P-239 - Simulation analysis of a peanut leaf spot risk advisory in North Florida environments

Passalora arachidicola (early leaf spot) and Nothopassalora personata (late leaf spot ) causes the two most economically important peanut foliar diseases. Weather-based advisories have been developed by several researchers to optimize fungicide inputs. While initial studies utilized in-canopy sensors, later research relied on local weather stations without direct comparison to in-canopy conditions. Our objective was to compare data sources on fungicide schedules simulated with the 89-ADV. Sensors were installed within the canopy of research plots in Live Oak, FL (LO) in 2019 and 2022 and Quincy, FL (QY) in 2021. Simulated fungicides were applied after reaching 48 infection hours of favorable conditions (RH ≥ 95%, 16-32°C). Accumulation of infection hours began 30 days after planting and were reset to 0 under lethal environmental conditions or for 10 days after applying fungicides. The first fungicide was recommended soon (2 to 10 days) after beginning infection hours regardless of data source, but total applications were fewer using the local Florida Automated Weather Network (5 in LO 2019, 6 in QY 2021, 4 in LO 2022) compared to in-canopy (7 in LO 2019, 7 in QY 2021, 5 in LO 2022). This research shows that sensor location can impact weather-based disease risk advisories and a need for optimizing when to initiate infection hours. The 89-ADV assumes pathogen presence on leaves but does not account for the complex factors that affect the time and amount of inoculum dispersed from residue in the soil. Our next step is to incorporate these factors to improve the model.