Data from: Development and validation of a weather-based warning system to advise fungicide applications to control dollar spot on turfgrass

Dollar spot is one of the most common diseases of golf course turfgrass
and numerous fungicide applications are often required to provide adequate
control. Weather-based disease warning systems have been developed to more
accurately time fungicide applications; however, they tend to be
ineffective and are not currently in widespread use. The primary objective
of this research was to develop a new weather-based disease warning system
to more accurately advise fungicide applications to control dollar spot
activity across a broad geographic and climactic range. The new dollar
spot warning system was developed from data collected at field sites in
Madison, WI and Stillwater, OK in 2008 and warning system validation sites
were established in Madison, WI, Stillwater, OK, Knoxville, TN, State
College, PA, Starkville, MS, and Storrs, CT between 2011 and 2016. A
meta-analysis of all site-years was conducted and the most effective
warning system for dollar spot development consisted of a five-day moving
average of relative humidity and average daily temperature. Using this
model the highest effective probability that provided dollar spot control
similar to that of a calendar-based program across the numerous sites and
years was 20%. Additional analysis found that the 20% spray threshold
provided comparable control to the calendar-based program while reducing
fungicide usage by up to 30%, though further refinement may be needed as
practitioners implement this warning system in a range of environments not
tested here. The weather-based dollar spot warning system presented here
will likely become an important tool for implementing precision disease
management strategies for future turfgrass managers, especially as
financial and regulatory pressures increase the need to reduce pesticide
usage on golf course turfgrass.

币斑病（dollar spot）是高尔夫球场草坪最常见的病害之一，通常需要多次施用杀菌剂才能获得足够的防治效果。基于气象的病害预警系统（weather-based disease warning system）已被开发用于更精准地确定杀菌剂施用时机，但这类系统往往效果不佳，目前尚未得到广泛应用。本研究的核心目标是开发一款新型基于气象的病害预警系统，以在更广泛的地理与气候范围内，更精准地指导杀菌剂施用，从而防控币斑病的发生。新型币斑病预警系统基于2008年在美国威斯康星州麦迪逊市（Madison, WI）与俄克拉荷马州斯蒂尔沃特市（Stillwater, OK）的田间试验数据开发；预警系统的验证站点于2011至2016年间分别设立于威斯康星州麦迪逊市、俄克拉荷马州斯蒂尔沃特市、田纳西州诺克斯维尔市（Knoxville, TN）、宾夕法尼亚州州学院（State College, PA）、密西西比州斯塔克维尔市（Starkville, MS）以及康涅狄格州斯托尔斯市（Storrs, CT）。本研究对所有试验位点与年份的数据开展了荟萃分析（meta-analysis），结果显示，用于预测币斑病发生的最优预警系统基于相对湿度与日平均温度的5日滑动平均值构建。采用该模型时，能实现与常规基于日历的施药方案相当的币斑病防治效果的最高有效概率阈值为20%。进一步分析表明，20%的喷施阈值可在将杀菌剂施用量降低至多30%的同时，实现与常规日历施药方案相当的防治效果；不过当植保从业者在本研究未覆盖的环境中应用该预警系统时，可能仍需对其做进一步优化。本研究提出的基于气象的币斑病预警系统，有望成为未来草坪管理者实施精准病害管理策略的重要工具，尤其是在当前财政与监管压力日益增大、高尔夫球场草坪农药减量需求不断提升的背景下。