Corinne Robert

Coupling a 3D virtual wheat (Triticum aestivum) plant model with a Septoria tritici epidemic model (Septo3D): a new approach to investigate plant–pathogen interactions linked to canopy architecture

This work initiates a modelling approach that allows us to investigate the effects of canopy architecture on foliar epidemics development. It combines a virtual plant model of wheat (Triticum aestivum L.) with an epidemic model of Septoria tritici which is caused by Mycosphaerella graminicola, a hemi-biotrophic, splashed-dispersed fungus. Our model simulates the development of the lesions from the infected lower leaves to the healthy upper leaves in the growing canopy. Epidemics result from the repeated successions of lesion development (during which spores are produced) and spores dispersal. In the model, canopy development influences epidemic development through the amount of tissue available for lesion development and through its effects on rain penetration and droplets interception during spore dispersal. Simulations show that the impact of canopy architecture on epidemic development differs between canopy traits and depends on climate. Phyllochron has the strongest effect, followed by leaf size and stem elongation rate.

Wheat Leaf Rust Uredospore Production on Adult Plants: Influence of Leaf Nitrogen Content and Septoria tritici Blotch

ABSTRACT Leaf rust uredospore production and lesion size were measured on flag leaves of adult wheat plants in a glasshouse for different lesion densities. We estimated the spore weight produced per square centimeter of infected leaf, per lesion, and per unit of sporulating area. Three levels of fertilization were applied to the plants to obtain different nitrogen content for the inoculated leaves. In a fourth treatment, we evaluated the effect of Septoria tritici blotch on leaf rust uredospore production. The nitrogen and carbon content of the spores was unaffected or marginally affected by lesion density, host leaf nitrogen content, or the presence of Mycosphaerella graminicola on the same leaf. In leaves with a low-nitrogen content, spore production per lesion was reduced, but lesion size was unaffected. A threshold effect of leaf nitrogen content in spore production was however, evident, since production was similar in the medium- and high-fertilizer treatments. In leaves inoculated with M. graminicola and Puccinia triticina, the rust lesions were smaller and produced fewer spores. The relationships among rust lesion density, lesion size, and uredospore production were fitted to a model. We determined that the density effect on spore production resulted mainly from a reduction in lesion size, the spore production per unit of sporulating surface being largely independent of lesion density. These results are consistent with those obtained previously on wheat seedlings. The main difference was that the sporulation period lasted longer in adult leaves.

Aggressiveness components and adaptation to a host cultivar in wheat leaf rust.

Experimental evidence on the capacity of pathogen populations to quantitatively adapt to their hosts and on the life traits that are involved is lacking at this time. In this article, we identified a situation in which a leaf rust pathotype (P1) was found at a high frequency on a widely grown cultivar (Soissons) and we tested the hypothesis that P1 was more aggressive on Soissons than other virulent pathotypes (P2 and P3). Several components of the pathogen life cycle were measured on adult wheat plants in two different experiments under greenhouse conditions: latent period, spore production per lesion and per unit of sporulating tissue, uredinium size, and lesion life span. Regardless of the component, pathotype P1 was repeatedly found to be more aggressive than at least one of the other two pathotypes, with differences of 5 to 51%. Breaking down spore production per lesion into uredinium size and spore production per square millimeter of sporulating tissue showed that the three pathotypes presented different aggressiveness profiles, suggesting different development constraints for the pathogen, either for its growth capacity into host tissues or its ability to exploit the host resources for spore production. Although leaf rust pathotypes present a clonal structure, quantitative differences were found for aggressiveness traits within a pathotype.

Wheat leaf rust uredospore production and carbon and nitrogen export in relation to lesion size and density

ABSTRACT To develop mechanistic yield loss models for biotrophic fungi, we need better account for the export of dry matter, carbon, and nitrogen from the leaf into the spores. Three experiments in controlled environment chambers were performed to study the dynamics of uredospores production of Puccinia triticina on seedling leaves of wheat in relation to time, lesion density, and sporulating surface area. The detrimental effect of lesion density on the sporulation capacity of brown rust lesions was confirmed. When lesion density increased, spores production per lesion strongly decreased. However, our results showed that increasing lesion density also greatly reduces lesion size. A model was developed to summarize these relationships. Our main conclusion is that the density effect on spore production per lesion is accounted for by lesion size. When sporulation was related to the sporulating surface area, it became independent of density. As well, carbon and nitrogen contents of the spores were independent of lesion density. Our data suggest that when nitrogen available in the host is limiting, spore production is reduced but nitrogen content of spores tend to remain stable.

Local dispersal of Puccinia triticina and wheat canopy structure.

