Machine learning in agriculture: scientists are teaching computers to diagnose soybean stress

AMES, Iowa - Iowa State University scientists are working toward a future in which farmers can use unmanned aircraft to spot, and even predict, disease and stress in their crops. Their vision relies on machine learning, an automated process in which technology can help farmers respond to plant stress more efficiently. Arti Singh, an adjunct assistant professor of agronomy, is leading a multi-disciplinary research team that recently received a three-year, $499,845 grant from the U.S Department of Agriculture's National Institute of Food and Agriculture to develop machine learning technology that could automate the ability of farmers to diagnose a range of major stresses in soybeans. The technology under development would make use of cameras attached to unmanned aerial vehicles, or UAVs, to gather birds-eye images of soybean fields. A computer application would automatically analyze the images and alert the farmer of trouble spots.