Phytopathology. 1999 Nov;89(11):984-90. doi: 10.1094/PHYTO.1999.89.11.984.
ABSTRACT Although plant disease epidemiology has focused on populations in which all host plants have the same genotype, mixtures of host genotypes are more typical of natural populations and offer promising options for deployment of resistance genes in agriculture. In this review, we discuss Leonard's classic model of the effects of host genotype diversity on disease and its predictions of disease level based on the proportion of susceptible host tissue. As a refinement to Leonard's model, the spatial structure of host and pathogen population can be taken into account by considering factors such as autoinfection, interaction between host size and pathogen dispersal gradients, lesion expansion, and host carrying capacity for disease. The genetic composition of the host population also can be taken into account by considering differences in race-specific resistance among host genotypes, compensation, plant competition, and competitive interactions among pathogen genotypes. The magnitude of host-diversity effects for particular host-pathogen systems can be predicted by considering how the inherent characteristics of a system causes it to differ from the assumptions of the classic model. Because of the limited number of studies comparing host-diversity effects in different systems, it is difficult at this point to make more than qualitative predictions. Environmental conditions and management decisions also influence host-diversity effects on disease through their effect on factors such as host density and epidemic length and intensity.
摘要 尽管植物病害流行病学主要集中在所有宿主植物具有相同基因型的群体中,但宿主基因型的混合更为常见于自然种群,并为农业中抗性基因的部署提供了有前景的选择。在这篇综述中,我们讨论了 Leonard 经典的宿主基因型多样性对疾病影响的模型及其基于易感性宿主组织比例的疾病水平预测。作为对 Leonard 模型的改进,可以通过考虑自感染、宿主大小与病原体扩散梯度之间的相互作用、病变扩展以及宿主对疾病的承载能力等因素,考虑宿主和病原体种群的空间结构。还可以通过考虑宿主基因型之间的特定抗性、补偿、植物竞争以及病原体基因型之间的竞争相互作用等因素,考虑宿主群体的遗传组成。通过考虑系统的固有特征如何使其与经典模型的假设不同,可以预测特定宿主-病原体系统中宿主多样性效应的大小。由于比较不同系统中宿主多样性效应的研究数量有限,目前很难做出更定性的预测。环境条件和管理决策也通过影响宿主密度和流行长度和强度等因素,对疾病的宿主多样性效应产生影响。