Page 86 - Frontier Technologies to Protect the Environment and Tackle Climate Change

Frontier Technologies to Protect the Environment and Tackle Climate Change

The CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS)
reported that in 2014, 170 Colombian rice farmers avoided massive losses by taking the
advice of their producers’ federation, FEDEARROZ, not to plant in the first of the two annual
growing seasons. The farmers who took the advice avoided economic losses estimated at
USD 1.7 million. FEDEARROZ acted on a forecast by a team of young CCAFS scientists based
at the International Center for Tropical Agriculture (CIAT). The scientists mined ten years of
weather and crop data to understand how climatic variation impacts rice yields. The team
then fed patterns in climate and yields into a computer model and predicted a drought in
the Caribbean department of Córdoba, which led it to conclude that farmers in some regions
could save themselves from crop failure by not planting at all.

The ability to analyse masses of crop and climate data to provide farmers with accurate,
site-specific forecasts and advice has had huge implications, not only for rice, but also
for cassava, beans and potato (the main crops in Colombia). In Colombia, rice production
had fallen from around 6 tonnes a hectare to 5 tonnes since 2007. Variable weather from
season to season meant that harvests could fluctuate by 30 to 40 per cent. Now, based
on trends identified by the CIAT-CCAFS data team, FEDEARROZ and government extension
services in three regions recommend the rice varieties that work best under specific weather
conditions, and the best date to plant. By heeding forecasts and specific recommendations
on what, when and how to plant rice in their area, the farmers can avoid losses of 1 to 2
tonnes per hectare. This matters, because farmers in Colombia already struggle to remain
competitive in both domestic and export markets.
The CCAFS team recognized that more comprehensive data enable better and more accurate
forecasts. To collect more data, the team developed a mobile phone app for farmers to
capture and share information about their farms and their rice, maize and bean cultivation
practices. This local knowledge and site-specific information, when fed into the computer
model, enable scientists to refine their advice further. This advice gives farmers even more
of an advantage: as weather conditions become more variable, they can increase production
and so avoid catastrophic losses. The tools are now being scaled out throughout Colombia,
Argentina, Nicaragua, Peru and Uruguay.

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