GeoAI-Driven Diseases and Pests Detection
Use Manual Observation to Detect Diseases and Pests
Problem Statement: Fusarium Head Blight (FHB) negatively impacts both yield and quality and is the most damaging disease in Canadian wheat. Early detection of FHB is dependent on manual crop assessment and FHB risk maps. However, the provincial governments’ online FHB risk maps consider only the environment and do not perfectly represent a farmer’s individual field. In warm weather, growth stages where fungicides can be effectively applied last only a day or two, making accuracy vital. Quantification of wheat disease severity is based on manual observation. Breeders manually count FHB affected wheat heads on many thousands of cultivars. Moreover, the assessment accuracy can be dramatically reduced by fatigue and external distractions.
Early identification and evaluation of FHB severity are crucial. Losses in Canada due to FHB have ranged from $50 million to $300 million annually since the early 1990s.
Fusarium Head Blight (FHB)
Leverage Geospatial, AI, and UAV Technologies to Rapidly Detect and Control Diseases and Pests
GeoAI-Driven Drone Knows When and Where to Spray Fungicide and Pesticide.
Current manual observations often discover disease too late for effective treatment. Our platform can incorporate various data sources to create timely high-resolution FHB risk maps and identify disease and wheat growth stages for targeted fungicide application. This allows farmers to make improved management decisions, including reducing excessive fungicide and pesticide use.