UHPLC-PAD Protocol for the Simultaneous Identification of Polyphenols and Bitter Acids: Organoleptic and Nutraceutical Fingerprinting of Bergamot-Flavored Craft Beer.

In this study, a UHPLC-PDA method for the simultaneous identification of polyphenols and bitter acids (alpha, beta, and isoalpha) in beer was developed. The resulting chemical profiles were leveraged to distinguish the characteristics of four (IPA, Lager, Blanche, ALE) bergamot-flavored beers, produced on a pilot-scale plant. In a streamlined 29 min analysis, thirty polyphenols and fourteen bitter acids were successfully identified under optimized separation conditions.

A Predictive Model to Correlate Amino Acids and Aromatic Compounds in Calabrian Honeys.

To better understand the biochemistry of the organoleptic properties of honey influencing its commercial value, a predictive model for correlating amino acid profiles to aromatic compounds was built. Because the amino acid composition of different varieties of honey plays a key role as a precursor of specific aroma bouquets, it is necessary to relate the amino acid typesetting to aromatic molecules. A selection of unifloral honeys produced in Calabria, South Italy, were used, and a new methodology based on the use of HILIC-UHPLC-ESI-MS/MS and HS-SPME-GC-MS combined with multivariate processing has been developed.

High-Performance Anion Exchange Chromatography with Pulsed Amperometric Detection (HPAEC-PAD) and Chemometrics for Geographical and Floral Authentication of Honeys from Southern Italy ().

High-performance anion exchange chromatography with pulsed amperometric detection (HPAEC-PAD) combined with chemometric analysis was developed to describe, for the first time, the sugar profile of sixty-one honeys of different botanical origin produced in southern Italy (Calabria Region). The principal component and linear discriminant analysis used to describe the variability of sugar data were able to discriminate the honeys according to their botanical origin with a correlation index higher than 90%. For the purpose of the robustness of the conclusions of this study, the analytical advantages of the HPAEC-PAD method have been statistically demonstrated compared to the official Italian HPLC-RI method (Refractive Index detection).

The potential of e-nose aroma profiling for identifying the geographical origin of licorice (Glycyrrhiza glabra L.) roots.

Licorice roots cultivated commercially in distinct geographical areas such as China, Iran, Italy (Abruzzo, Basilicata, Calabria and Sicily) and Turkey were classified using an artificial olfactive system (e-nose) based on metal oxide semiconductor sensors (MOS). The resultant instrumental data were processed using a multivariate statistical analysis method in order to classify the raw samples according to its origin. The e-nose odourprintings were obtained by a canonical discriminant analysis carried out with the aim of relating the specific data-sets corresponding to whole licorice roots aroma with the e-nose reference dataset.

Non-destructive flavour evaluation of red onion (Allium cepa L.) ecotypes: an electronic-nose-based approach.

This work reports preliminary results on the potential of a metal oxide sensor (MOS)-based electronic nose, as a non-destructive method to discriminate three "Tropea Red Onion" PGI ecotypes (TrT, TrMC and TrA) from each other and the common red onion (RO), which is usually used to counterfeit. The signals from the sensor array were processed using a canonical discriminant function analysis (DFA) pattern recognition technique. The DFA on onion samples showed a clear separation among the four onion groups with an overall correct classification rate (CR) of 97.