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Detection of Stress Induced by Soybean Aphid (Hemiptera: Aphididae) Using Multispectral Imagery from Unmanned Aerial Vehicles
Soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae), is a common pest of soybean, Glycine max (L.) Merrill (Fabales: Fabaceae), in North America requiring frequent scouting as part of an integrated pest management plan. Current scouting methods are time consuming and provide incomplete co...
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Published in: | Journal of economic entomology 2020-04, Vol.113 (2), p.779-786 |
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creator | Marston, Zachary P. D Cira, Theresa M Hodgson, Erin W Knight, Joseph F MacRae, Ian V Koch, Robert L |
description | Soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae), is a common pest of soybean, Glycine max (L.) Merrill (Fabales: Fabaceae), in North America requiring frequent scouting as part of an integrated pest management plan. Current scouting methods are time consuming and provide incomplete coverage of soybean. Unmanned aerial vehicles (UAVs) are capable of collecting high-resolution imagery that offer more detailed coverage in agricultural fields than traditional scouting methods. Recently, it was documented that changes to the spectral reflectance of soybean canopies caused by aphid-induced stress could be detected from ground-based sensors; however, it remained unknown whether these changes could also be detected from UAV-based sensors. Small-plot trials were conducted in 2017 and 2018 where cages were used to manipulate aphid populations. Additional open-field trials were conducted in 2018 where insecticides were used to create a gradient of aphid pressure. Whole-plant soybean aphid densities were recorded along with UAV-based multispectral imagery. Simple linear regressions were used to determine whether UAV-based multispectral reflectance was associated with aphid populations. Our findings indicate that near-infrared reflectance decreased with increasing soybean aphid populations in caged trials when cumulative aphid days surpassed the economic injury level, and in open-field trials when soybean aphid populations were above the economic threshold. These findings provide the first documentation of soybean aphid-induced stress being detected from UAV-based multispectral imagery and advance the use of UAVs for remote scouting of soybean aphid and other field crop pests. |
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D ; Cira, Theresa M ; Hodgson, Erin W ; Knight, Joseph F ; MacRae, Ian V ; Koch, Robert L</creator><contributor>Rondon, Silvia</contributor><creatorcontrib>Marston, Zachary P. D ; Cira, Theresa M ; Hodgson, Erin W ; Knight, Joseph F ; MacRae, Ian V ; Koch, Robert L ; Rondon, Silvia</creatorcontrib><description>Soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae), is a common pest of soybean, Glycine max (L.) Merrill (Fabales: Fabaceae), in North America requiring frequent scouting as part of an integrated pest management plan. Current scouting methods are time consuming and provide incomplete coverage of soybean. Unmanned aerial vehicles (UAVs) are capable of collecting high-resolution imagery that offer more detailed coverage in agricultural fields than traditional scouting methods. Recently, it was documented that changes to the spectral reflectance of soybean canopies caused by aphid-induced stress could be detected from ground-based sensors; however, it remained unknown whether these changes could also be detected from UAV-based sensors. Small-plot trials were conducted in 2017 and 2018 where cages were used to manipulate aphid populations. Additional open-field trials were conducted in 2018 where insecticides were used to create a gradient of aphid pressure. Whole-plant soybean aphid densities were recorded along with UAV-based multispectral imagery. Simple linear regressions were used to determine whether UAV-based multispectral reflectance was associated with aphid populations. Our findings indicate that near-infrared reflectance decreased with increasing soybean aphid populations in caged trials when cumulative aphid days surpassed the economic injury level, and in open-field trials when soybean aphid populations were above the economic threshold. These findings provide the first documentation of soybean aphid-induced stress being detected from UAV-based multispectral imagery and advance the use of UAVs for remote scouting of soybean aphid and other field crop pests.