Satellite-based remote sensing allows us to see much more than we can see when standing on the ground. New research from the University of Minnesota found, when combined with artificial intelligence, remote sensing could dramatically improve management of soybean aphid, an invasive pest that negatively impacts soybean yield and quality.
Published in the journal Crop Protection, the study shows that publicly available data from the Sentinel-2 satellite system — a pair of satellites orbiting Earth collecting imagery data — can be used to detect and classify infestations of soybean aphid in commercial fields.
This research was funded by the Minnesota Invasive Terrestrial Plants and Pests Center, supported by the Minnesota Environment and Natural Resources Trust Fund as recommended by the Legislative-Citizen Commission on Minnesota Resources.
Researchers compared Sentinel-2 imagery of commercial soybean fields with infestation assessments from staff manually counting aphids on plants in those fields. The team used regression analyses to determine if satellite data could detect plant stress caused by aphids.
