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专刊:用无人机改善虫害管理

A Special Collection: Drones to Improve Insect Pest Management.

机构信息

M3 Consulting Group, LLC., Dayton, OH, USA.

Texas A&M AgriLife Research, Department of Entomology, Corpus Christi, TX 78406, USA.

出版信息

J Econ Entomol. 2021 Oct 13;114(5):1853-1856. doi: 10.1093/jee/toab081.

Abstract

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.

摘要

《利用无人机改善虫害管理的特刊》介绍了无人飞行器系统(UAS,即无人机)技术的研究与开发,以改善虫害管理。这些文章涵盖了从更基础的研究(例如,评估和改进无人机探测虫害问题或施用药剂的能力)到面向应用的案例研究(例如,评估无人机在虫害管理系统中的应用机会和挑战)。本特刊由首次发表的文章和之前在《经济昆虫学杂志》(JEE)上发表的精选文章组成。特刊中的文章以及其他出版物中引用的精选文章反映了在无人机结构和软件工程(如自主飞行制导、飞行前后数据存储和处理)方面的进步的刺激下,昆虫学领域利用无人机开展研究的增加,以及空间数据管理和分析方面的相关进展,包括机器学习和数据可视化。本特刊还旨在激发关于 JEE 作为未来有关无人机和其他控制物理系统、大数据分析和深度学习过程的文章的出版场所的作用的讨论。虽然这些技术起源于可能远离昆虫学领域的领域,但我们认为,跨学科合作是应用研究和技术转让的途径,可加速这些技术的研发,以改善虫害管理。

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