Predicting crop yields based on climate, planting and other variables can help regions optimize their limited resources.
Farmers are used to optimizing crop production on their own lands. They do soil tests to choose the right amount of fertilisers to apply and they sometimes plant row crops on some fields while keeping others in pasture. But is it possible to optimize production across a much bigger area? That’s the question a team of USDA-ARS
Crop Systems and Global Change Lab scientists in Beltsville (USA) has begun to tackle by developing a sophisticated new modeling tool.
Known as the
Geospatial Agricultural Management and Crop Assessment Framework, the tool brings together crop models that estimate plant growth and crop yield at scales as fine as 30 meters (90 feet), with spatial sources of information on soils, water, land use and other factors. Crop models aren’t normally designed to work automatically with spatial data, explains
Jonathan Resop, who led the platform’s development as a USDA-ARS postdoc. Now, the new interface - published in Agronomy journal (see
abstract) - allows exactly that.
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Scource: American Society of Agronomy