Development and Evaluation of Two Pecan Scab Prediction Models.

Area of Science:

• Plant Pathology
• Agricultural Meteorology
• Mycology

Background:

• Pecan scab, caused by Fusicladium effusum, is a major economic threat to pecan production.
• Current fungicide application advisories rely on 'scab hours,' defined by specific temperature and humidity thresholds.

Purpose of the Study:

• To validate the existing temperature and relative humidity thresholds used in pecan scab advisories.
• To explore alternative weather variables for predicting pecan scab development.

Main Methods:

• Collected disease severity data and hourly weather variables over multiple growing seasons and locations.
• Developed logistic regression models using generalized estimating equations, including temperature/relative humidity and dew point/dew point depression models.
• Validated model predictions against field observations.

Main Results:

• The temperature/relative humidity model indicated current thresholds are largely viable, though relative humidity may require adjustment.
• A dew point/dew point depression model, incorporating rain, adequately explained scab events.
• Model validation confirmed the influence of weather on pecan scab development.

Conclusions:

• The existing weather-based advisory for pecan scab is fundamentally sound but could be improved with humidity modifications.
• Future models for predicting pecan scab should incorporate dew point, dew point depression, and rainfall data.
• Optimizing fungicide application timing is crucial for managing this significant pecan pathogen.