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Spatio-temporal analysis of a plant disease in a non-uniform crop: a Monte Carlo approach

机译:不均匀作物中植物病害的时空分析:蒙特卡洛方法

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Identification of the type of disease pattern and spread in a field is critical in epidemiological investigations of plant diseases. For example, an aggregation pattern of infected plants suggests that, at the time of observation, the pathogen is spreading from a proximal source. Conversely, a random pattern suggests a lack of spread from a proximal source. Most of the existing methods of spatial pattern analysis work with only one variety of plant at each location and with uniform genetic disease susceptibility across the field. Pecan orchards, used in this study, and other orchard crops are usually composed of different varieties with different levels of susceptibility to disease. A new measure is suggested to characterize the spatio-temporal transmission patterns of disease; a Monte Carlo test procedure is proposed to test whether the transmission of disease is random or aggregated. In addition, we propose a mixed-transmission model, which allows us to quantify the degree of aggregation effect.
机译:在植物病害流行病学调查中,确定病害类型和在田间传播的类型至关重要。例如,受感染植物的聚集模式表明,在观察时,病原体从近端传播。相反,随机模式表明缺乏来自近端源的扩散。大多数现有的空间格局分析方法只能在每个位置使用一种植物,并且整个田间具有统一的遗传疾病易感性。本研究中使用的山核桃果园和其他果园作物通常由不同品种组成,对疾病的敏感性不同。建议采取一种新措施来表征疾病的时空传播模式。提出了蒙特卡洛测试程序来测试疾病的传播是随机的还是聚集的。此外,我们提出了一种混合传输模型,该模型可以量化聚集效应的程度。

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