</description><identifier>ISSN: 0022-0493</identifier><identifier>EISSN: 1938-291X</identifier><identifier>DOI: 10.1093/jee/toz306</identifier><identifier>PMID: 31782504</identifier><language>eng</language><publisher>US: Entomological Society of America</publisher><subject>Agricultural chemicals industry ; Agricultural land ; Agricultural pests ; Agricultural practices ; Animals ; Aphididae ; Aphids ; Aphis glycines ; crop scouting ; Drone aircraft ; Economics ; FIELD AND FORAGE CROPS ; Glycine max ; Hemiptera ; Insecticides ; Integrated pest management ; Linear Models ; multispectral ; North America ; Pest control ; Pests ; Reflectance ; Remote sensing ; Sensors ; Soybean ; Soybeans ; unmanned aerial vehicle ; Unmanned aerial vehicles</subject><ispartof>Journal of economic entomology, 2020-04, Vol.113 (2), p.779-786</ispartof><rights>The Author(s) 2019. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. journals.permissions@oup.com</rights><rights>The Author(s) 2019. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. 2019</rights><rights>The Author(s) 2019. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. 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Recently, it was documented that changes to the spectral reflectance of soybean canopies caused by aphid-induced stress could be detected from ground-based sensors; however, it remained unknown whether these changes could also be detected from UAV-based sensors. Small-plot trials were conducted in 2017 and 2018 where cages were used to manipulate aphid populations. Additional open-field trials were conducted in 2018 where insecticides were used to create a gradient of aphid pressure. Whole-plant soybean aphid densities were recorded along with UAV-based multispectral imagery. Simple linear regressions were used to determine whether UAV-based multispectral reflectance was associated with aphid populations. Our findings indicate that near-infrared reflectance decreased with increasing soybean aphid populations in caged trials when cumulative aphid days surpassed the economic injury level, and in open-field trials when soybean aphid populations were above the economic threshold. 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D</au><au>Cira, Theresa M</au><au>Hodgson, Erin W</au><au>Knight, Joseph F</au><au>MacRae, Ian V</au><au>Koch, Robert L</au><au>Rondon, Silvia</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Detection of Stress Induced by Soybean Aphid (Hemiptera: Aphididae) Using Multispectral Imagery from Unmanned Aerial Vehicles</atitle><jtitle>Journal of economic entomology</jtitle><addtitle>J Econ Entomol</addtitle><date>2020-04-06</date><risdate>2020</risdate><volume>113</volume><issue>2</issue><spage>779</spage><epage>786</epage><pages>779-786</pages><issn>0022-0493</issn><eissn>1938-291X</eissn><abstract>Soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae), is a common pest of soybean, Glycine max (L.) Merrill (Fabales: Fabaceae), in North America requiring frequent scouting as part of an integrated pest management plan. Current scouting methods are time consuming and provide incomplete coverage of soybean. Unmanned aerial vehicles (UAVs) are capable of collecting high-resolution imagery that offer more detailed coverage in agricultural fields than traditional scouting methods. Recently, it was documented that changes to the spectral reflectance of soybean canopies caused by aphid-induced stress could be detected from ground-based sensors; however, it remained unknown whether these changes could also be detected from UAV-based sensors. Small-plot trials were conducted in 2017 and 2018 where cages were used to manipulate aphid populations. Additional open-field trials were conducted in 2018 where insecticides were used to create a gradient of aphid pressure. Whole-plant soybean aphid densities were recorded along with UAV-based multispectral imagery. Simple linear regressions were used to determine whether UAV-based multispectral reflectance was associated with aphid populations. Our findings indicate that near-infrared reflectance decreased with increasing soybean aphid populations in caged trials when cumulative aphid days surpassed the economic injury level, and in open-field trials when soybean aphid populations were above the economic threshold. These findings provide the first documentation of soybean aphid-induced stress being detected from UAV-based multispectral imagery and advance the use of UAVs for remote scouting of soybean aphid and other field crop pests.</abstract><cop>US</cop><pub>Entomological Society of America</pub><pmid>31782504</pmid><doi>10.1093/jee/toz306</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0001-8038-5200</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Agricultural chemicals industry Agricultural land Agricultural pests Agricultural practices Animals Aphididae Aphids Aphis glycines crop scouting Drone aircraft Economics FIELD AND FORAGE CROPS Glycine max Hemiptera Insecticides Integrated pest management Linear Models multispectral North America Pest control Pests Reflectance Remote sensing Sensors Soybean Soybeans unmanned aerial vehicle Unmanned aerial vehicles |
title | Detection of Stress Induced by Soybean Aphid (Hemiptera: Aphididae) Using Multispectral Imagery from Unmanned Aerial Vehicles |
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