest priority – documenting and publishing our research, delivering impact, and securing new support.”
Daniel JiménezDaniel says that the Big Data team is in the forefront of a movement aimed at democratizing the use of data and information to foster climate-smart agriculture, based on site-specific management. The team pursues this aim through projects with organizations in various countries, working through strategic alliances that respond to the urgent need in Latin America for reducing persistent yield gaps in agriculture.
Contributing to the reduction of hunger and poverty
The Big Data team contributes to CIAT´s mission of combatting hunger and poverty primarily through an approach referred to as “site-specific agriculture,” which involves sophisticated analysis of large volumes of data.
“In our work on site-specific agriculture, we aim to fine-tune farming systems, using a Big Data approach focused on identifying the factors or combinations of factors that best account for high or low production.”
Hugo DoradoIn working to make agriculture climate smart, we follow the principles of traditional agronomy, promoting changes based on direct observation. But we also exploit new opportunities created by recent technological advances in the collection, storage, and analysis of large sets of data and in the dissemination of processed information to facilitate decision making under specific conditions, with the aim of achieving sustainable intensification of agriculture.
In keeping with CIAT´s mission, climate-smart agriculture must also be socially equitable and environmentally friendly. To achieve these aims through data-driven approaches requires the development of low-cost methods and free software together with the application of open-data policies to democratize information access among the users who need it. The challenge then is to demonstrate how data analysis can boost production through more rational use of inputs.
Closing yield gaps in areas with similar soil and climate
The Big Data team has achieved concrete results in closing yield gaps, as with fruit production in Colombia. Focusing on production areas that are geographically distant but similar in soil and climate, the scientists identified agronomic practices that account for higher yields at some locations for transfer to others where yields are low.
This work took place through a project conducted jointly with the Colombian Vegetable and Fruit Growers Association (ASOHOFRUCOL, its acronym in Spanish), which created an information platform for the association and also strengthened the capacity of its staff. Currently, more than 4,000 farmers and 80 technicians benefit from use of the new tool.
Earning recognition
In 2014, during the build-up to the United Nations Climate Summit held in New York, the CIAT team was named one of two winners of the Big Data Climate Challenge by the UN Global Pulse. This award recognized the outstanding results of the team´s effort to help Colombia´s rice sector cope with climate change impacts. Carried out through an alliance with the country´s National Federation of Rice Growers (Fedearroz), this research built on much previous work with data analysis methods.
Also noteworthy is the continuing impact of the work with ASOHOFRUCOL, which has adopted Big Data concepts and approaches as a result of its relationship with the CIAT team, delivering important benefits to farmers.
In other important developments, the team has caught the attention of the World Bank, Latin American Fund for Irrigated Rice (FLAR) as well as national organizations in various countries of Latin America (Peru, Nicaragua, Brazil, Uruguay, and Argentina) and Eastern Africa (Uganda and Kenya), among others. Growing interest in the team´s data-driven approach to site-specific agriculture promises to considerably widen the scope of its influence.
Six years of learning
The Big Data team is decidedly multicultural, with members from various parts of Colombia (including the departments of Antioquia and Cauca as well as the national capital, Bogotá) along with France and the UK. The team is also multidisciplinary, requiring careful coordination of its work and respect for different points of view.
Through 6 years of research on Big Data at CIAT, the team has learned that to obtain good results it must plan and document its work with care and keep up to date its protocols for analyzing and interpreting data.
“We have biologists, agronomists, and statisticians on the team, and we all learn from one another and adapt to one another´s terminology. Now, we need to strengthen our capacity to handle new technologies and would particularly like to have additional expertise in the use of satellite imagery.”
Andrés AguilarA “big” team
The Big Data team is led by Daniel Jiménez, whose main functions, among others, are to ensure that its science is of high quality, achieves impact, and is strategically positioned, while also mobilizing more resources for research.
Sylvain Delerce provides leadership in agronomic analysis and interpretation of data; Hugo Andrés Dorado is the team´s most experienced statistician; Víctor Hugo Patiño, also a statistician, is an expert in processing climate information; Andrés Aguilar, works on modeling and processing of satellite imagery; and Luis Armando Muñoz coordinates project operations, using a knowledge management approach to ensure that the results and methods are appropriate for different actors.
