Classification of Italian propolis by HR-NMR: influence of different production techniques

Propolis, a complex resinous substance collected by bees, has been known for its healing properties. It has various biological activities related to the chemical composition which varies according to its variety, the geographical source and also the method of harvest. The influence of the method of production on the composition and the properties of propolis seems to be related with the recognized behavior of the bees that cover the smooth and narrow surfaces, as the thin space created by the wedges, with propolis that is purer and richer in balsams, whereas they use the propolis mixed with major amount of waxes to cover the irregular surfaces of the beehive or the plastic nets used for the propolis production. Considering the widespread use of propolis products and the increased interest concerning the characterization of chemical composition, the present study was conducted to evaluate if the HR-NMR used as chemical fingerprint analysis coupled with multivariate statistical methods is able to classify poplar propolis according to the method of harvest and to gain extra knowledge concerning the fingerprint of propolis. In this regard, 60 raw propolis collected with different methods by several local beekeepers and by CRA-API (Consiglio per la Ricerca e la Sperimentazione in Agricoltura-Istituto Nazionale di Apicoltura e Bachicoltura) (Bologna, Italy) were extracted with ethanol and, before performing the NMR experiments, were analyzed for quantification of the main bioactive substances of poplar type propolis (total phenolics, total flavones and flavonols, total flavanones and dihydroflavonols) and balsams, to confirm the poplar source. The ethanolic propolis extracts were analyzed by HR-NMR using both 1H NMR and HMBC. Spectral data were analyzed by application of multivariate statistical techniques (FA and GDA). The best results were obtained using the 1H NMR which enabled to develope a sufficiently effective and appropriate model.