Combined multivariate data analysis of high-performance thin-layer chromatography fingerprints and direct analysis in real time mass spectra for profiling of natural products like propolis

Sophisticated statistical tools are required to extract the full analytical power from high-performance thin-layer chromatography (HPTLC). Especially, the combination of HPTLC fingerprints (image) with chemometrics is rarely used so far. Also, the newly developed, instantaneous direct analysis in real time mass spectrometry (DART-MS) method is perspective for sample characterization and differentiation by multivariate data analysis. This is a first novel study on the differentiation of natural products using a combination of fast fingerprint techniques, like HPTLC and DART-MS, for multivariate data analysis. The results obtained by the chemometric evaluation of HPTLC and DART-MS data provided complementary information. The complexity, expense, and analysis time were significantly reduced due to the use of statistical tools for evaluation of fingerprints. The approach allowed categorizing 91 propolis samples from Germany and other locations based on their phenolic compound profile. A high level of confidence was obtained when combining orthogonal approaches (HPTLC and DART-MS) for ultrafast sample characterization. HPTLC with selective post-chromatographic derivatization provided information on polarity, functional groups and spectral properties of marker compounds, while information on possible elemental formulae of principal components (phenolic markers) was obtained by DART-MS.