A Special Collection: Drones to Improve Insect Pest Management

The Special Collection Drones to Improve Insect Pest Management presents research and development of unmanned (or uncrewed) aircraft system (UAS, or drone) technology to improve insect pest management. The articles bridge from more foundational studies (i.e., evaluating and refining abilities of dro...

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Veröffentlicht in:Journal of economic entomology 2021-10, Vol.114 (5), p.1853-1856
Hauptverfasser: Moses-Gonzales, Nathan, Brewer, Michael J
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container_title Journal of economic entomology
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creator Moses-Gonzales, Nathan
Brewer, Michael J
description The Special Collection Drones to Improve Insect Pest Management presents research and development of unmanned (or uncrewed) aircraft system (UAS, or drone) technology to improve insect pest management. The articles bridge from more foundational studies (i.e., evaluating and refining abilities of drones to detect pest concerns or deliver pest management materials) to application-oriented case studies (i.e., evaluating opportunities and challenges of drone use in pest management systems). The collection is composed of a combination of articles presenting information first-time published, and a selection of articles previously published in Journal of Economic Entomology (JEE). Articles in the Collection, as well as selected citations of articles in other publications, reflect the increase in entomology research using drones that has been stimulated by advancement in drone structural and software engineering such as autonomous flight guidance; in- and post-flight data storage and processing; and companion advances in spatial data management and analyses including machine learning and data visualization. The Collection is also intended to stimulate discussion on the role of JEE as a publication venue for future articles on drones as well as other cybernectic-physical systems, big data analyses, and deep learning processes. While these technologies have their genesis in fields arguably afar from the discipline of entomology, we propose that interdisciplinary collaboration is the pathway for applications research and technology transfer leading to an acceleration of research and development of these technologies to improve pest management.
doi_str_mv 10.1093/jee/toab081
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The articles bridge from more foundational studies (i.e., evaluating and refining abilities of drones to detect pest concerns or deliver pest management materials) to application-oriented case studies (i.e., evaluating opportunities and challenges of drone use in pest management systems). The collection is composed of a combination of articles presenting information first-time published, and a selection of articles previously published in Journal of Economic Entomology (JEE). Articles in the Collection, as well as selected citations of articles in other publications, reflect the increase in entomology research using drones that has been stimulated by advancement in drone structural and software engineering such as autonomous flight guidance; in- and post-flight data storage and processing; and companion advances in spatial data management and analyses including machine learning and data visualization. The Collection is also intended to stimulate discussion on the role of JEE as a publication venue for future articles on drones as well as other cybernectic-physical systems, big data analyses, and deep learning processes. While these technologies have their genesis in fields arguably afar from the discipline of entomology, we propose that interdisciplinary collaboration is the pathway for applications research and technology transfer leading to an acceleration of research and development of these technologies to improve pest management.</description><identifier>ISSN: 0022-0493</identifier><identifier>EISSN: 1938-291X</identifier><identifier>DOI: 10.1093/jee/toab081</identifier><language>eng</language><publisher>US: Entomological Society of America</publisher><subject>actuation drones ; Biological control ; Case studies ; Data management ; Data storage ; Deep learning ; Drones ; Entomology ; Flight ; Geospatial data ; Imaging systems ; Industrial research ; Information storage and retrieval ; insect pest management ; Insect pests ; Insects ; Learning algorithms ; Machine learning ; Pest control ; Pests ; R&amp;D ; Research &amp; development ; Spatial analysis ; spectral imaging technology ; Technology transfer ; unmanned aerial system</subject><ispartof>Journal of economic entomology, 2021-10, Vol.114 (5), p.1853-1856</ispartof><rights>The Author(s) 2021. 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) 2021. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. 2021</rights><rights>COPYRIGHT 2021 Oxford University Press</rights><rights>The Author(s) 2021. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. 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source Oxford University Press Journals All Titles (1996-Current); Alma/SFX Local Collection
subjects actuation drones
Biological control
Case studies
Data management
Data storage
Deep learning
Drones
Entomology
Flight
Geospatial data
Imaging systems
Industrial research
Information storage and retrieval
insect pest management
Insect pests
Insects
Learning algorithms
Machine learning
Pest control
Pests
R&D
Research & development
Spatial analysis
spectral imaging technology
Technology transfer
unmanned aerial system
title A Special Collection: Drones to Improve Insect Pest Management
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