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2020-04-29Zeitschriftenartikel DOI: 10.18452/23711
Discrimination of grass pollen of different species by FTIR spectroscopy of individual pollen grains
Diehn, Sabrina
Zimmermann, Boris cc
Tafintseva, Valeria
Bağcıoğlu, Murat
Kohler, Achim cc
Ohlson, Mikael cc
Fjellheim, Siri
Kneipp, Janina
Mathematisch-Naturwissenschaftliche Fakultät
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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DOI
10.18452/23711
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https://doi.org/10.18452/23711
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<a href="https://doi.org/10.18452/23711">https://doi.org/10.18452/23711</a>