Title of the Thesis: “Mapping Potato Late Blight Risk using High-Resolution Weather Data”

Potato late blight (PLB), caused by the oomycete Phytophthora infestans, is one of the most damaging potato diseases in the world, and growers rely on frequent fungicide sprays to protect crops. While this approach has been effective, it does not always reflect actual disease risk and can lead to unnecessary costs, environmental impacts, and resistance issues. Newfoundland and Labrador’s (NL) cool, humid climate is well-suited to the disease, and PLB is observed in most growing seasons, but growers do not have access to reliable tools to inform timing of fungicide applications to protect their crops. Forecasting models such as Blitecast and NegFry are designed to guide spray decisions using weather and crop data but because of the spatial distance between many farms and available weather stations, these tools lack reliable inputs in NL and other parts of Atlantic Canada. To address this data gap high-resolution gridded weather data from Environment and Climate Change Canada’s (ECCC) High-Resolution Deterministic Prediction System (HRDPS) were evaluated as model inputs. Disease risk maps were then created in ArcGIS Pro to visualize disease risk, and we undertook a two-year field trial that compared model-based and calendar-based spray programs. This work evaluated existing PLB forecasting models in NL and found that forecasting models could potentially provide a practical and sustainable alternative to traditional PLB management practices in the region.

December 1, 2025, 12:30 pm via Web Conferencing

If you wish to attend the public presentation, please contact the Graduate Studies Coordinator at gsc@upei.ca to receive the link.