Modelling interaction dynamics between two foliar pathogens in wheat: a multi-scale approach.

Area of Science:

• Plant pathology
• Computational biology
• Agricultural science

Background:

• Epidemiological models often simplify pathosystems by focusing on single pathogens.
• Interactions between multiple parasites on a single host and canopy properties are crucial but understudied.
• This research addresses the need for models that incorporate disease complexes and plant architecture.

Purpose of the Study:

• To develop a novel disease complex model integrating two wheat fungal diseases (Zymoseptoria tritici and Puccinia triticina) with a functional-structural wheat plant model.
• To investigate the competitive interactions between septoria and brown rust at both leaf and canopy scales.
• To explore how canopy properties influence the dynamics of these interacting diseases.

Main Methods:

• Developed coupled sub-models for infection cycles of Zymoseptoria tritici and Puccinia triticina, including lesion competition at the leaf scale.
• Created a geometrically explicit model of lesion interaction, then upscaled it into a statistical metamodel.
• Integrated the statistical leaf-scale model into a 3-D epidemiological canopy growth model to simulate disease dynamics.

Main Results:

• The statistical leaf-scale model accurately represented the mechanistic model's outcomes.
• At the canopy scale, septoria significantly impacted brown rust epidemics across various scenarios, with limited reciprocal effect.
• Modifying rust's latent period or inoculum timing shifted competition dynamics, leading to more balanced epidemics.

Conclusions:

• This study represents a foundational step in integrating multiple diseases into virtual plant models.
• Findings highlight the differential competitive advantages of pathogens and the influence of disease-specific parameters.
• Further research is needed to elucidate complex interactions between canopy architecture and competing pathogens for sustainable crop protection.