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Discrimination of grass pollen of different species by FTIR spectroscopy of individual pollen grains
Fourier-transform infrared (FTIR) spectroscopy enables the chemical characterization and identification of pollen samples, leading to a wide range of applications, such as paleoecology and allergology. This is of particular interest in the identification of grass (Poaceae) species since they have po...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer Berlin Heidelberg
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442581/ https://www.ncbi.nlm.nih.gov/pubmed/32350580 http://dx.doi.org/10.1007/s00216-020-02628-2 |
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author | Diehn, Sabrina Zimmermann, Boris Tafintseva, Valeria Bağcıoğlu, Murat Kohler, Achim Ohlson, Mikael Fjellheim, Siri Kneipp, Janina |
author_facet | Diehn, Sabrina Zimmermann, Boris Tafintseva, Valeria Bağcıoğlu, Murat Kohler, Achim Ohlson, Mikael Fjellheim, Siri Kneipp, Janina |
author_sort | Diehn, Sabrina |
collection | PubMed |
description | Fourier-transform infrared (FTIR) spectroscopy enables the chemical characterization and identification of pollen samples, leading to a wide range of applications, such as paleoecology and allergology. This is of particular interest in the identification of grass (Poaceae) species since they have pollen grains of very similar morphology. Unfortunately, the correct identification of FTIR microspectroscopy spectra of single pollen grains is hindered by strong spectral contributions from Mie scattering. Embedding of pollen samples in paraffin helps to retrieve infrared spectra without scattering artifacts. In this study, pollen samples from 10 different populations of five grass species (Anthoxanthum odoratum, Bromus inermis, Hordeum bulbosum, Lolium perenne, and Poa alpina) were embedded in paraffin, and their single grain spectra were obtained by FTIR microspectroscopy. Spectra were subjected to different preprocessing in order to suppress paraffin influence on spectral classification. It is shown that decomposition by non-negative matrix factorization (NMF) and extended multiplicative signal correction (EMSC) that utilizes a paraffin constituent spectrum, respectively, leads to good success rates for the classification of spectra with respect to species by a partial least square discriminant analysis (PLS-DA) model in full cross-validation for several species. PLS-DA, artificial neural network, and random forest classifiers were applied on the EMSC-corrected spectra using an independent validation to assign spectra from unknown populations to the species. Variation within and between species, together with the differences in classification results, is in agreement with the systematics within the Poaceae family. The results illustrate the great potential of FTIR microspectroscopy for automated classification and identification of grass pollen, possibly together with other, complementary methods for single pollen chemical characterization. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00216-020-02628-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-7442581 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-74425812020-08-27 Discrimination of grass pollen of different species by FTIR spectroscopy of individual pollen grains Diehn, Sabrina Zimmermann, Boris Tafintseva, Valeria Bağcıoğlu, Murat Kohler, Achim Ohlson, Mikael Fjellheim, Siri Kneipp, Janina Anal Bioanal Chem Research Paper Fourier-transform infrared (FTIR) spectroscopy enables the chemical characterization and identification of pollen samples, leading to a wide range of applications, such as paleoecology and allergology. This is of particular interest in the identification of grass (Poaceae) species since they have pollen grains of very similar morphology. Unfortunately, the correct identification of FTIR microspectroscopy spectra of single pollen grains is hindered by strong spectral contributions from Mie scattering. Embedding of pollen samples in paraffin helps to retrieve infrared spectra without scattering artifacts. In this study, pollen samples from 10 different populations of five grass species (Anthoxanthum odoratum, Bromus inermis, Hordeum bulbosum, Lolium perenne, and Poa alpina) were embedded in paraffin, and their single grain spectra were obtained by FTIR microspectroscopy. Spectra were subjected to different preprocessing in order to suppress paraffin influence on spectral classification. It is shown that decomposition by non-negative matrix factorization (NMF) and extended multiplicative signal correction (EMSC) that utilizes a paraffin constituent spectrum, respectively, leads to good success rates for the classification of spectra with respect to species by a partial least square discriminant analysis (PLS-DA) model in full cross-validation for several species. PLS-DA, artificial neural network, and random forest classifiers were applied on the EMSC-corrected spectra using an independent validation to assign spectra from unknown populations to the species. Variation within and between species, together with the differences in classification results, is in agreement with the systematics within the Poaceae family. The results illustrate the great potential of FTIR microspectroscopy for automated classification and identification of grass pollen, possibly together with other, complementary methods for single pollen chemical characterization. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00216-020-02628-2) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2020-04-29 2020 /pmc/articles/PMC7442581/ /pubmed/32350580 http://dx.doi.org/10.1007/s00216-020-02628-2 Text en © The Author(s) 2020 Open Access This 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/. |
spellingShingle | Research Paper Diehn, Sabrina Zimmermann, Boris Tafintseva, Valeria Bağcıoğlu, Murat Kohler, Achim Ohlson, Mikael Fjellheim, Siri Kneipp, Janina Discrimination of grass pollen of different species by FTIR spectroscopy of individual pollen grains |
title | Discrimination of grass pollen of different species by FTIR spectroscopy of individual pollen grains |
title_full | Discrimination of grass pollen of different species by FTIR spectroscopy of individual pollen grains |
title_fullStr | Discrimination of grass pollen of different species by FTIR spectroscopy of individual pollen grains |
title_full_unstemmed | Discrimination of grass pollen of different species by FTIR spectroscopy of individual pollen grains |
title_short | Discrimination of grass pollen of different species by FTIR spectroscopy of individual pollen grains |
title_sort | discrimination of grass pollen of different species by ftir spectroscopy of individual pollen grains |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442581/ https://www.ncbi.nlm.nih.gov/pubmed/32350580 http://dx.doi.org/10.1007/s00216-020-02628-2 |
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