A Modeling Approach to Separate Within-Leaf Pathogen Growth from Whole-Plant Pathogen Dispersal - A Case Study on Pea...

Area of Science:

• Plant pathology
• Epidemiology
• Computational biology

Background:

• Predicting crop disease spread is vital for reducing losses.
• Disease progression involves pathogen growth and spread, often hard to separate.
• Current models struggle to distinguish between intra-organ pathogen growth and inter-organ dispersal.

Purpose of the Study:

• To develop a mechanistic model distinguishing disease growth within organs from dispersal between organs.
• To quantify the impact of intercropping on disease progression in pea cultivars.
• To introduce "apparent diffusion speed" as a novel trait for characterizing epidemic dynamics.

Main Methods:

• Developed a mechanistic model separating intra- and inter-organ disease processes.
• Fitted the model to foliar anthracnose and Ascochyta blight data in pea cultivars.
• Modeled disease spread using a logistic function derived from the Fisher-KPP model over thermal time and leaf levels.

Main Results:

• The model successfully distinguished disease growth from dispersal.
• Apparent diffusion speed varied across pea cultivars, years, and cropping systems.
• Intercropping peas with wheat consistently reduced apparent diffusion speed.

Conclusions:

• Apparent diffusion speed is a novel, biologically interpretable trait for epidemic characterization.
• This metric aids plant pathologists and breeders in assessing within-plant disease progression.
• Intercropping strategies show potential for managing foliar diseases in pea crops.