A Distributed Lag Analysis of the Relationship Between Gibberella zeae Inoculum Density on Wheat Spikes and Weather...

Area of Science:

• Plant Pathology
• Agricultural Meteorology
• Mycology

Background:

• Gibberella zeae is a significant pathogen affecting wheat canopies.
• Understanding the relationship between weather and pathogen inoculum is crucial for disease management.
• Previous studies have not fully characterized the temporal dynamics of weather impacts on inoculum levels.

Purpose of the Study:

• To characterize the association between specific weather variables and Gibberella zeae inoculum abundance in wheat canopies.
• To identify the time window and functional form of weather variable effects on pathogen propagules.
• To assess the influence of location and year on inoculum levels.

Main Methods:

• Wheat spikes were sampled across multiple locations (1999-2005) and assayed for Gibberella zeae colony forming units per spike (CFU/spike).
• 49 daily weather variables were analyzed using polynomial distributed lag regression and linear mixed models.
• Statistical models identified significant weather variables, their time lags, and the form of their relationship with log-transformed CFU/spike.

Main Results:

• Inoculum abundance (CFU/spike) was significantly related to weather variables from the day of sampling and up to 8 days prior (9-day window).
• Moisture-related variables (e.g., relative humidity) showed the strongest association, followed by air temperature and rainfall.
• All significant weather variables had a positive marginal effect on inoculum levels; location and year influenced magnitude but not temporal trends.

Conclusions:

• Local weather conditions are key predictors of Gibberella zeae spore density on wheat spikes.
• The identified 9-day weather influence window and variable relationships can enhance predictive models.
• This research provides a foundation for utilizing weather data to forecast pathogen pressure and optimize wheat disease management strategies.