A generic model of interactions between FSPM, foliar pathogens and microclimate

International audienceA framework was defined to model the interactions between FSPM, foliar fungal pathogens and microclimate, with the concern of interoperability of the components and extensibility. The framework was applied on two existing models of pathosystems (powdery mildew on grapevine and septoria on wheat) to make them more modular and extensible. It will facilitate the design of new disease models on FSPMs

Etablissement et validation de classes de pédotransfert pour un modèle de culture à l'échelle parcellaire : application au modèle STICS

National audienceLe travail présenté s'inscrit dans le cadre d'une étude méthodologique de la modulation spatiale de la fertilisation azotée du blé. Il a été mené sur deux parcelles de 10 ha chacune, situées près de Laon, et présentant des caractéristiques pédologiques différentes. Il a consisté à créer, pour chaque parcelle, des classes de pédo-transfert (CPT) permettant d'estimer, à partir de cartes des sols établies à l'échelle du 1/2 500, les paramètres "sol" nécessaires à l'utilisation du modèle de culture Stics. Les paramètres suivants ont été étudiés pour leur grande influence sur les sorties du modèle : profondeur d'apparition d'un obstacle aux racines (obstarac); humidité massiques à la capacité au champ (Hcc) et au point de flétrissement (Hpf), densité apparente (Da), teneur en argile minéralogique (AM), de chaque horizon. Les observations ont été extraites de cartes d'impacts racinaires, effectuées au sein de fosses pédologiques, pour établir les CPT pour obstarac et de mesures, faites sur 82 points de prélèvements de chaque parcelle, pour les autres paramètres. Les résultats ont consisté à établir :(1) des critères qualitatifs pour prédire obstarac, (2) des classes combinant texture et type de matériau pour prédire Hcc, Hpf et DA et (3) une relation continue entre AM et des données analytiques. La qualité des prédictions des paramètres a permis de juger du bien fondé des méthodes utilisées. Les CPT d'obstarac semblent suffisantes, pour renseigner le modèle, dans les cas où les informations sur le sol sont accessibles. La prédiction de Hcc s'effectue quasiment sans biais et avec un RMSE de 0,02 g.g-1. La confrontation des sorties du modèle ainsi renseigné, aux variables d'intérêt mesurées, est satisfaisante. Le croisement des couches d'information sol et CPT a révélé la grande sensibilité du modèle Stics à 1a précision d'obtention de ces informations. Le déterminisme de la variabilité intra-parcellaire du stockage de l'eau et des solutés diffère selon les parcelles, avec : - la profondeur maximale d'enracinement, qui varie de 45 à 160 cm, dans la première parcelle : - la Hcc, qui varie de 6 et 23 % de teneur en eau massique, dans la seconde. La qualité des CPT obtenues pour la prédiction des paramètres du modèle est à mettre en lien avec le nombre de données acquises. Une telle approche, très lourde à mettre en oeuvre, ne peut être conçue que dans le cadre d'étude de parcelles expérimentales ou de secteurs de référence. La stratégie de constitution des CPT est tributaire du niveau de résolution spatiale choisi. Ce choix relève d'un débat pluri-disciplinaire pour permettre une modulation techniquement accessible, écologiquement utile et économiquement rentable

Data assimilation and parameter estimation for precision agriculture using the crop model STICS

International audienceMany different mathematical and statistical methods are essential in crop modeling. They are necessary in the development, analysis and application of crop models. Up to now, however, there has been no single source where crop modelers could learn about these methods. Furthermore, these methods are often described in other contexts and their application to crop modeling is not always straightforward. This book aims at making a large range of relevant mathematical and statistical methods accessible to crop modelers. Each methodology chapter starts from basic principles and simple applications and builds gradually to state-of-the-art methods. Crop models are used as examples, and practical advice on applying the methods to crop models is given. Working with Dynamic Crop Models is an essential learning and reference resource for students and researchers who want to understand and apply rigorous methods to crop models. This book will also be of value for other fields which use dynamic models of complex systems. Topics covered include: * Parameter estimation- including Bayesian methods * Model evaluation- including prediction quality and decision quality * Sensitivity analysis- including global analysis and interactions * Data assimilation- the Kalman filter and extensions * Management optimization- including stochastic optimization * Models for multiple fields- emphasizing how to obtain input values * Crop models and crop breeding - recent advances in using crop model

