## 3 Results
### Multivariate Statistical Analysis  
An orthogonal partial least squares discriminant analysis (OPLS-DA) is an extension of Partial Least Squares Regression (PLS-R). This method can effectively reduce the model's complexity and enhance its interpretability without sacrificing its predictive ability [73]. In this study, five producing areas were identified by an OPLS-DA analysis, and a reliable model was constructed (\(R^{2}X=0.992\), \(R^{2}Y=0.878\), and \(Q^{2}=0.776\)) (Figure 4A). The stability of the model was verified through 200 permutation tests. The results show that the intercepts of R\({}^{2}\) and Q\({}^{2}\) are 0.353 and \(-0.653\), respectively (Figure 4B).  
The results indicate that there was a clear separation trend among the producing areas. The HL and YC producing areas are located in the first quadrant, which could be attributed to the similar aroma characteristics of the wines from the geographically close planting areas [34]. YN and QTX are distributed in the second and third quadrants and  
Figure 4: Multivariate statistical analysis of volatile compounds obtained by GC\(\times\)GC-TOFMS. (**A**) OPLS-DA score plot. (**B**) Cross-validation plot through 200 permutation tests. (**C**) Substance with VIP \(>1\). (**D**) Heat map based on VIP \(>1\).  
are adjacent to each other. It is speculated that they are related to the similar climatic conditions in the two regions, while the HSP producing area became a clearly separated cluster. The same trend was also observed in the cluster heat map (Figure 4D). Compounds with VIP values greater than 1 are generally regarded as having a high contribution to the classification [74]. In this study, a total of 15 substances were found to have VIP values greater than 1 (Figure 4C). Although esters account for a significant proportion in terms of quantity, including ethyl octanoate, isobutyl acetate, ethyl decanoate, diethyl succinate, ethyl hexanoate, isoamyl acetate, and ethyl enoate, alcohols remain the main contributors (Figure 4C). In particular, the VIP values of phenylethanol and isoamyl alcohol were markedly higher than those of the other components, thereby further highlighting their dominant role in aroma characteristics. Previous studies have confirmed that these two compounds are important volatiles that affect the bouquet of wines and are key factors in the subtle flavor differences among wines, endowing wines with rose and whiskey flavors [75]. Although previous studies have confirmed that norisoprenoids and terpen have an important impact on the geographical differences and typicality of wine [2], this study did not find these substances to have key roles in the model. By constructing a heat map, the differences in these substances in different producing areas can be visually presented (Figure 4D). For example, the concentration of benzyl alcohol in the QTX producing area was significantly higher than that in the other production areas; 3-methylpentanol and phenylethyl alcohol had the highest concentrations in the HL producing area, while the YN producing area had the highest concentration of isobutyl acetate and the lowest concentration of 2-methylbutyric acid. These results reflect the significant differences in the accumulation of specific compounds in each producing area and reveal the similarities and differences in chemical characteristics between regions.