Identification of Tentative Traceability Markers with Direct Implications in Polyphenol Fingerprinting of Red Wines: Application of LC-MS and Chemometrics Methods

Geographical identification of Chinese wine based on chemometrics combined with mineral elements, volatile components and untargeted metabonomics

Identifying the geographic origin of a wine is of great importance, as origin fakery is commonplace in the wine industry. This study analyzed the mineral elements, volatile components, and metabolites in wine using inductively coupled plasma-mass spectrometry, headspace solid phase microextraction gas chromatography-mass spectrometry, and ultra-high-performance liquid chromatography-quadrupole-exactive orbitrap mass spectrometry. The most critical variables (5 mineral elements, 13 volatile components, and 51 metabolites) for wine origin classification were selected via principal component analysis and orthogonal partial least squares discriminant analysis. Subsequently, three algorithms-K-nearest neighbors, support vector machine, and random forest -were used to model single and fused datasets for origin identification. These results indicated that fused datasets, based on feature variables (mineral elements, volatile components, and metabolites), achieved the best performance, with predictive rates of 100% for all three algorithms. This study demonstrates the effectiveness of a multi-source data fusion strategy for authenticity identification of Chinese wine.

Chemometric analysis for authentication of 'Syrah' and 'Tempranillo' red wines of San Francisco Valley-Brazil compared to wines from other world regions by the molecular profile in HPLC

The aim of this study was to evaluate the phenolic composition, sugars, and organic acids by HPLC-DAD/RID, and the antioxidant capacity of 100% commercial 'Syrah' and 'Tempranillo' red wines from the San Francisco Valley-SFV wineries, and to compare them with commercial monovarietal wines of the same cultivars from countries such as South Africa, Spain, Chile, and Australia. In total, 25 phenolic compounds were quantified and classified into chemical groups in all wines (phenolics acids, flavanones, flavan-3-ols, flavonols, anthocyanins, and stilbenes). Among these, catechin, procyanidins B1 and B2, lactic acid, and antioxidant capacity were highlighted as the markers responsible for the typification of SFV wines when compared to wines from temperate regions. The data reported here contribute to the knowledge of the potential for producing quality wines in tropical climate regions. The wines of cultivars 'Syrah' and 'Tempranillo' are consolidated among the wineries in the SFV region, Brazil, due to their excellent adaptation to the semi-arid tropical climate. The SFV recently applied for a wine geographical indication as its wines are young with tropical climate typicity. This study shows that it is possible to differentiate SFV Syrah and Tempranillo wines from other world regions by HPLC molecular profile using chemometric techniques.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13197-023-05739-7.

Untargeted metabolomics analysis based on LC-IM-QTOF-MS for discriminating geographical origin and vintage of Chinese red wine

Identifying wine geographical origin and vintage is vital due to the abundance of fraudulent activity associated with wine mislabeling of region and vintage. In this study, an untargeted metabolomic approach based on liquid chromatography/ion mobility quadrupole time-of-flight mass spectrometry (LC-IM-QTOF-MS) was used to discriminate wine geographical origin and vintage. Wines were well discriminated according to region and vintage with orthogonal partial least squares-discriminant analysis (OPLS-DA). The differential metabolites subsequently were screened by OPLS-DA with pairwise modeling. 42 and 48 compounds in positive and negative ionization modes were screened as differential metabolitesfor the discrimination of different wine regions, and 37 and 35 compounds were screened for wine vintage. Furthermore, new OPLS-DA models were performed using these compounds, and the external verification trial showed excellent practicality with an accuracy over 84.2%. This study indicated that LC-IM-QTOF-MS-based untargeted metabolomics was a feasible tool for wine geographical origin and vintage discrimination.

Untargeted metabolomic analysis of Chinese red wines for geographical origin traceability by UPLC-QTOF-MS coupled with chemometrics

Identifying geographical origins of red wines made in specific regions is of significance since the false claim of geographical origins has been frequently exposed in China's wine industry. In this work, an untargeted metabolomic approach based on UPLC-QTOF-MS was established to discriminate geographical origins of Chinese red wines. The principal component analysis (PCA) showed significant differences between wine samples from three famous geographical origins in China. The metabolites contributing to the differentiation were screened by orthogonal partial least squares-discriminant analysis (OPLS-DA) with pairwise modeling. 40 and 46 differential metabolites in positive and negative ionization modes were putatively identified as chemical markers. Furthermore, heatmap visualization and OPLS-DA models were constructed based on these identified markers and external verification wine samples from different regions were successfully discriminated, with recognition rate up to 96.7%. This study indicated that UPLC-QTOF-MS-based untargeted metabolomics has great potential for the geographical origin traceability of Chinese red wines.