The University of Florida was awarded a $747,671 Project Grant from the United States Department of Agriculture National Institute of Food and Agriculture under the Agriculture and Food Research Initiative competitive grants program (AFRI, CFDA No. 10.310). The four-year project aims to enhance modeling of broadleaf weed emergence across diverse agricultural regions in the southeastern U.S. through several key deliverables. Researchers will develop deep learning models to detect and identify weed species in farm fields using imagery from autonomous sensor stations. Emergence data collected by the sensors will be used to create temperature-based weed emergence models. An online platform will then be designed to embed the models and provide a decision support system to help growers better manage climate risks and optimize weed management inputs. The project supports AFRI priorities around pest and beneficial species factors affecting crop production systems.
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