Currently, field treatments for soybean aphids (SBA) are based on average field populations that are determined through the timely process of scouting. More recent research has suggested that near-infrared remote sensing may be able to detect plant stresses, but this has not been expanded to a field/landscape scale. Post-doc Arthur Vieira Ribeiro and Professor’s Robert Koch and Ian MacRae recently published a paper titled Economic-threshold-basedclassification of soybean aphid, Aphis glycines, infestations incommercial soybean fields using Sentinel-2 satellite data. With the use of the Sentinel-2 satellite, which offers free multispectral imagery, Koch and his team have been able to take full field images. They analyze these images with the help of AI to help determine the SBA population density. This could save the farmers lots of time in their busiest season, and advance regional and local management programs for SBA.
Watch the CBS interview, read the University of Minnesota’s research brief and the published study to learn more.
