Optimized imaging methods for species-level identification of food-contaminating beetles

Abstract Identifying the exact species of pantry beetle responsible for food contamination, is imperative in assessing the risks associated with contamination scenarios. Each beetle species is known to have unique patterns on their hardened forewings (known as elytra) through which they can be ident...

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Autores principales:	Tanmay Bera, Leihong Wu, Hongjian Ding, Howard Semey, Amy Barnes, Zhichao Liu, Himansu Vyas, Weida Tong, Joshua Xu
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/9cbdaa038c854abbb39ea8b2d75dbd5f
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spelling	oai:doaj.org-article:9cbdaa038c854abbb39ea8b2d75dbd5f2021-12-02T15:51:15ZOptimized imaging methods for species-level identification of food-contaminating beetles10.1038/s41598-021-86643-y2045-2322https://doaj.org/article/9cbdaa038c854abbb39ea8b2d75dbd5f2021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-86643-yhttps://doaj.org/toc/2045-2322Abstract Identifying the exact species of pantry beetle responsible for food contamination, is imperative in assessing the risks associated with contamination scenarios. Each beetle species is known to have unique patterns on their hardened forewings (known as elytra) through which they can be identified. Currently, this is done through manual microanalysis of the insect or their fragments in contaminated food samples. We envision that the use of automated pattern analysis would expedite and scale up the identification process. However, such automation would require images to be captured in a consistent manner, thereby enabling the creation of large repositories of high-quality images. Presently, there is no standard imaging technique for capturing images of beetle elytra, which consequently means, there is no standard method of beetle species identification through elytral pattern analysis. This deficiency inspired us to optimize and standardize imaging methods, especially for food-contaminating beetles. For this endeavor, we chose multiple species of beetles belonging to different families or genera that have near-identical elytral patterns, and thus are difficult to identify correctly at the species level. Our optimized imaging method provides enhanced images such that the elytral patterns between individual species could easily be distinguished from each other, through visual observation. We believe such standardization is critical in developing automated species identification of pantry beetles and/or other insects. This eventually may lead to improved taxonomical classification, allowing for better management of food contamination and ecological conservation.Tanmay BeraLeihong WuHongjian DingHoward SemeyAmy BarnesZhichao LiuHimansu VyasWeida TongJoshua XuNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Tanmay Bera Leihong Wu Hongjian Ding Howard Semey Amy Barnes Zhichao Liu Himansu Vyas Weida Tong Joshua Xu Optimized imaging methods for species-level identification of food-contaminating beetles
description	Abstract Identifying the exact species of pantry beetle responsible for food contamination, is imperative in assessing the risks associated with contamination scenarios. Each beetle species is known to have unique patterns on their hardened forewings (known as elytra) through which they can be identified. Currently, this is done through manual microanalysis of the insect or their fragments in contaminated food samples. We envision that the use of automated pattern analysis would expedite and scale up the identification process. However, such automation would require images to be captured in a consistent manner, thereby enabling the creation of large repositories of high-quality images. Presently, there is no standard imaging technique for capturing images of beetle elytra, which consequently means, there is no standard method of beetle species identification through elytral pattern analysis. This deficiency inspired us to optimize and standardize imaging methods, especially for food-contaminating beetles. For this endeavor, we chose multiple species of beetles belonging to different families or genera that have near-identical elytral patterns, and thus are difficult to identify correctly at the species level. Our optimized imaging method provides enhanced images such that the elytral patterns between individual species could easily be distinguished from each other, through visual observation. We believe such standardization is critical in developing automated species identification of pantry beetles and/or other insects. This eventually may lead to improved taxonomical classification, allowing for better management of food contamination and ecological conservation.
format	article
author	Tanmay Bera Leihong Wu Hongjian Ding Howard Semey Amy Barnes Zhichao Liu Himansu Vyas Weida Tong Joshua Xu
author_facet	Tanmay Bera Leihong Wu Hongjian Ding Howard Semey Amy Barnes Zhichao Liu Himansu Vyas Weida Tong Joshua Xu
author_sort	Tanmay Bera
title	Optimized imaging methods for species-level identification of food-contaminating beetles
title_short	Optimized imaging methods for species-level identification of food-contaminating beetles
title_full	Optimized imaging methods for species-level identification of food-contaminating beetles
title_fullStr	Optimized imaging methods for species-level identification of food-contaminating beetles
title_full_unstemmed	Optimized imaging methods for species-level identification of food-contaminating beetles
title_sort	optimized imaging methods for species-level identification of food-contaminating beetles
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/9cbdaa038c854abbb39ea8b2d75dbd5f
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Optimized imaging methods for species-level identification of food-contaminating beetles

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