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Discrimination of grass pollen of different species by FTIR spectroscopy of individual pollen grains.

Authors
  • Diehn, Sabrina1
  • Zimmermann, Boris2
  • Tafintseva, Valeria2
  • Bağcıoğlu, Murat2
  • Kohler, Achim2
  • Ohlson, Mikael3
  • Fjellheim, Siri4
  • Kneipp, Janina5
  • 1 Department of Chemistry, Humboldt-Universität zu Berlin, Brook-Taylor-Straße 2, 12489, Berlin, Germany. , (Germany)
  • 2 Faculty of Science and Technology, Norwegian University of Life Sciences, 1432, Ås, Norway. , (Norway)
  • 3 Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, 1432, Ås, Norway. , (Norway)
  • 4 Faculty of Biosciences, Norwegian University of Life Sciences, 1432, Ås, Norway. , (Norway)
  • 5 Department of Chemistry, Humboldt-Universität zu Berlin, Brook-Taylor-Straße 2, 12489, Berlin, Germany. [email protected] , (Germany)
Type
Published Article
Journal
Analytical and Bioanalytical Chemistry
Publisher
Springer-Verlag
Publication Date
Sep 01, 2020
Volume
412
Issue
24
Pages
6459–6474
Identifiers
DOI: 10.1007/s00216-020-02628-2
PMID: 32350580
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

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.

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