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Original Research ARTICLE

Front. Plant Sci. | doi: 10.3389/fpls.2019.01788

Combining chemical information from grass pollen in multimodal characterization Provisionally accepted The final, formatted version of the article will be published soon. Notify me

 Sabrina Diehn1,  Boris Zimmermann2, Valeria Tafintseva3, Stephan Seifert1,  Murat Bagcioglu2, Mikael Ohlson2, Steffen Weidner4,  Siri Fjellheim2, Achim Kohler2 and  Janina Kneipp1*
  • 1Humboldt University of Berlin, Germany
  • 2Norwegian University of Life Sciences, Norway
  • 3Faculty of Science and Technology, Norwegian University of Life Sciences, Norway
  • 4Federal Institute for Materials Research and Testing (BAM), Germany

The analysis of pollen chemical composition is important to many fields, including agriculture, plant physiology, ecology, allergology, and climate studies. Here, the potential of a combination of different spectroscopic and spectrometric methods regarding the characterization of small biochemical differences between pollen samples was evaluated using multivariate statistical approaches. Pollen samples, collected from three populations of the grass Poa alpina were analyzed using Fourier-transform infrared (FTIR) spectroscopy, Raman spectroscopy, surface enhanced Raman scattering (SERS), and matrix assisted laser desorption/ionization mass spectrometry (MALDI-TOF MS). The variation in the sample set can be described in a hierarchical framework comprising three populations of the same grass species and four different growth conditions of the parent plants for each of the populations. Therefore, the data set can work here as a model system to evaluate the classification and characterization ability of the different spectroscopic and spectrometric methods. ANOVA Simultaneous Component Analysis (ASCA) was applied to achieve a separation of different sources of variance in the complex sample set. Since the chosen methods and sample preparations probe different parts and/ or molecular constituents of the pollen grains, complementary information about the chemical composition of the pollen can be obtained. By using consensus principal component analysis (CPCA), data from the different methods are linked together. This enables an investigation of the underlying global information, since complementary chemical data are combined. The molecular information from four spectroscopies was combined with phenotypical information gathered from the parent plants, thereby helping to potentially link pollen chemistry to other biotic and abiotic parameters

Keywords: Pollen, Poa alpina L., Population, environmental parameters, Fourier-transform infrared (FTIR) spectroscopy, Raman spectroscopy, surface-enhanced raman scattering (SERS), MALDI-TOF-mass spectrometry, Prinicpal Component Analysis, Consensus Principal Component Analysis (CPCA), ^ANOVA Simultaneous Component Analysis (ASCA)

Received: 30 Aug 2019; Accepted: 20 Dec 2019.

Copyright: © 2019 Diehn, Zimmermann, Tafintseva, Seifert, Bagcioglu, Ohlson, Weidner, Fjellheim, Kohler and Kneipp. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mx. Janina Kneipp, Humboldt University of Berlin, Berlin, Baden-Württemberg, Germany,