Plant architecture and foliar senescence impact the race between wheat growth and Zymoseptoria tritici epidemics.

Background and Aims: In order to optimize crop management in innovative agricultural production systems, it is crucial to better understand how plant disease epidemics develop and what factors influence them. This study explores how canopy growth, its spatial organization and leaf senescence impact Zymoseptoria tritici epidemics. Methods: We used the Septo3D model, an epidemic model of Septoria tritici blotch (STB) coupled with a 3-D virtual wheat structural plant model (SPM). The model was calibrated and evaluated against field experimental data. Sensitivity analyses were performed on the model to explore how wheat plant traits impact the interaction between wheat growth and Z. tritici epidemics. Key Results: The model reproduces consistently the effects of crop architecture and weather on STB progress on the upper leaves. Model sensitivity analyses show that the effects of plant traits on epidemics depended on weather conditions. The simulations confirm the known effect of increased stem height and stem elongation rate on limiting STB progress on upper leaves. Strikingly, the timing of leaf senescence is one of the most influential traits on simulated STB epidemics. When the green life span duration of leaves is reduced by early senescence, epidemics are strongly reduced. Conclusions: We introduce the notion of a 'race' for the colonization of emerging healthy host tissue between the growing canopy and the developing epidemics. This race is 2-fold: (1) an upward race at the canopy scale where STB must catch the newly emerging leaves before they grow away from the spore sources; and (2) a local race at the leaf scale where STB must use the resources of its host before it is caught by leaf apical senescence. The results shed new light on the importance of dynamic interactions between host and pathogen.

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

Background and Aims: Disease models can improve our understanding of dynamic interactions in pathosystems and thus support the design of innovative and sustainable strategies of crop protections. However, most epidemiological models focus on a single type of pathogen, ignoring the interactions between different parasites competing on the same host and how they are impacted by properties of the canopy. This study presents a new model of a disease complex coupling two wheat fungal diseases, caused by Zymoseptoria tritici (septoria) and Puccinia triticina (brown rust), respectively, combined with a functional-structural plant model of wheat. Methods: At the leaf scale, our model is a combination of two sub-models of the infection cycles for the two fungal pathogens with a sub-model of competition between lesions. We assume that the leaf area is the resource available for both fungi. Due to the necrotic period of septoria, it has a competitive advantage on biotrophic lesions of rust. Assumptions on lesion competition are first tested developing a geometrically explicit model on a simplified rectangular shape, representing a leaf on which lesions grow and interact according to a set of rules derived from the literature. Then a descriptive statistical model at the leaf scale was designed by upscaling the previous mechanistic model, and both models were compared. Finally, the simplified statistical model has been used in a 3-D epidemiological canopy growth model to simulate the diseases dynamics and the interactions at the canopy scale. Key Results: At the leaf scale, the statistical model was a satisfactory metamodel of the complex geometrical model. At the canopy scale, the disease dynamics for each fungus alone and together were explored in different weather scenarios. Rust and septoria epidemics showed different behaviours. Simulated epidemics of brown rust were greatly affected by the presence of septoria for almost all the tested scenarios, but the reverse was not the case. However, shortening the rust latent period or advancing the rust inoculum shifted the competition more in favour of rust, and epidemics became more balanced. Conclusions: This study is a first step towards the integration of several diseases within virtual plant models and should prompt new research to understand the interactions between canopy properties and competing pathogens.

A modelling framework to simulate foliar fungal epidemics using functional-structural plant models.

BACKGROUND AND AIMS: Sustainable agriculture requires the identification of new, environmentally responsible strategies of crop protection. Modelling of pathosystems can allow a better understanding of the major interactions inside these dynamic systems and may lead to innovative protection strategies. In particular, functional-structural plant models (FSPMs) have been identified as a means to optimize the use of architecture-related traits. A current limitation lies in the inherent complexity of this type of modelling, and thus the purpose of this paper is to provide a framework to both extend and simplify the modelling of pathosystems using FSPMs. METHODS: Different entities and interactions occurring in pathosystems were formalized in a conceptual model. A framework based on these concepts was then implemented within the open-source OpenAlea modelling platform, using the platform's general strategy of modelling plant-environment interactions and extending it to handle plant interactions with pathogens. New developments include a generic data structure for representing lesions and dispersal units, and a series of generic protocols to communicate with objects representing the canopy and its microenvironment in the OpenAlea platform. Another development is the addition of a library of elementary models involved in pathosystem modelling. Several plant and physical models are already available in OpenAlea and can be combined in models of pathosystems using this framework approach. KEY RESULTS: Two contrasting pathosystems are implemented using the framework and illustrate its generic utility. Simulations demonstrate the framework's ability to simulate multiscaled interactions within pathosystems, and also show that models are modular components within the framework and can be extended. This is illustrated by testing the impact of canopy architectural traits on fungal dispersal. CONCLUSIONS: This study provides a framework for modelling a large number of pathosystems using FSPMs. This structure can accommodate both previously developed models for individual aspects of pathosystems and new ones. Complex models are deconstructed into separate 'knowledge sources' originating from different specialist areas of expertise and these can be shared and reassembled into multidisciplinary models. The framework thus provides a beneficial tool for a potential diverse and dynamic research community.