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Obtaining weather data for input to crop disease-warning systems: leaf wetness duration as a case study

机译:获取天气数据以输入农作物疾病预警系统:以叶片湿润持续时间为例

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Disease-warning systems are decision support tools designed to help growers determine when to apply control measures to suppress crop diseases. Weather data are nearly ubiquitous inputs to warning systems. This contribution reviews ways in which weather data are gathered for use as inputs to disease-warning systems, and the associated logistical challenges. Grower-operated weather monitoring is contrasted with obtaining data from networks of weather stations, and the advantages and disadvantages of measuring vs. estimating weather data are discussed. Special emphasis is given to leaf wetness duration (LWD), not only because LWD data are inputs to many disease-warning systems but also because accurate data are uniquely challenging to obtain. It is concluded that there is no single " best" method to acquire weather data for use in disease-warning systems; instead, local, regional, and national circumstances are likely to influence which strategy is most successful.
机译:疾病预警系统是决策支持工具,旨在帮助种植者确定何时采取控制措施来抑制农作物疾病。气象数据几乎是警报系统的普遍输入。该文稿回顾了收集天气数据以用作疾病预警系统的输入的方式,以及相关的后勤挑战。种植者操作的天气监视与从气象站网络获取数据形成对比,并讨论了测量与估计天气数据的优缺点。尤其要注意叶片的湿润持续时间(LWD),这不仅是因为LWD数据是许多疾病预警系统的输入,而且因为准确的数据很难获得。结论是,没有单一的“最佳”方法来获取用于疾病预警系统的天气数据。相反,当地,地区和国家的情况可能会影响哪种策略最成功。

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