Year: 2021
Type: review
Abstract: Owing to their evolutionary potential, plant pathogens are able to rapidly adapt to genetically controlled plant resistance, often resulting in resistance breakdown and major epidemics in agricultural crops. Various deployment strategies have been proposed to improve resistance management. Globally, these rely on careful selection of resistance sources and their combination at various spatiotemporal scales (e.g., via gene pyramiding, crop rotations and mixtures, landscape mosaics). However, testing and optimizing these strategies using controlled experiments at large spatiotemporal scales are logistically challenging. Mathematical models provide an alternative investigative tool, and many have been developed to explore resistance deployment strategies under various contexts. This review analyzes 69 modeling studies in light of specific model structures (e.g., demographic or demogenetic, spatial or not), underlying assumptions (e.g., whether preadapted pathogens are present before resistance deployment), and evaluation criteria (e.g., resistance durability, disease control, cost-effectiveness). It highlights major research findings and discusses challenges for future modeling efforts.
Source: Annual Review of Phytopathology
Institutions: Commonwealth Scientific and Industrial Research Organisation, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Agriculture and Food, Pathologie végétale, École Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine, Santé et Agroécologie du Vignoble, Biostatistique et processus spatiaux, Biologie et gestion des champignons phytopathogènes
Language: English
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: green
OpenAlex ID: W3157327775