Data assimilation and parameter estimation for precision agriculture using the crop model STICS

International audienceMany different mathematical and statistical methods are essential in crop modeling. They are necessary in the development, analysis and application of crop models. Up to now, however, there has been no single source where crop modelers could learn about these methods. Furthermore, these methods are often described in other contexts and their application to crop modeling is not always straightforward. This book aims at making a large range of relevant mathematical and statistical methods accessible to crop modelers. Each methodology chapter starts from basic principles and simple applications and builds gradually to state-of-the-art methods. Crop models are used as examples, and practical advice on applying the methods to crop models is given. Working with Dynamic Crop Models is an essential learning and reference resource for students and researchers who want to understand and apply rigorous methods to crop models. This book will also be of value for other fields which use dynamic models of complex systems. Topics covered include: * Parameter estimation- including Bayesian methods * Model evaluation- including prediction quality and decision quality * Sensitivity analysis- including global analysis and interactions * Data assimilation- the Kalman filter and extensions * Management optimization- including stochastic optimization * Models for multiple fields- emphasizing how to obtain input values * Crop models and crop breeding - recent advances in using crop model

Using combined virtual plant - pathogen models to compare the influence of wheat architecture on epidemics of two contrasted foliar fungi

Book of abstracts-postersIt is urgent for agriculture to adopt new methods of crop protection that use less pesticide. In the perspective of agroecology, a solution is to regulate the pathogen populations via the properties of plant canopies. Here, we focus on the effects of plant architecture on foliar fungal epidemics. Combined FSPM-epidemic models are potential good tools to simulate these effects and to identify the most influential plant traits on epidemics. In wheat, the main fungal foliar diseases are septoria and brown rust. Both diseases develop lesions on leaves but the symptoms, the infection cycles and the dispersal types are different. Zymoseptoria tritici is a hemi-biotrophic fungus with sporulation occurring on necrotic leaf tissue after a biotrophic colonization phase, and it is mainly dispersed by rain-splash. Puccinia triticina is a strictly biotrophic fungus that grows and sporulates only on living tissues and spores are mainly dispersed by wind. The effects of architecture may depend on the dispersal strategy and infection cycle. This raises questions on the influence of plant architecture on these varied types of foliar fungi: do architectural traits impact their epidemics in the same way? Are there plant traits with opposite effects on the diseases? Answering these questions is crucial in the perspective of controlling fungi complexes on the same host. Several wheat architectural traits, such as stem height and plant development rate, are known to influence septoria. However, only very few studies are available on leaf rust. Our objective is to compare the effects of wheat architecture on epidemics of septoria and brown rust. For this, two FSPM models (Wheat-septoria and Wheat-brown rust) were developed and used to compare the effects of wheat properties on epidemics. The tested plant traits are phenology, organ growth rates (stems and leaves), organ dimensions, leaf curvature, and timing of leaf senescence. The outputs compared are the disease severity on each leaf rank of the canopy. The analysis is done for different climates. The results show that the two pathogens are impacted differently by plant architectural traits, even if they are both very sensitive to leaf green life span. The interaction with climate is also different. This work is an important step in developing methods to study varied pathosystems using FSPMs. This is also a first step to establish a more generic understanding of how different types of fungus are influenced by plant architectur

Elaboration d’un indicateur de nutrition azotée du blé basé sur l’indice foliaire et la teneur en chlorophylle

National audienc

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

International audienceBackground and AimsDisease 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.MethodsAt 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 ResultsAt 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.ConclusionsThis 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

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

International audienceBackground and AimsIn 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.MethodsWe 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 ResultsThe 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.ConclusionsWe 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