Modeling Biological Responses to Meteorological Variables to Predict Disease Risk for European Canker (Neonectria...

Area of Science:

• Plant Pathology
• Epidemiology
• Mathematical Modeling

Background:

• European canker (EC), caused by Neonectria ditissima, significantly impacts apple tree health and yield, especially in wet climates.
• Effective disease management relies on accurate prediction models integrating biological and epidemiological data.
• Current management practices can be enhanced by understanding pathogen responses to weather patterns.

Purpose of the Study:

• To develop a mathematical model of the European canker disease cycle.
• To identify critical epidemiological mechanisms, particularly pathogen responses to meteorological factors.
• To enable infection risk comparisons and support decision-making for EC management.

Main Methods:

• A mathematical model was developed incorporating experimental and published data.
• Model parameters included infection response to temperature, rainfall, and tree disease incidence.
• Spore production was modeled in relation to lesion drying dynamics.

Main Results:

• Sensitivity analysis indicated optimal temperature as the most influential parameter for predicted risk.
• Rainfall and drying thresholds had minimal impact on infection risk predictions.
• Daily and annual accumulated infection risk indices showed significant variation across regions and years.

Conclusions:

• The developed model provides a tool for comparing EC infection risk across different locations and time periods.
• The model highlights the need for adaptive management strategies in response to varying infection pressures.
• Further international calibration and validation are recommended for broader application of the EC infection risk prediction model.