A foliar disease model for use in wheat disease management decision support systems.

A model of winter wheat foliar disease is described, parameterised and tested for Septoria tritici (leaf blotch), Puccinia striiformis (yellow rust), Erysiphe graminis (powdery mildew) and Puccinia triticina (brown rust). The model estimates diseaseinduced green area loss, and can be coupled with a wheat canopy model, in order to estimate remaining light intercepting green tissue, and hence the capacity for resource capture. The model differs from those reported by other workers in three respects. Firstly, variables (such as weather, host resistance and inoculum pressure) which affect disease risk are integrated in their effect on disease progress. The agronomic and meteorological data called for are restricted to those commonly available to growers by their own observations and from meteorological service networks. Secondly, field observations during the growing season can be used both to correct current estimates of disease severity and modify parameters which determine predicted severity. Thirdly, pathogen growth and symptom expression are modeled to allow the effects of fungicides to be accounted for as protectant activity (reducing infections which occur postapplication) and eradicant activity (reducing growth of pre-symptomatic infections). The model was tested against data from a wide range of sites and varieties, and was shown to predict the expected level of disease sufficiently accurately to support fungicide treatment decisions

A White Paper on Global Wheat Health Based on Scenario Development and Analysis

International audienceScenario analysis constitutes a useful approach to synthesize knowledge and derive hypotheses in the case of complex systems that are documented with mainly qualitative or very diverse information. In this article, a framework for scenario analysis is designed and then, applied to global wheat health within a timeframe from today to 2050. Scenario analysis entails the choice of settings, the definition of scenarios of change, and the analysis of outcomes of these scenarios in the chosen settings. Three idealized agrosystems, representing a large fraction of the global diversity of wheat-based agrosystems, are considered, which represent the settings of the analysis. Several components of global changes are considered in their consequences on global wheat health: climate change and climate variability, nitrogen fertilizer use, tillage, crop rotation, pesticide use, and the deployment of host plant resistances. Each idealized agrosystem is associated with a scenario of change that considers first, a production situation and its dynamics, and second, the impacts of the evolving production situation on the evolution of crop health. Crop health is represented by six functional groups of wheat pathogens: the pathogens associated with Fusarium head blight; biotrophic fungi, Septoria-like fungi, necrotrophic fungi, soilborne pathogens, and insect-transmitted viruses. The analysis of scenario outcomes is conducted along a risk-analytical pattern, which involves risk probabilities represented by categorized probability levels of disease epidemics, and risk magnitudes represented by categorized levels of crop losses resulting from these levels of epidemics within each production situation. The results from this scenario analysis suggest an overall increase of risk probabilities and magnitudes in the three idealized agrosystems. Changes in risk probability or magnitude however vary with the agrosystem and the functional groups of pathogens. We discuss the effects of global changes on the six functional groups, in terms of their epidemiology and of the crop losses they cause. Scenario analysis enables qualitative analysis of complex systems, such as plant pathosystems that are evolving in response to global changes, including climate change and technology shifts. It also provides a useful framework for quantitative simulation modeling analysis for plant disease epidemiology

A white paper on global wheat health based on scenario development and analysis.

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An experimental design to test the effect of wheat variety mixtures on biodiversity and ecosystem services

Website: https://www6.inra.fr/wheatamix The present document details how the Wheatamix consortium, inspired by ecological experiments exploring relationships between plant biodiversity and ecosystem functioning (e.g. the Jena experiment Weisser et al. 2017), selected bread wheat (Triticum aestivum L.) lines, phenotyped them across a range of functional traits and used this information to set up an experimental design able to unravel the effects of variety number and of the functional diversity and identity within variety mixtures for evaluating the impact of intraspecific crop diversity on a range of ecosystem services. Wheat line selection The Wheatamix project investigates the potential benefits of variety mixtures in the Paris basin wheat supply chain, and therefore focuses on varieties and lines adapted to the local climate. A consensus list of 57 wheat lines (Table 1) was thus settled on these grounds and to meet the expectations of agronomists, geneticists, phytopathologists and ecophysiologists of the group. This list is composed of i) 32 elite bread wheat varieties registered in the French catalogue, selected for their high yields under conventional farming, ii) 5 modern varieties bred for organic farming (OF), iii) 10 landraces resulting from farmers' mass-selection, cultivated in France in the early 1900es, and iv) 11 lines from an INRA-MAGIC multiparental and highly recombinant population (Thepot et al., 2015), adapted to Northern France. Due to the heterogeneity of information available for each variety and line, various criteria were used for this selection. The 32 elite bread wheat varieties were chosen on the basis of their wide use in the Paris Basin, and to ensure representativeness of the diversity for earliness, disease resistance or bread-making quality, using the available information in the variet

An experimental design to test the effect of wheat variety mixtures on biodiversity and ecosystem services

The present document details how the Wheatamix consortium, inspired by ecological experiments exploring relationships between plant biodiversity and ecosystem functioning (e.g. the Jena experiment), selected bread wheat (Triticum aestivum L.) lines, phenotyped them across a range of functional traits and used this information to set up an experimental design able to unravel the effects of variety number and of the functional diversity and identity within variety mixtures for evaluating the impact of intraspecific crop diversity on a range of ecosystem services.Website: https://www6.inra.fr/wheatamix The present document details how the Wheatamix consortium, inspired by ecological experiments exploring relationships between plant biodiversity and ecosystem functioning (e.g. the Jena experiment Weisser et al. 2017), selected bread wheat (Triticum aestivum L.) lines, phenotyped them across a range of functional traits and used this information to set up an experimental design able to unravel the effects of variety number and of the functional diversity and identity within variety mixtures for evaluating the impact of intraspecific crop diversity on a range of ecosystem services. Wheat line selection The Wheatamix project investigates the potential benefits of variety mixtures in the Paris basin wheat supply chain, and therefore focuses on varieties and lines adapted to the local climate. A consensus list of 57 wheat lines (Table 1) was thus settled on these grounds and to meet the expectations of agronomists, geneticists, phytopathologists and ecophysiologists of the group. This list is composed of i) 32 elite bread wheat varieties registered in the French catalogue, selected for their high yields under conventional farming, ii) 5 modern varieties bred for organic farming (OF), iii) 10 landraces resulting from farmers' mass-selection, cultivated in France in the early 1900es, and iv) 11 lines from an INRA-MAGIC multiparental and highly recombinant population (Thepot et al., 2015), adapted to Northern France. Due to the heterogeneity of information available for each variety and line, various criteria were used for this selection. The 32 elite bread wheat varieties were chosen on the basis of their wide use in the Paris Basin, and to ensure representativeness of the diversity for earliness, disease resistance or bread-making quality, using the available information in the variet