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

Describing and predicting epidemic progress is critical for effective reduction of crop losses due to infectious diseases. Disease progression is commonly characterized using quantitative or semi-quantitative indicators of severity, influenced by both pathogen growth at the organ scale and its spread at the plant scale. Although these two processes cannot be disentangled from raw data alone, we developed a mechanistic model that, for the first time, distinguishes disease growth within organs from dispersal between organs. We fitted this model to a set of experimental data on the severity of foliar anthracnose and Ascochyta blight on four susceptible pea cultivars (Flambo, Hamino, Smiley, and Spencer) at five time points in pure stand plots or in plots intercropped with wheat under natural infection conditions. Disease spread and growth over thermal time (degree days) and space (leaf levels) was modeled by a two-variable logistic function, derived from an approximation of the traveling wave Fisher-KPP model solution. Results showed that the apparent diffusion speed of the disease varied across cultivars, years, and cropping systems and was consistently reduced under intercropping. By interpreting model parameters biologically, we identified apparent diffusion as a novel quantitative trait to characterize pathogen strategies and epidemic speed. This new metric offers plant pathologists and breeders a useful tool to better describe within-plant disease progression across environments and genotypes. [Formula: see text]