Scale-Dependent Assessment of Relative Disease Resistance to Plant Pathogens

Agronomy

Peter Skelsey¹ 

[1] Information and Computational Sciences, James Hutton Institute, Dundee DD2 5DA, UK; E-Mail:

关键词: simulation model;    crop disease;    spatial heterogeneity;    scale;    partial resistance;    epidemic spread;    dispersal scaling hypothesis;    phenotyping trials;    cultivar selection;   

DOI  :  10.3390/agronomy4020178

来源: mdpi

【 摘 要 】

Phenotyping trials may not take into account sufficient spatial context to infer quantitative disease resistance of recommended varieties in commercial production settings. Recent ecological theory—the dispersal scaling hypothesis—provides evidence that host heterogeneity and scale of host heterogeneity interact in a predictable and straightforward manner to produce a unimodal (“humpbacked”) distribution of epidemic outcomes. This suggests that the intrinsic artificiality (scale and design) of experimental set-ups may lead to spurious conclusions regarding the resistance of selected elite cultivars, due to the failure of experimental efforts to accurately represent disease pressure in real agricultural situations. In this model-based study we investigate the interaction of host heterogeneity and scale as a confounding factor in the inference from ex-situ assessment of quantitative disease resistance to commercial production settings. We use standard modelling approaches in plant disease epidemiology and a number of different agronomic scenarios. Model results revealed that the interaction of heterogeneity and scale is a determinant of relative varietal performance under epidemic conditions. This is a previously unreported phenomenon that could provide a new basis for informing the design of future phenotyping platforms, and optimising the scale at which quantitative disease resistance is assessed.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.