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Wei Liu, Xueren Cao ,Jieru Fan, Zhenhua Wang, and Zhengyuan Yan, Yong Luo, Jonathan S. West, Xiangming Xu and YilinZhou*. Detecting Wheat Powdery Mildew and Predicting Grain Yield Using Unmanned Aerial Photography. Plant Disease. 2018,102:1981-1988

       点击数: 次      发布时间:2019-01-28

Abstract
    High-resolution aerial imaging with an unmanned aerial vehicle (UAV) was used to quantify wheat powdery mildew and estimate grain yield. Aerial digital images were acquired at Feekes growth stage (GS) 10.5.4 from flight altitudes of 200, 300, and 400 m during the 2009–10 and 2010–11 seasons; and 50, 100, 200, and 300 m during the 2011–12, 2012–13, and 2013–14 seasons. The image parameter lgR was consistently correlated positively with wheat powdery mildew severity and negatively with wheat grain yield for all combinations of flight altitude and year. Fitting the data with random coefficient regression models showed that the exact relationship of lgR with disease severity and grain yield varied considerably from year to year and to a lesser extent with flight altitude within the same year. The present results raise an important question about the consistency of using remote imaging information to estimate disease severity and grain yield. Further research is needed to understand the nature of interyear variability in the relationship of remote imaging data with disease or grain yield. Only then can we determine how the remote imaging tool can be used in commercial agriculture.

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