TY - JOUR A1 - Ivleva, N.P. A1 - Niessner, R. A1 - Panne, Ulrich T1 - Characterization and discrimination of pollen by Raman microscopy N2 - The chemical characterization and discrimination of allergy-relevant pollen (common ragweed (Ambrosia artemisiifolia), white birch (Betula pendula), English oak (Quercus robur), and European linden (Tilia cordata)) has been studied by Raman microscopy. Spectra were obtained at different excitation wavelengths (514, 633, and 780 nm) and various methods were examined to minimize the strong fluorescence background. The use of a He–Ne laser (633 nm) for excitation yields high-quality single pollen Raman spectra, which contain multiple bands due to pollen components such as carotenoids, proteins, nucleic acids, carbohydrates, and lipids. Multivariate classification, i.e. principal component analysis (PCA) and hierarchical cluster analysis, demonstrated the validity of the approach for discrimination between different pollen species. KW - Raman spectroscopy KW - Pollen KW - Multivariate classification PY - 2005 U6 - https://doi.org/10.1007/s00216-004-2942-1 SN - 1618-2642 SN - 1618-2650 VL - 381 IS - 1 SP - 261 EP - 267 PB - Springer CY - Berlin AN - OPUS4-7185 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Krause, Benjamin Christoph A1 - Seifert, Stephan A1 - Panne, Ulrich A1 - Kneipp, Janina A1 - Weidner, Steffen T1 - Matrix-assisted laser desorption/ionization mass spectrometric investigation of pollen and their classification by multivariate statistics N2 - 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. KW - MALDI TOF mass spectrometry KW - Pollen KW - Multivariate statistics PY - 2012 U6 - https://doi.org/10.1002/rcm.6202 SN - 0951-4198 SN - 1097-0231 VL - 26 IS - 9 SP - 1032 EP - 1038 PB - Wiley CY - Chichester AN - OPUS4-25648 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Seifert, Stephan A1 - Weidner, Steffen A1 - Panne, Ulrich A1 - Kneipp, Janina T1 - Taxonomic relationship of pollen from MALDI TOF MS data using multivariate statistics N2 - Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) has been suggested as a promising tool for the investigation of pollen, but the usefulness of this approach for classification and identification of pollen species has to be proven by an application to samples of varying taxonomic relations. KW - MALDI mass spectrometry KW - Pollen KW - Multivariate statistics PY - 2015 U6 - https://doi.org/10.1002/rcm.7207 SN - 0951-4198 SN - 1097-0231 VL - 29 SP - 1145 EP - 1154 PB - Wiley CY - Chichester AN - OPUS4-35296 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -