Essential oils are highly volatile, aromatic concentrated extracts from plants with wide applications. In this study, fast, easy-to-use attenuated total reflection Fourier-transform infrared spectroscopy (ATR-FTIR) was combined with chemometric techniques to verify essential oils’ taxonomy and purity. Principal component analysis (PCA) clustered 30 essential oil samples into three different groups based on plant botanical family and concentration. The first group contained highly concentrated oils from the Asteraceae family, the second group contained highly concentrated oils from the Lamiaceae family, while the last group contained three highly concentrated essential oils from different botanical families and commercial-grade essential oils. Thus, commercial-grade oil samples did not cluster with the corresponding concentrated oil samples despite their similar spectral patterns or botanical family. A loading plot identified infrared (IR) bands that correspond to carbonyl, vinyl, methyl and methylene group vibrations as the most important spectral bands that can be used as marker bands for discrimination between different botanical plant family groups. Hierarchical cluster analysis (HCA) confirmed the results obtained by PCA. ATR-FTIR spectroscopy combined with chemometric algorithms provides a direct and non-destructive method for chemotaxonomic classification of medicinal and aromatic essential oils and an assessment of their purity.

Propolis is one of the most used natural products known for centuries for its beneficial effects. Due to significant differences in chemical composition of samples originating from different geographic and climatic zones it is crucial to characterize reliably each type of propolis. This article comprises the latest findings concerning the poplar type propolis, i.e. it gives a cross section of chemical composition, botanical origin and biological activity of poplar type propolis in order to encourage further investigations that would indicate its beneficial effects.

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.

New information has come to light about the biological activity of propolis and the quality of natural products which requires a rapid and reliable assessment method such as High Performance Thin-Layer Chromatography (HPTLC) fingerprinting. This study investigates chromatographic and chemometric approaches for determining the antimicrobial activity of propolis of Serbian origin against various bacterial species. A linear multivariate calibration technique, using Partial Least Squares, was used to extract the relevant information from the chromatographic fingerprints, i.e. to indicate peaks which represent phenolic compounds that are potentially responsible for the antimicrobial capacity of the samples. In addition, direct bioautography was performed to localize the antibacterial activity on chromatograms. The biological activity of the propolis samples against various bacterial species was determined by a minimum inhibitory concentration assay, confirming their affiliation with the European poplar type of propolis and revealing the existence of two types (blue and orange) according to botanical origin. The strongest antibacterial activity was exhibited by sample 26 against Staphylococcus aureus, with a MIC value of 0.5 mg/mL, and Listeria monocytogenes, with a MIC as low as 0.1 mg/mL, which was also the lowest effective concentration observed in our study. Generally, the orange type of propolis shows higher antimicrobial activity compared to the blue type. PLS modelling was performed on the HPTLC data set and the resulting models might qualitatively indicate compounds that play an important role in the activity exhibited by the propolis samples. The most relevant peaks influencing the antimicrobial activity of propolis against all bacterial strains were phenolic compounds at R_F values of 0.37, 0.40, 0.45, 0.51, 0.60 and 0.70. The knowledge gained through this study could be important for attributing the antimicrobial activity of propolis to specific chemical compounds, as well as the verification of HPTLC fingerprinting as a reliable method for the identification of compounds that are potentially responsible for antimicrobial activity. This is the first report on the activity of Serbian propolis as determined by several combined methods, including the modelling of antimicrobial activity by HPTLC fingerprinting.