RATIONALE: A fast and reliable online identification of pollen is not yet available. The identification of pollen is based mainly on the evaluation of morphological data obtained by microscopic methods. METHODS: Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-TOF MS) was applied to the analysis of extracts and milled pollen samples. The obtained MALDI data were explored for characteristic peak patterns which could be subjected to a multivariate statistical analysis. RESULTS: Two sample preparation methods are presented, which require only minimal or no chemical extraction of the pollen. MALDI pollen spectra could be recorded showing various peak patterns. A multivariate statistics approach allowed the classification of pollen into clusters indicating similarities and differences between various species. CONCLUSIONS: These results demonstrate the potential and the reliability of MALDI-TOF MS for the identification and, in combination with multivariate statistics, also for the classification of pollen.
RATIONALE: A fast and reliable online identification of pollen is not yet available. The identification of pollen is based mainly on the evaluation of morphological data obtained by microscopic methods. METHODS: Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-TOF MS) was applied to the analysis of extracts and milled pollen samples. The obtained MALDI data were explored for characteristic peak patterns which could be subjected to a multivariate statistical analysis. RESULTS: Two sample preparation methods are presented, which require only minimal or no chemical extraction of the pollen. MALDI pollen spectra could be recorded showing various peak patterns. A multivariate statistics approach allowed the classification of pollen into clusters indicating similarities and differences between various species. CONCLUSIONS: These results demonstrate the potential and the reliability of MALDI-TOF MS for the identification and, in combination with multivariate statistics, also for the classification of pollen.
Authors: Sabrina Diehn; Boris Zimmermann; Valeria Tafintseva; Stephan Seifert; Murat Bağcıoğlu; Mikael Ohlson; Steffen Weidner; Siri Fjellheim; Achim Kohler; Janina Kneipp Journal: Front Plant Sci Date: 2020-01-31 Impact factor: 5.753