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利用无人机快速评估害虫爆发情况:以大豆田中的(胡伯纳)(鳞翅目:夜蛾科)为例

Rapid Assessment of Insect Pest Outbreak Using Drones: A Case Study with (Hübner) (Lepidoptera: Noctuidae) in Soybean Fields.

作者信息

Park Yong-Lak, Naharki Kushal, Karimzadeh Roghaiyeh, Seo Bo Yoon, Lee Gwan-Seok

机构信息

Entomology Program, Division of Plant and Soil Sciences, West Virginia University, Morgantown, WV 26506, USA.

Department of Plant Protection, Faculty of Agriculture, University of Tabriz, Tabriz 5166614888, Iran.

出版信息

Insects. 2023 Jun 15;14(6):555. doi: 10.3390/insects14060555.

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, (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 outbreaks, which can inform decision-making for management.

摘要

快速评估作物损害对于成功管理害虫爆发至关重要。在本研究中,我们调查了使用无人机系统(UAS)和图像分析来评估韩国大豆田爆发的甜菜夜蛾Spodoptera exigua (Hübner)(鳞翅目:夜蛾科)。部署了旋翼无人机系统以获取31个大豆地块的一系列航拍图像。将这些图像拼接在一起以生成合成图像,然后进行图像分析以量化大豆的落叶情况。进行了经济分析,以比较航空调查与传统地面调查的成本。结果表明,与地面调查相比,航空调查能更精确地估计落叶情况,在31个地块中,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地块数量超过15个时,通过图像分析的航空调查比传统地面调查更经济。我们的研究清楚地证明了使用自主无人机系统和图像分析对甜菜夜蛾爆发造成的大豆损害进行低成本航空调查的有效性,这可为害虫管理决策提供依据。

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