Detecting Wheat Powdery Mildew and Predicting Grain Yield Using Unmanned Aerial Photography
Detecting Wheat Powdery Mildew and Predicting Grain Yield Using Unmanned Aerial Photography
复制标题
利用无人机摄影检测小麦白粉病并预测粮食产量
DOI：
10.1094/pdis-12-17-1893-re
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发表时间：
2018-10-01
期刊：
影响因子：
4.5
通讯作者：
Zhou, Yilin
中科院分区：
文献类型：
--
作者：
Liu, Wei;Cao, Xueren;Zhou, Yilin
利用无人机的高分辨率航空成像技术对小麦白粉病进行了定量研究，并估算了小麦产量。航空数字图像是在费克斯生长阶段(GS)10.5.4获得的，飞行高度在2009-10和2010-11赛季期间为200、300和400米；在2011-12、2012-13和2013-14赛季期间为50、100、200和300米。在所有飞行高度和年份组合中，图像参数LGR与小麦白粉病严重程度一致呈正相关，与小麦籽粒产量呈负相关。用随机系数回归模型对数据进行了拟合，结果表明，LGR与病情严重程度和粮食产量的关系年际间差异较大，与当年飞行高度的关系较小。目前的结果提出了一个重要的问题，即利用遥感图像信息来估计病情严重程度和粮食产量的一致性。还需要进一步研究，以了解遥感成像数据与疾病或粮食产量之间关系的年际变异性的性质。只有到那时，我们才能确定远程成像工具如何用于商业农业。
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.