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首页> 外文期刊>Phytopathology >Analysis of Nonlinear Relationships in Dual Epidemics, and Its Application to the Management of Grapevine Downy and Powdery Mildews
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Analysis of Nonlinear Relationships in Dual Epidemics, and Its Application to the Management of Grapevine Downy and Powdery Mildews

机译:双重流行病的非线性关系分析及其在葡萄霜霉病和白粉病管理中的应用

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摘要

Dual epidemics are defined as epidemics developing on two or several plant organs in the course of a cropping season. Agricultural pathosystems where such epidemics develop are often very important, because the harvestable part is one of the organs affected. These epidemics also are often difficult to manage, because the linkage between epidemiological components occurring on different organs is poorly understood, and because prediction of the risk toward the harvestable organs is difficult. In the case of downy mildew (DM) and powdery mildew (PM) of grapevine, nonlinear modeling and logistic regression indicated nonlinearity in the foliage-cluster relationships. Nonlinear modeling enabled the parameterization of a transmission coefficient that numerically links the two components, leaves and clusters, in DM and PM epidemics. Logistic regression analysis yielded a series of probabilistic models that enabled predicting preset levels of cluster infection risks based on DM and PM severities on the foliage at successive crop stages. The usefulness of this framework for tactical decision-making for disease control is discussed.
机译:双重流行病的定义是在一个种植季节期间在两个或几个植物器官上发生的流行病。发生这种流行病的农业病理系统通常非常重要,因为可收获部分是受影响的器官之一。这些流行病通常也很难管理,因为人们对在不同器官上发生的流行病学成分之间的联系了解得很少,并且因为很难预测可收获器官的风险。在葡萄的霜霉病(DM)和白粉病(PM)的情况下,非线性建模和逻辑回归表明叶丛关系中存在非线性。非线性建模可以对传输系数进行参数化,该系数将DM和PM流行中的两个组成部分(叶子和簇)数字化地联系起来。 Logistic回归分析得出了一系列概率模型,这些模型能够根据连续作物阶段叶片上的DM和PM严重程度来预测簇感染风险的预设水平。讨论了该框架对疾病控制战术决策的有用性。

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