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Optimization of a hyperspectral imaging system for rapid detection of microplastics down to 100 µm
Plastic pollution has become one of the most emergent issues threating aquatic and terrestrial ecosystems. However, it is still challenging to rapidly detect small microplastics. Here, we present a method to rapidly detect microplastics using hyperspectral imaging in which we optimized a commerciall...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7744770/ https://www.ncbi.nlm.nih.gov/pubmed/33354520 http://dx.doi.org/10.1016/j.mex.2020.101175 |
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author | Zhu, Chunmao Kanaya, Yugo Tsuchiya, Masashi Nakajima, Ryota Nomaki, Hidetaka Kitahashi, Tomo Fujikura, Katsunori |
author_facet | Zhu, Chunmao Kanaya, Yugo Tsuchiya, Masashi Nakajima, Ryota Nomaki, Hidetaka Kitahashi, Tomo Fujikura, Katsunori |
author_sort | Zhu, Chunmao |
collection | PubMed |
description | Plastic pollution has become one of the most emergent issues threating aquatic and terrestrial ecosystems. However, it is still challenging to rapidly detect small microplastics. Here, we present a method to rapidly detect microplastics using hyperspectral imaging in which we optimized a commercially available hyperspectral imaging system (Pika NIR-640, Resonon Inc., USA). The optimizations included: (1) changing the four-lamp assembly to a symmetrical set of converged-light near-infrared lamps that are placed sideways instead of above the sample stage; (2) adopting a macro-photography technique by applying an extension tube between the camera and the lens, and moving the lens of the hyperspectral camera to the imaging target (working distance of ~3 cm); (3) adjusting the exposure and aspect ratio by tuning the frame rate and scan speed of the imaging system. After optimization, the detection resolution of each pixel improved from 250 µm to 14.8 µm. With the optimized system, microplastics down to 100 µm in size were rapidly detected. This result is promising for the application of our new method in the accelerated detection of microplastics and will contribute to a better understanding of the microplastic pollution situation. |
format | Online Article Text |
id | pubmed-7744770 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-77447702020-12-21 Optimization of a hyperspectral imaging system for rapid detection of microplastics down to 100 µm Zhu, Chunmao Kanaya, Yugo Tsuchiya, Masashi Nakajima, Ryota Nomaki, Hidetaka Kitahashi, Tomo Fujikura, Katsunori MethodsX Method Article Plastic pollution has become one of the most emergent issues threating aquatic and terrestrial ecosystems. However, it is still challenging to rapidly detect small microplastics. Here, we present a method to rapidly detect microplastics using hyperspectral imaging in which we optimized a commercially available hyperspectral imaging system (Pika NIR-640, Resonon Inc., USA). The optimizations included: (1) changing the four-lamp assembly to a symmetrical set of converged-light near-infrared lamps that are placed sideways instead of above the sample stage; (2) adopting a macro-photography technique by applying an extension tube between the camera and the lens, and moving the lens of the hyperspectral camera to the imaging target (working distance of ~3 cm); (3) adjusting the exposure and aspect ratio by tuning the frame rate and scan speed of the imaging system. After optimization, the detection resolution of each pixel improved from 250 µm to 14.8 µm. With the optimized system, microplastics down to 100 µm in size were rapidly detected. This result is promising for the application of our new method in the accelerated detection of microplastics and will contribute to a better understanding of the microplastic pollution situation. Elsevier 2020-12-08 /pmc/articles/PMC7744770/ /pubmed/33354520 http://dx.doi.org/10.1016/j.mex.2020.101175 Text en © 2020 The Author(s). Published by Elsevier B.V. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Method Article Zhu, Chunmao Kanaya, Yugo Tsuchiya, Masashi Nakajima, Ryota Nomaki, Hidetaka Kitahashi, Tomo Fujikura, Katsunori Optimization of a hyperspectral imaging system for rapid detection of microplastics down to 100 µm |
title | Optimization of a hyperspectral imaging system for rapid detection of microplastics down to 100 µm |
title_full | Optimization of a hyperspectral imaging system for rapid detection of microplastics down to 100 µm |
title_fullStr | Optimization of a hyperspectral imaging system for rapid detection of microplastics down to 100 µm |
title_full_unstemmed | Optimization of a hyperspectral imaging system for rapid detection of microplastics down to 100 µm |
title_short | Optimization of a hyperspectral imaging system for rapid detection of microplastics down to 100 µm |
title_sort | optimization of a hyperspectral imaging system for rapid detection of microplastics down to 100 µm |
topic | Method Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7744770/ https://www.ncbi.nlm.nih.gov/pubmed/33354520 http://dx.doi.org/10.1016/j.mex.2020.101175 |
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