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

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 occurr...

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Published inInsects (Basel, Switzerland) Vol. 14; no. 6; p. 555
Main Authors Park, Yong-Lak, Naharki, Kushal, Karimzadeh, Roghaiyeh, Seo, Bo Yoon, Lee, Gwan-Seok
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 15.06.2023
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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.
AbstractList 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.
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.
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.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.
Simple SummaryWhen 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.AbstractRapid 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.
Author Park, Yong-Lak
Lee, Gwan-Seok
Seo, Bo Yoon
Naharki, Kushal
Karimzadeh, Roghaiyeh
AuthorAffiliation 1 Entomology Program, Division of Plant and Soil Sciences, West Virginia University, Morgantown, WV 26506, USA; kn00019@mix.wvu.edu (K.N.); roghaiyeh.karimzadeh@mail.wvu.edu (R.K.)
2 Department of Plant Protection, Faculty of Agriculture, University of Tabriz, Tabriz 5166614888, Iran
3 Crop Foundation Division, National Institute of Crop Science, Rural Development Administration, Wanju 55300, Republic of Korea; seoby@korea.kr
4 Division of Crop Protection, National Institute of Agricultural Sciences, Rural Development Administration, Wanju 55300, Republic of Korea; gslee12@korea.kr
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– name: 3 Crop Foundation Division, National Institute of Crop Science, Rural Development Administration, Wanju 55300, Republic of Korea; seoby@korea.kr
– name: 2 Department of Plant Protection, Faculty of Agriculture, University of Tabriz, Tabriz 5166614888, Iran
– name: 4 Division of Crop Protection, National Institute of Agricultural Sciences, Rural Development Administration, Wanju 55300, Republic of Korea; gslee12@korea.kr
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/37367371$$D View this record in MEDLINE/PubMed
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CitedBy_id crossref_primary_10_1093_jee_toae117
crossref_primary_10_3389_fsufs_2024_1361012
crossref_primary_10_1002_agj2_70004
crossref_primary_10_3390_agriengineering6010034
crossref_primary_10_3390_drones8010001
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Snippet 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...
Simple SummaryWhen an insect pest outbreak occurs, it is crucial to quickly assess the damage to manage the outbreak effectively. This study investigated a...
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StartPage 555
SubjectTerms Aerial surveys
Agricultural economics
Aircraft
Altitude
case studies
Cost analysis
Crop damage
Crops
Damage assessment
Decision making
Defoliation
drone
Drone aircraft
Drones
Economic analysis
Effectiveness
Efficiency
Image analysis
Image processing
insect pests
Insecticides
Insects
Lepidoptera
Low cost
Noctuidae
Outbreaks
pest detection
Pest outbreaks
Pests
Polls & surveys
rapid methods
Remote sensing
SADIE
Satellites
site-specific pest management
South Korea
Soybeans
Spodoptera exigua
Surveys
UAS
unmanned aerial vehicles
Unmanned aircraft
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Title Rapid Assessment of Insect Pest Outbreak Using Drones: A Case Study with Spodoptera exigua (Hübner) (Lepidoptera: Noctuidae) in Soybean Fields
URI https://www.ncbi.nlm.nih.gov/pubmed/37367371
https://www.proquest.com/docview/2829815857
https://www.proquest.com/docview/2830214811
https://www.proquest.com/docview/2942104752
https://pubmed.ncbi.nlm.nih.gov/PMC10299355
https://doaj.org/article/6dbb1457c3e5422d80bd50989cd4d3d0
Volume 14
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