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Comparison of two rapid automated analysis tools for large FTIR microplastic datasets
One of the biggest issues in microplastic (MP, plastic items <5 mm) research is the lack of standardisation and harmonisation in all fields, reaching from sampling methodology to sample purification, analytical methods and data analysis. This hampers comparability as well as reproducibility amon...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10284987/ https://www.ncbi.nlm.nih.gov/pubmed/36939884 http://dx.doi.org/10.1007/s00216-023-04630-w |
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author | Moses, Sonya R. Roscher, Lisa Primpke, Sebastian Hufnagl, Benedikt Löder, Martin G. J. Gerdts, Gunnar Laforsch, Christian |
author_facet | Moses, Sonya R. Roscher, Lisa Primpke, Sebastian Hufnagl, Benedikt Löder, Martin G. J. Gerdts, Gunnar Laforsch, Christian |
author_sort | Moses, Sonya R. |
collection | PubMed |
description | One of the biggest issues in microplastic (MP, plastic items <5 mm) research is the lack of standardisation and harmonisation in all fields, reaching from sampling methodology to sample purification, analytical methods and data analysis. This hampers comparability as well as reproducibility among studies. Concerning chemical analysis of MPs, Fourier-transform infrared (FTIR) spectroscocopy is one of the most powerful tools. Here, focal plane array (FPA) based micro-FTIR (µFTIR) imaging allows for rapid measurement and identification without manual preselection of putative MP and therefore enables large sample throughputs with high spatial resolution. The resulting huge datasets necessitate automated algorithms for data analysis in a reasonable time frame. Although solutions are available, little is known about the comparability or the level of reliability of their output. For the first time, within our study, we compare two well-established and frequently applied data analysis algorithms in regard to results in abundance, polymer composition and size distributions of MP (11–500 µm) derived from selected environmental water samples: (a) the siMPle analysis tool (systematic identification of MicroPlastics in the environment) in combination with MPAPP (MicroPlastic Automated Particle/fibre analysis Pipeline) and (b) the BPF (Bayreuth Particle Finder). The results of our comparison show an overall good accordance but also indicate discrepancies concerning certain polymer types/clusters as well as the smallest MP size classes. Our study further demonstrates that a detailed comparison of MP algorithms is an essential prerequisite for a better comparability of MP data. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00216-023-04630-w. |
format | Online Article Text |
id | pubmed-10284987 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-102849872023-06-23 Comparison of two rapid automated analysis tools for large FTIR microplastic datasets Moses, Sonya R. Roscher, Lisa Primpke, Sebastian Hufnagl, Benedikt Löder, Martin G. J. Gerdts, Gunnar Laforsch, Christian Anal Bioanal Chem Research Paper One of the biggest issues in microplastic (MP, plastic items <5 mm) research is the lack of standardisation and harmonisation in all fields, reaching from sampling methodology to sample purification, analytical methods and data analysis. This hampers comparability as well as reproducibility among studies. Concerning chemical analysis of MPs, Fourier-transform infrared (FTIR) spectroscocopy is one of the most powerful tools. Here, focal plane array (FPA) based micro-FTIR (µFTIR) imaging allows for rapid measurement and identification without manual preselection of putative MP and therefore enables large sample throughputs with high spatial resolution. The resulting huge datasets necessitate automated algorithms for data analysis in a reasonable time frame. Although solutions are available, little is known about the comparability or the level of reliability of their output. For the first time, within our study, we compare two well-established and frequently applied data analysis algorithms in regard to results in abundance, polymer composition and size distributions of MP (11–500 µm) derived from selected environmental water samples: (a) the siMPle analysis tool (systematic identification of MicroPlastics in the environment) in combination with MPAPP (MicroPlastic Automated Particle/fibre analysis Pipeline) and (b) the BPF (Bayreuth Particle Finder). The results of our comparison show an overall good accordance but also indicate discrepancies concerning certain polymer types/clusters as well as the smallest MP size classes. Our study further demonstrates that a detailed comparison of MP algorithms is an essential prerequisite for a better comparability of MP data. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00216-023-04630-w. Springer Berlin Heidelberg 2023-03-20 2023 /pmc/articles/PMC10284987/ /pubmed/36939884 http://dx.doi.org/10.1007/s00216-023-04630-w Text en © The Author(s) 2023 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 Paper Moses, Sonya R. Roscher, Lisa Primpke, Sebastian Hufnagl, Benedikt Löder, Martin G. J. Gerdts, Gunnar Laforsch, Christian Comparison of two rapid automated analysis tools for large FTIR microplastic datasets |
title | Comparison of two rapid automated analysis tools for large FTIR microplastic datasets |
title_full | Comparison of two rapid automated analysis tools for large FTIR microplastic datasets |
title_fullStr | Comparison of two rapid automated analysis tools for large FTIR microplastic datasets |
title_full_unstemmed | Comparison of two rapid automated analysis tools for large FTIR microplastic datasets |
title_short | Comparison of two rapid automated analysis tools for large FTIR microplastic datasets |
title_sort | comparison of two rapid automated analysis tools for large ftir microplastic datasets |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10284987/ https://www.ncbi.nlm.nih.gov/pubmed/36939884 http://dx.doi.org/10.1007/s00216-023-04630-w |
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