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

Creator: Savary, S.
Creator: Djurle, A.
Creator: Yuen, J.
Creator: Ficke, A.
Creator: Rossi, V.
Creator: Esker, P.D.
Creator: Fernandes, J.M.C.
Creator: Ponte, E.M. Del
Creator: Kumar, J.
Creator: Madden, L.V.
Creator: Paul, P.
Creator: McRoberts, N.
Creator: Singh, P.K.
Creator: Huber, L.
Creator: Pope de Vallavielle, C.
Creator: Saint-Jean, S.
Creator: Willocquet, L.
Year: 2017
ISSN: 1943-7684 (Online)
ISSN: 0031-949X (Print)
Abstract: Scenario 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.
Format: PDF
Language: English
Publisher: American Phytopathological Society (APS)
Copyright: CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose.
Type: Article
Place of Publication: St. Paul, MN (USA)
Pages: 1109-1122
Issue: 10
Volume: 107
DOI: 10.1094/PHYTO-01-17-0027-FI
Agrovoc: WHEAT
Journal: Phytopathology

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  • Wheat
    Wheat - breeding, phytopathology, physiology, quality, biotech

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