Strawberry powdery mildew (SPM), caused by Podosphaera aphanis, is gaining in importance as production of day-neutral strawberry and resistance to fungicide increase. This disease is difficult to predict because of the wide range of weather conditions favorable to its development. We explored dynamic simulation modelling. The model uses equations developed in-house, published algorithms describing sub-processes of P. aphanis life cycle (e.g. sporulation, conidia germination, leaf colonization) and assembled knowledge of the interactions among the pathogen, host, and weather. Weather, disease, and host data collected at three sites in 2006, 2007, 2008, 2015, 2016 and 2018, for a total of nine epidemics were used to validate the model. The results show a good simulation of the trends, shape and amplitude of SPM severity. The relationship between simulated and observed SPM severity was significant at all sites and years. The proportion of linear variations in the observed SPM explained by the variation in simulated disease severity were between 0.60 and 0.80. Based on receiver operating curve analysis, the model accurately predicted both warning and action thresholds of 5% and 15% disease severity. This is the first model that can quantitatively predict SPM severity, warning and action thresholds to tune fungicide application strategies. In addition, the model can be used to assess the impact of different production systems on powdery mildew and hence anticipate risk.

由Podosphaera aphanis引起的草莓白粉病 (SPM)随着日间中性草莓的生产和对杀菌剂的抗性增加而变得越来越重要。由于有利于其发展的各种天气条件，这种疾病很难预测。我们探索了动态仿真建模。该模型使用内部开发的方程，已发布的算法描述了P. aphanis 的子过程生命周期（例如孢子形成、分生孢子萌发、叶片定植）以及病原体、宿主和天气之间相互作用的综合知识。2006 年、2007 年、2008 年、2015 年、2016 年和 2018 年在三个地点收集的天气、疾病和宿主数据，共九次流行病用于验证模型。结果显示了对 SPM 严重性的趋势、形状和幅度的良好模拟。模拟和观察到的 SPM 严重程度之间的关系在所有地点和年份都显着。由模拟疾病严重程度的变化解释的观察到的 SPM 中线性变化的比例在 0.60 和 0.80 之间。基于接受者操作曲线分析，该模型准确预测了 5% 和 15% 疾病严重程度的警告和行动阈值。这是第一个可以定量预测SPM严重程度的模型，调整杀菌剂应用策略的警告和行动阈值。此外，该模型可用于评估不同生产系统对白粉病的影响，从而预测风险。