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Geostatistical Analysis of the Spatiotemporal Dynamics of Powdery Mildew and Leaf Rust in Wheat

机译:小麦白粉病和叶锈病时空动态的地统计学分析

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Plant diseases are dynamic systems that progress or regress in spatial and temporal dimensions. Site-specific or temporally optimized disease control requires profound knowledge about the development of each stressor. The spatiotemporal dynamics of leaf rust (Puccinia recondite f. sp. tritici) and powdery mildew (Blumeria graminis f. sp. tritici) in wheat was analyzed in order to evaluate typical species-dependent characteristics of disease spread. During two growing seasons, severity data and other relevant plant growth parameters were collected in wheat fields. Spatial characteristics of both diseases were assessed by cluster analyses using spatial analysis by distance indices, whereas the temporal epidemic trends were assessed using statistical parameters. Multivariate statistics were used to identify parameters suitable for characterizing disease trends into four classes of temporal dynamics. The results of the spatial analysis showed that both diseases generally occurred in patches but a differentiation between the diseases by their spatial patterns and spread was not possible. In contrast, temporal characteristics allowed for a differentiation of the diseases, due to the fact that a typical trend was found for leaf rust which differed from the trend of powdery mildew. Therefore, these trends suggested a high potential for temporally optimized disease control. Precise powdery mildew control would be more complicated due to the observed high variability in spatial and temporal dynamics. The general results suggest that, in spite of the high variability in spatiotemporal dynamics, disease control that is optimized in space and time is generally possible but requires consideration of disease- and case-dependent characteristics.
机译:植物病害是在空间和时间维度上进展或消退的动态系统。特定于地点或在时间上进行优化的疾病控制需要有关每个应激源发育的深刻知识。分析了小麦叶锈病(Puccinia recondite f。sp。tritici)和白粉病(Blumeria graminis f。sp。tritici)的时空动态,以评估疾病传播的典型物种依赖性。在两个生长季节中,收集了麦田的严重性数据和其他相关植物生长参数。两种疾病的空间特征均通过聚类分析和距离指数进行空间分析,而时间流行趋势则使用统计参数进行评估。多变量统计用于确定适合于将疾病趋势表征为四类时间动态的参数。空间分析的结果表明,两种疾病通常都发生在斑块中,但是无法通过空间分布和传播来区分疾病。相反,由于发现了叶锈病的典型趋势不同于白粉病的趋势,因此时间特征允许疾病的分化。因此,这些趋势暗示了在时间上优化疾病控制的巨大潜力。由于观察到的时空动态高度可变性,精确的白粉病控制将更加复杂。总体结果表明,尽管时空动态变化很大,但在时空上进行优化的疾病控制通常是可行的,但需要考虑疾病和病例相关的特征。

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