Thursday, February 15, 2024 — 11:00 – 11:40 a.m. 

Crop imagery from drones and satellites can now provide farmers and agronomists useful information to assist in crop management. This presentation will review some of the recent research at the Crop Imaging Lab at the University of Saskatchewan. We are now at a crossroads where remotely sensed satellite information can be analyzed with machine learning to inform agronomic decisions. Cheap drones can be used to scout canola fields for crop emergence and allow farmers to make informed reseeding decisions. UAV trained machine learning models can now use satellite data to map kochia infestations on farmer’s fields and target control measures. AI models informed with satellite and environment data can make accurate yield predictions before harvest. Crop classification maps can be used to determine the risk of root rot based on crop rotations for any field in western Canada. And finally, our lab is in the process of wall-to-wall mapping of all western Canada at a 10m resolution to measure and understand the causes of within field spatial variability in crop yield and profitability.