TY - JOUR A1 - Seifert, Stephan A1 - Merk, V. A1 - Kneipp, Janina T1 - Identification of aqueous pollen extracts using surface enhanced Raman scattering (SERS) and pattern recognition methods JF - Journal of Biophotonics N2 - Aqueous pollen extracts of varying taxonomic relations were analyzed with surface enhanced Raman scattering (SERS) by using gold nanoparticles in aqueous suspensions as SERS substrate. This enables a selective vibrational characterization of the pollen water soluble fraction (mostly cellular components) devoid of the spectral contributions from the insoluble sporopollenin outer layer. The spectra of the pollen extracts are species-specific, and the chemical fingerprints can be exploited to achieve a classification that can distinguish between different species of the same genus. In the simple experimental procedure, several thousands of spectra per species are generated. Using an artificial neural network (ANN), it is demonstrated that analysis of the intrinsic biochemical information of the pollen cells in the SERS data enables the identification of pollen from different plant species at high accuracy. The ANN extracts the taxonomically-relevant information from the data in spite of high intra-species spectral variation caused by signal fluctuations and preparation specifics. The results show that SERS can be used for the reliable characterization and identification of pollen samples. They have implications for improved investigation of pollen physiology and for allergy warning. KW - Pattern recognition KW - Surface enhanced Raman scattering (SERS) KW - Artificial neural networks (ANN) KW - Multivariate statistics KW - Pollen PY - 2016 DO - https://doi.org/10.1002/jbio.201500176 VL - 9 IS - 1-2 SP - 181 EP - 189 PB - Wiley VCH AN - OPUS4-38092 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 JF - Rapid communications in mass spectrometry 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 DO - 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 JF - Rapid communications in mass spectrometry 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 DO - 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 -