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

SIMPLE SUMMARY: When an insect pest outbreak occurs, it is crucial to quickly assess the damage to manage the outbreak effectively. This study investigated a serious outbreak of the beet armyworm, Spodoptera exigua (Hübner) (Lepidoptera: Noctuidae), that occurred in soybean fields in South Korea. We conducted an aerial survey of 31 soybean blocks within the outbreak region using drones. The aerial images were analyzed to quantify soybean defoliation and to investigate the spatial patterns of the soybean damage by S. exigua. The results of this study showed that the aerial survey was an effective and rapid method for estimating the defoliation of soybeans caused by S. exigua. Moreover, it was found that the aerial survey followed by image analysis was more economical and required less time than a conventional ground survey, especially when the number of target soybean blocks subject to the survey was more than 15 blocks. Overall, the study demonstrated the effectiveness of using an autonomous drone and image analysis to conduct a low-cost aerial survey of soybean damage caused by S. exigua during its outbreak. 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.