Development of Weather-Based Predictive Models for Fusarium Head Blight and Deoxynivalenol Accumulation for Spring...

Area of Science:

• Agricultural Science
• Plant Pathology
• Food Safety

Background:

• Fusarium head blight (FHB) is a significant disease in malting barley.
• Deoxynivalenol (DON) contamination poses a risk to grain quality and safety.
• Understanding FHB and DON dynamics is crucial for crop management.

Purpose of the Study:

• To examine the association between FHB, DON accumulation, and weather conditions in spring malting barley.
• To develop predictive models for DON accumulation based on hourly weather data.
• To assess the risk of economically significant DON contamination.

Main Methods:

• Data collected over six growing seasons in the U.S. Northern Great Plains.
• FHB incidence and DON concentration measured in three barley cultivars.
• Nine predictor variables derived from hourly temperature and relative humidity data.
• Logistic regression models developed using a 0.5 mg/kg DON threshold.

Main Results:

• FHB incidence strongly correlates with DON accumulation in barley grain.
• Four predictive models demonstrated >80% sensitivity for DON risk.
• Model specificity ranged from 67% to 84%.
• The most effective predictor combined average temperature and duration of high relative humidity (>90%).

Conclusions:

• Weather conditions preceding head emergence are key predictors of DON accumulation.
• Predictive models can accurately forecast the risk of economically significant DON levels.
• This research aids in managing FHB and ensuring malting barley quality.