PDF(Pubmed)
Abstract：
Rapid assessment of crop damage is essential for successful management of insect pest outbreaks. In this study, we investigated the use of an unmanned aircraft system (UAS) and image analyses to assess an outbreak of the beet armyworm, Spodoptera exigua (Hübner) (Lepidoptera: Noctuidae), that occurred in soybean fields in South Korea. A rotary-wing UAS was deployed to obtain a series of aerial images over 31 soybean blocks. The images were stitched together to generate composite imagery, followed by image analyses to quantify soybean defoliation. An economic analysis was conducted to compare the cost of the aerial survey with that of a conventional ground survey. The results showed that the aerial survey precisely estimated the defoliation compared to the ground survey, with an estimated defoliation of 78.3% and a range of 22.4-99.8% in the 31 blocks. Moreover, the aerial survey followed by image analyses was found to be more economical than the conventional ground survey when the number of target soybean blocks subject to the survey was more than 15 blocks. Our study clearly demonstrated the effectiveness of using an autonomous UAS and image analysis to conduct a low-cost aerial survey of soybean damage caused by S. exigua outbreaks, which can inform decision-making for S. exigua management.
摘要：
快速评估作物损害对于成功管理虫害暴发至关重要。在这项研究中,我们调查了无人驾驶飞机系统（UAS）和图像分析的使用，以评估甜菜夜蛾的爆发，斜纹夜蛾（Hübner）（鳞翅目：夜蛾科），发生在韩国的大豆田。部署了旋转翼UAS，以在31个大豆块上获得一系列航拍图像。这些图像被拼接在一起以生成合成图像，然后通过图像分析来量化大豆落叶。进行了经济分析，以比较航空勘测与常规地面勘测的成本。结果表明,与地面测量相比,航测精确估计落叶,在31个区块中，估计落叶率为78.3%，范围为22.4-99.8%。此外，当接受调查的目标大豆块数量超过15块时，发现航空调查和图像分析比常规地面调查更经济。OurstudyclearlydemonstratedtheeffectivenessofusinganautonomousUASandimageanalysistoconductalow-costairalsurveyofbeanoydamagecausedbyS.exiguafluenced,这可以为S.exigua管理的决策提供信息。
