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Image processing tools in the study of environmental contamination by microplastics: reliability and perspectives
Microplastic pollution is one of the greatest environmental concerns for contemporary times and the future. In the last years, the number of publications about microplastic contamination has increased rapidly and the list is daily updated. However, the lack of standard analytical approaches might ge...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9813107/ https://www.ncbi.nlm.nih.gov/pubmed/35902515 http://dx.doi.org/10.1007/s11356-022-22128-3 |
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author | Valente, Tommaso Ventura, Daniele Matiddi, Marco Sbrana, Alice Silvestri, Cecilia Piermarini, Raffaella Jacomini, Carlo Costantini, Maria Letizia |
author_facet | Valente, Tommaso Ventura, Daniele Matiddi, Marco Sbrana, Alice Silvestri, Cecilia Piermarini, Raffaella Jacomini, Carlo Costantini, Maria Letizia |
author_sort | Valente, Tommaso |
collection | PubMed |
description | Microplastic pollution is one of the greatest environmental concerns for contemporary times and the future. In the last years, the number of publications about microplastic contamination has increased rapidly and the list is daily updated. However, the lack of standard analytical approaches might generate data inconsistencies, reducing the comparability among different studies. The present study investigates the potential of two image processing tools (namely the shapeR package for R and ImageJ 1.52v) in providing an accurate characterization of the shape of microplastics using a restricted set of shape descriptors. To ascertain that the selected tools can measure small shape differences, we perform an experiment to verify the detection of pre-post variations in the shape of different microplastic types (i.e., nylon [NY], polyethylene [PE], polyethylene terephthalate [PET], polypropylene [PP], polystyrene [PS], and polyvinylchloride [PVC]) treated with mildly corrosive chemicals (i.e., 10% KOH at 60 °C, 30% H(2)O(2) at 50 °C, and 15% H(2)O(2) + 5% HNO(3) at 40 °C; incubation time ≈ 12 h). Analysis of surface area variations returns results about the vulnerability of plastic polymers to digestive solutions that are aligned with most of the acquired knowledge. The largest decrease in surface area occurs for KOH-treated PET particles, while NY results in the most susceptible polymer to the 30% H(2)O(2) treatment, followed by PVC and PS. PE and PP are the most resistant polymers to all the used treatments. The adopted methods to characterize microplastics seem reliable tools for detecting small differences in the shape and size of these particles. Then, the analytic perspectives that can be developed using such widely accessible and low-cost equipment are discussed. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11356-022-22128-3. |
format | Online Article Text |
id | pubmed-9813107 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-98131072023-01-06 Image processing tools in the study of environmental contamination by microplastics: reliability and perspectives Valente, Tommaso Ventura, Daniele Matiddi, Marco Sbrana, Alice Silvestri, Cecilia Piermarini, Raffaella Jacomini, Carlo Costantini, Maria Letizia Environ Sci Pollut Res Int Research Article Microplastic pollution is one of the greatest environmental concerns for contemporary times and the future. In the last years, the number of publications about microplastic contamination has increased rapidly and the list is daily updated. However, the lack of standard analytical approaches might generate data inconsistencies, reducing the comparability among different studies. The present study investigates the potential of two image processing tools (namely the shapeR package for R and ImageJ 1.52v) in providing an accurate characterization of the shape of microplastics using a restricted set of shape descriptors. To ascertain that the selected tools can measure small shape differences, we perform an experiment to verify the detection of pre-post variations in the shape of different microplastic types (i.e., nylon [NY], polyethylene [PE], polyethylene terephthalate [PET], polypropylene [PP], polystyrene [PS], and polyvinylchloride [PVC]) treated with mildly corrosive chemicals (i.e., 10% KOH at 60 °C, 30% H(2)O(2) at 50 °C, and 15% H(2)O(2) + 5% HNO(3) at 40 °C; incubation time ≈ 12 h). Analysis of surface area variations returns results about the vulnerability of plastic polymers to digestive solutions that are aligned with most of the acquired knowledge. The largest decrease in surface area occurs for KOH-treated PET particles, while NY results in the most susceptible polymer to the 30% H(2)O(2) treatment, followed by PVC and PS. PE and PP are the most resistant polymers to all the used treatments. The adopted methods to characterize microplastics seem reliable tools for detecting small differences in the shape and size of these particles. Then, the analytic perspectives that can be developed using such widely accessible and low-cost equipment are discussed. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11356-022-22128-3. Springer Berlin Heidelberg 2022-07-28 2023 /pmc/articles/PMC9813107/ /pubmed/35902515 http://dx.doi.org/10.1007/s11356-022-22128-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Article Valente, Tommaso Ventura, Daniele Matiddi, Marco Sbrana, Alice Silvestri, Cecilia Piermarini, Raffaella Jacomini, Carlo Costantini, Maria Letizia Image processing tools in the study of environmental contamination by microplastics: reliability and perspectives |
title | Image processing tools in the study of environmental contamination by microplastics: reliability and perspectives |
title_full | Image processing tools in the study of environmental contamination by microplastics: reliability and perspectives |
title_fullStr | Image processing tools in the study of environmental contamination by microplastics: reliability and perspectives |
title_full_unstemmed | Image processing tools in the study of environmental contamination by microplastics: reliability and perspectives |
title_short | Image processing tools in the study of environmental contamination by microplastics: reliability and perspectives |
title_sort | image processing tools in the study of environmental contamination by microplastics: reliability and perspectives |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9813107/ https://www.ncbi.nlm.nih.gov/pubmed/35902515 http://dx.doi.org/10.1007/s11356-022-22128-3 |
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