The development of dynamic models jointly to simulate host growth and disease spread necessitates a precise description of pathogen dispersal in relation to canopy structure. In this study, we measured disease spread from a single infected leaf positioned at different heights in wheat canopies. The resulting lesion distribution was described along crop rows and over three leaf layers. The spore sources, although limited to a single leaf, nearly saturated the host surface accessible to the spores. Most of the lesions were found within 30 to 40 cm of the source. The vertical position of the source influenced the lesion distribution and the steepness of the disease gradients. The leaf layer and the wheat row that contained the spore source were the most infected. Close to the source, a few heavily infected leaves produced steep disease gradients, whereas spore diffusion resulted in shallower gradients along the adjacent rows and on the other leaf layers. Depending on the precision needed, the lesion distribution can be described either at the level of leaf layers or by dispersal gradients for each row and leaf layer.

Variation in aggressiveness is detected among Puccinia triticina isolates of the same pathotype and clonal lineage in the adult plant stage

Puccinia triticina reproduces asexually in France and thus individual genotype is the unit of selection. A strong link has been observed between genotype identities (as assessed by microsatellite markers) and pathotypes (pools of individuals with the same combination of qualitative virulence factors). Here, we tested whether differences in quantitative traits of aggressiveness could be detected within those clonal lineages by comparing isolates of identical pathotype and microsatellite profile. Pairs of isolates belonging to different pathotypes were compared for their latent period, lesion size and spore production capacity on adult plants under greenhouse conditions, with a high number of replicates. Isolates of the same pathotype showed remarkably similar values for the measured traits, except in three situations: differences were obtained within two pathotypes for latent period and within one pathotype for sporulation capacity. One of these differences was tested again and confirmed. This indicates that the average aggressiveness level of a leaf rust pathotype may increase without any change in its virulence factors or microsatellite profile.

Crop Fertilization Impacts Epidemics and Optimal Latent Period of Biotrophic Fungal Pathogens

Crop pathogens are known to rapidly adapt to agricultural practices. Although cultivar resistance breakdown and resistance to pesticides have been broadly studied, little is known about the adaptation of crop pathogens to fertilization regimes and no epidemiological model has addressed that question. However, this is a critical issue for developing sustainable low-input agriculture. In this article, we use a model of life history evolution of biotrophic wheat fungal pathogens in order to understand how they could adapt to changes in fertilization practices. We focus on a single pathogen life history trait, the latent period, which directly determines the amount of resources allocated to growth and reproduction along with the speed of canopy colonization. We implemented three fertilization scenarios, corresponding to major effects of increased nitrogen fertilization on crops: (i) increase in nutrient concentration in leaves, (ii) increase of leaf lifespan, and (iii) increase of leaf number (tillering) and size that leads to a bigger canopy size. For every scenario, we used two different fitness measures to identify putative evolutionary responses of latent period to changes in fertilization level. We observed that annual spore production increases with fertilization, because it results in more resources available to the pathogens. Thus, diminishing the use of fertilizers could reduce biotrophic fungal epidemics. We found a positive relationship between the optimal latent period and fertilization when maximizing total spore production over an entire season. In contrast, we found a negative relationship between the optimal latent period and fertilization when maximizing the within-season exponential growth rate of the pathogen. These contrasting results were consistent over the three tested fertilization scenarios. They suggest that between-strain diversity in the latent period, as has been observed in the field, may be due to diversifying selection in different cultural environments.

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.

Sharing efforts for modelling plant systems: from publications to reusable software components

Plant models become increasingly complex and their implementation often implies the use of advanced techniques in computer science. This evolution has been accompanied by the production of dedicated plant modelling tools, such as simulation platforms, that facilitate research in this field. However, much less sharing is observed for plant models themselves, that is for computer programs produced by scientists to address their specific questions. Yet, these programs could be highly valuable for other researchers, to avoid redundant development of similar code or to help non-specialists to simulate parts of a complex system. Model descriptions found in academic publications, even combined with code sources, are generally not sufficient for model reuse. Most difficulties come from the heterogeneity of language used, the structure of the programs, the download and installation procedures, the accessibility to the source code of the model, and the availability of documentation. The OpenAlea initiative (http://openalea.gforge.inria.fr) has been launched to address these problems by providing plant modellers with collaborative tools and guidelines to increase software quality, hence re-usability of their models. The Alinea pilot project further tested these concepts in a sample community of ecophysiologists and biophysicists. Based on this experience, we illustrate pros and cons of the approach and discuss future direction of progress. We foresee three steps towards a better re-usability of models: a better interoperability of existing tools and simulation platforms, the emergence of design patterns for plant modelling, and the definition of standardised data structures.