Advances in automatic identifcation of fying insects using optical sensors and machine learning

A - Papers appearing in refereed journals

Kirkeby, C, Rydhmer, K, Cook, S. M., Strand, A, Torrance, M. T., Swain, J. L., Prangsma, J, Johnen, A, Jensen, M, Brydegaard, M and Graesboll, K 2021. Advances in automatic identifcation of fying insects using optical sensors and machine learning. Scientific Reports. 11 (1), pp. 1-8. https://doi.org/10.1038/s41598-021-81005-0

AuthorsKirkeby, C, Rydhmer, K, Cook, S. M., Strand, A, Torrance, M. T., Swain, J. L., Prangsma, J, Johnen, A, Jensen, M, Brydegaard, M and Graesboll, K
Abstract

Worldwide, farmers use insecticides to prevent crop damage caused by insect pests, while they also rely on insect pollinators to enhance crop yield and other insect as natural enemies of pests. In order to target pesticides to pests only, farmers must know exactly where and when pests and beneficial insects are present in the field. A promising solution to this problem could be optical sensors combined with machine learning. We obtained around 10,000 records of flying insects found in oilseed rape (Brassica napus) crops, using an optical remote sensor and evaluated three different classification methods for the obtained signals, reaching over 80% accuracy. We demonstrate that it is possible
to classify insects in fight, making it possible to optimize the application of insecticides in space and time. This will enable a technological leap in precision agriculture, where focus on prudent and environmentally-sensitive use of pesticides is a top priority.

KeywordsMachine learning; AI; Optical sensors; Oilseed rape; Monitoring ; Sustainable agriculture; Insect pest management
Year of Publication2021
JournalScientific Reports
Journal citation11 (1), pp. 1-8
Digital Object Identifier (DOI)https://doi.org/10.1038/s41598-021-81005-0
Web address (URL)https://doi.org/10.1038/s41598-021-81005-0
Open accessPublished as ‘gold’ (paid) open access
FunderBASF
Publisher's version
Output statusPublished
Publication dates
Online15 Jan 2021
Publication process dates
Accepted29 Dec 2020
PublisherNature Publishing Group
ISSN2045-2322

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