Differentiation of Transylvanian fruit distillates using supervised statistical tools based on isotopic and elemental fingerprint

Comparative Investigation of Aroma-Active Volatiles in ("Ruixue", "Liangzhi", "Crystal Fuji," and "Guifei") Apples by Application of Gas Chromatography-Mass Spectrometry-Olfactometry (GC-MS-O) and Two-Dimensional Gas Chromatography-Quadrupole Mass Spectrometry (GC × GC-qMS) Coupled with Sensory Molecular Science

Aroma dramatically impacts the overall flavor profiles and consumer acceptance; therefore, it is necessary to conduct a comprehensive analysis of the aroma characteristics of apples. In this study, the aroma differences among four popular apple varieties ("Ruixue", "Liangzhi", "Crystal Fuji," and "Guifei") were compared using two extraction methods (headspace-solid phase microextraction, and solvent-assisted flavor evaporation) coupled with gas chromatography-mass spectrometry-olfactometry (GC-MS-O) and two-dimensional gas chromatography-quadrupole mass spectrometry (GC × GC-qMS). A total of 82 odorants were identified via GC-MS-O, and 143 volatiles were identified by GC× GC-qMS. Among them, 41 key aroma-active compounds (butanal, ethyl acetate, 3-methylbutanal, methyl butanoate, 2-methylpropyl acetate, ethyl 2-methylbutanoate, ethyl 3-methylbutanoate, butyl acetate, hexanal, 2-methylbutyl acetate, 1-butanol, 2-methylpropyl butanoate, 3-methylbutyl acetate, (E)-2-hexenal, butyl butanoate, butyl 2-methylbutanoate, hexyl acetate, hexyl butanoate, hexyl, 2-methylbutanoate, 1-octen-3-ol, 3-methylthiopropanol, 1,3-octanediol, linalyl acetate, and so on) with high odor activity values (OAVs) and AI value (odor activity values ≥1 or aroma intensity ≥3) were identified. Partial least-squares-discriminant analysis showed that Ruixue exhibited a high "fruity" note, Guifei and Crystal Fuji had the greatest "wood," "floral," and "sweet" notes, while Liangzhi presented a significant "green" note. This study provided flavor chemistry support for the apple quality control and production.

Influence of Geographical Origin on Isotopic and Elemental Compositions of Pork Meat

Pigs are a primary source of meat, accounting for over 30% of global consumption. Consumers' preferences are determined by health considerations, paying more attention to foodstuffs quality, animal welfare, place of origin, and swine feeding regime, and being willing to pay a higher price for a product from a certain geographical region. In this study, the isotopic fingerprints (δ2H, δ18O, and δ13C) and 29 elements of loin pork meat samples were corroborated with chemometric methods to obtain the most important variables that could classify the samples' geographical origin. δ2H and δ18O values ranged from -71.0 to -21.2‱, and from -9.3 to -2.8‱, respectively. The contents of macro- and micro-essential elements are presented in the following order: K > Na > Mg > Ca > Zn > Fe > Cu > Cr. The LDA model assigned in the initial classification showed 91.4% separation of samples, while for the cross-validation procedure, a percentage of 90% was obtained. δ2H, K, Rb, and Pd were identified as the most representative parameters to differentiate the pork meat samples coming from Romania vs. those from abroad. The mean values of metal concentrations were used to estimate the potential health risks associated with the consumption of pork meat The results showed that none of the analyzed metals (As, Cd, Sn, Pb, Cu, and Zn) pose a carcinogenic risk.

Volatile Profile in Greek Grape Marc Spirits with HS-SPME-GC-MS and Chemometrics: Evaluation of Terroir Impact

Greek grape marc spirits, although being traditional products, have lately attracted increasing attention as a revisited spirit product category. A headspace solid-phase microextraction coupled to the gas chromatography-mass spectrometry method was optimized in order to determine the volatile composition of 39 samples of grape marc spirits from eight major geographical regions of Greece and 4 protected designations of origin (PDOs). This untargeted analysis approach yielded the identification and quantification of 200 volatiles characterizing those products. Principal component analysis and partial least-squares-discriminant analysis (PLS-DA) combined with the volatile matrix were further employed to identify terroir denomination. Initial results showed a clear separation of the PDO products from Tyrnavos from the rest. Variable importance in projection data pretreatment was further adopted, and with 31 volatiles subsequently used with PLS-DA, products were correctly classified according to region of origin at 76.92% and for 3 out of 4 PDO denominations at 100%.