Signature of Sr isotope ratios and the contents of elements as a tool to distinguish wine regions in China.

This study investigated 120 Chinese wines from seven regions and had two objectives: to clarify the Sr isotope ratios and elemental characteristics of each region and to develop a strategy to distinguish the geographic origin of wine without authentic samples to predict its origin. The analyzed 87Sr/86Sr values ranged from 0.708256 to 0.715148, which correlated with the geological characteristics of the regions where they were grown. The Hexi Corridor exhibited the highest ratios of Sr isotopes, while Xinjiang had the lowest. The 87Sr/86Sr values were applied to establish a prediction map which was evaluated through cross-validation. The prediction error was found to be less than 0.00074. The Sr isotope ratio could remain stable for an extended period in a specific location. This map shows the feasibility of identifying wine origin and could be applied to other food products. Adding Sr isotope ratios could improve the accuracy in tracing wine origin.

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.

Geographical Origin Classification of Chinese Wines Based on Carbon and Oxygen Stable Isotopes and Elemental Profiles.

ABSTRACT: Wines from different regions have different qualities due to the impact of geographical location and climate. The sale of inferior wines seriously violates the fair-trade rights of consumers. This article provides an elemental analysis classification method for verifying the geographical origin of wines in the People's Republic of China. Inductively coupled plasma mass spectrometry, liquid chromatography isotope ratio mass spectrometry, and an isotope ratio mass spectrometer were used to analyze 142 wine samples collected from Helan Mountain, Xinjiang, Yunchuanzang, the Yanhuai Valley, and the Hexi Corridor regions. The data included elemental profiles, carbon isotope ratios (δ13C), and oxygen isotope ratios (δ18O). The results of multivariate analysis revealed that the geographical origin of wine is closely related to variations in elemental profiles and isotope ratios. Introducing δ18O and the elements Li, Mn, Ag, In, Th, Ta, and Re into the discriminant model yielded correct classification rates of the linear discriminant model of 90.8% for the training set and 87.3% for the test set.