To investigate the variation and fractionation of stable isotopes from irrigation water to soil, grapes, and wine, δ2H, δ18O, and δ17O in different samples from 10 regions in China were determined using a water isotope analyser. The values were significantly different among regions according to the chemometric analysis. All isotopes were significantly and positively correlated with irrigation water-soil and grape-wine. A significant water isotopic fractionation effect was observed from the irrigation water to the soil, grapes, and wine. Stable isotope distribution characteristics correlated with longitude, latitude, altitude, temperature, precipitation, station pressure and wind speed. The linear discriminant analysis (LDA), random forest (RF), support vector machine (SVM), and feed-forward neural network (FNN) models 58.33-100 %, 80-100 %, 53.33-100 %, and 73.33-100 % accurate for distinguishing the geographical origins of all samples from training and test data, respectively. These findings provide a theoretical basis for authenticating the geographic origin of Chinese wines using stable isotope analysis.

Stable isotopes and multi-element profiles of grapes and corresponding soils from different origins and vintages were determined by IRMS and ICP-MS, respectively. Stable isotope ratios and multi-element contents show significant differences among distinct regions and vintages. Grapes and soils were separated using δ2H and δ18O according to regions and vintages. PCA and CA results further verified that multi-element profiles were influenced by origins and vintages. In particular, δ2H, δ18O, and 21 elements in grapes were correlated with those in soil. Redundancy and Spearman analyses revealed that the BCF values were related to the longitude, latitude, altitude, precipitation, and average temperature. RF shows better performance than PLS-DA for discriminating grape origins and vintages. K, Tb, Cs, δ2H, and Co were important variables in discriminating grape origins. These findings confirm that isotopic and elemental profiles depend on the origin, vintage, and soil, establishing a promising method to discriminate grape origins and vintages.

The structural and functional diversities of the microbial ecosystem on the grape surface affect the health of berries and the flavor of wines, which are also changed by many factors such as climate, weather conditions, agronomic practices, and physiological development. To understand and explore the natural characteristics of the grape surface microbial ecosystem during ripening, the species composition and dynamics of fungal and bacterial communities on the skin of Ecolly grape were determined by Illumina Novaseq platform sequencing. The results showed that 2146 fungal OTUs and 4175 bacterial OTUs were obtained, belonging to four fungal phyla and 20 bacterial phyla. The Shannon index indicated that the fungal community had the highest species diversity at the véraison stage and the bacterial community at the harvest stage. The four dominant fungal genera during grape ripening were Alternaria, Naganishia, Filobasidium, and Aureobasidium, which accounted for 82.8% of the total fungal community, and the dominant bacterial genera included Sphingomonas, Brevundimonas, Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium, and Massilia, which accounted for 77.9% of the total bacterial community. The species richness and diversity in the grape microbial ecosystem changed constantly during the maturation stages, and there were strong correlations between certain core microbial genera, which may have an important impact on the function and ecological role of the community. This study provides a basis for understanding the natural characteristics of the microbial ecosystem on the grape surface during grape ripening, as well as the sustainable production concept of the microecology driving the viticulture management system.