INRA, UMR 1402 ECOSYS, F-78850 Thiverval-Grignon, France.
ITK, avenue de l'Europe, Clapiers, France.
Ann Bot. 2018 Apr 18;121(5):975-989. doi: 10.1093/aob/mcx192.
In order to optimize crop management in innovative agricultural production systems, it is crucial to better understand how plant disease epidemics develop and what factors influence them. This study explores how canopy growth, its spatial organization and leaf senescence impact Zymoseptoria tritici epidemics.
We used the Septo3D model, an epidemic model of Septoria tritici blotch (STB) coupled with a 3-D virtual wheat structural plant model (SPM). The model was calibrated and evaluated against field experimental data. Sensitivity analyses were performed on the model to explore how wheat plant traits impact the interaction between wheat growth and Z. tritici epidemics.
The model reproduces consistently the effects of crop architecture and weather on STB progress on the upper leaves. Model sensitivity analyses show that the effects of plant traits on epidemics depended on weather conditions. The simulations confirm the known effect of increased stem height and stem elongation rate on limiting STB progress on upper leaves. Strikingly, the timing of leaf senescence is one of the most influential traits on simulated STB epidemics. When the green life span duration of leaves is reduced by early senescence, epidemics are strongly reduced.
We introduce the notion of a 'race' for the colonization of emerging healthy host tissue between the growing canopy and the developing epidemics. This race is 2-fold: (1) an upward race at the canopy scale where STB must catch the newly emerging leaves before they grow away from the spore sources; and (2) a local race at the leaf scale where STB must use the resources of its host before it is caught by leaf apical senescence. The results shed new light on the importance of dynamic interactions between host and pathogen.
为了优化创新农业生产系统中的作物管理,更好地了解植物病害流行的发展方式以及影响因素至关重要。本研究探讨了冠层生长、其空间组织和叶片衰老如何影响叶枯病菌流行。
我们使用了 Septo3D 模型,这是一种与三维虚拟小麦结构植物模型(SPM)耦合的叶枯病条斑(STB)流行模型。对模型进行了校准和评估,以验证其对田间实验数据的拟合程度。对模型进行了敏感性分析,以探讨小麦植株特征如何影响小麦生长与叶枯病菌相互作用。
该模型一致再现了作物结构和天气对小麦上部叶片上 STB 进展的影响。模型敏感性分析表明,植株特征对流行的影响取决于天气条件。模拟结果证实了茎高和茎伸长率增加对限制上部叶片 STB 流行的已知影响。引人注目的是,叶片衰老时间是对模拟叶枯病流行影响最大的特征之一。当叶片的绿色寿命缩短导致早期衰老时,流行会大大减少。
我们引入了一个概念,即“竞争”,用于在生长的冠层和发展中的流行之间争夺对新出现的健康宿主组织的定殖。这种竞争有两个方面:(1)在冠层尺度上的向上竞争,其中 STB 必须在新出现的叶片长到远离孢子源的位置之前赶上它们;(2)在叶片尺度上的局部竞争,其中 STB 必须在被叶片顶端衰老捕获之前利用宿主的资源。研究结果揭示了宿主与病原体之间动态相互作用的重要性。