## 3 Results and Discussion
### PCA and OPLS-DA Analysis of Volatile Compounds
The plot only has one predictive principal component, t1, while there can be multiple orthogonal principal components. OPLS-DA maximizes the differences between groups on t1, thus allowing for a direct distinction of inter-group variations on t1, while it reflects the intra-group variations on the orthogonal principal components. Figure 2 displays the OPLS-DA score and loading plots of soluble compounds. The 12 wine samples are clearly clustered into two groups, marked with ellipses, and colored with blue diamonds for IBW samples and red circles for FBW samples. A clear distinction between the two groups indicates a successful discrimination of the model. The variable importance in projection (VIP) is calculated to measure the contribution and explanatory  
Figure 1: The PCA score plot and loading plot of volatile compounds: (**a**) Scores scatter plot t1 vs. t2; t[1] and t[2] represent PC1 and PC2. (**b**) Loadings scatter plot p1 vs. p2. Figure 2: The OPLS-DA score plot and loading plot of volatile compounds: (**a**) Scores scatter plot t1 vs. t10; (**b**) loadings scatter plot pq1 vs. pos10. ability of the concentrations of each compound in the classification and discrimination of samples. This information is used to assist in the screening of marker compounds, with the screening standard being VIP \(>\) 1.0 and \(p\) < 0.05. A total of 21 volatile compounds with significant difference (VSD) were screened and are shown in Table 3.  
According to the VIP values, the VSDs that made the greatest contribution to the differences between IBW and FBW were 1-pentanol, \(\beta\)-caryophyllene, and isopentanol. As shown in Table 3, compounds such as 1-pentanol (balsamic odor), isopentanol (whiskey, malt, burnt odor), hexadecane (alkane odor), and 3-methyl-1-butanol acetate (banana odor) were only detected in IBW. Conversely, cis-3-hexen-1-ol (green odor), 1-terpinene-4-ol (wo woody, turpentine, nutmeg odor), \(\gamma\)-nonalactone (coconut, peach odor), and ethyl benzoate (chamomile, floral, celery, fruit odor) were only detected in FBW. Among the VSDs, propanoic acid showed the highest fold change of 18.13 (IBW/FBW), followed by 2-methoxy-1,3-dioxolane with a fold change of 16.25 (FBW/IBW) and octanoic acid with a fold change of 10.97 (FBW/IBW). The high content of aldehydes and terpenes is one of the most important characteristics of the volatile components in bayberry. Specially, \(\beta\)-caryophyllene has been identified as the most dominant terme compound and the key flavor component of bayberry in previous studies [1; 16; 18; 19]. Our results show that \(\beta\)-caryophyllene was the most abundant volatile compound in IBW and was 3.73 times more abundant in IBW than in FBW. This high concentration of \(\beta\)-caryophyllene (25.89%) contributed highly to the strong bayberry flavor of IBW compared to FBW. However, the number of terpenoids and aldehydes was significantly less than the results reported in the above studies. This demonstrated that most terpenoids and aldehydes from bayberry juice were not retained in the final wine, but were degraded or volatilized during the brewing process. It has been reported that certain characteristic aroma volatiles in bayberry, such as 3-hexen-1-ol (green), 3-nonen-1-ol (cucumber), and terpinen-4-ol (wood, turpentine, nutmeg), significantly increased after fermentation in bayberry juice [17]. Our study confirms these findings, as 3-hexen-1-ol, 3-nonen-1-ol, and terpinen-4-ol were much higher in FBW than in IBW. Interestingly, while cis-3-hexen-1-ol, which represents a fresh and green note, was not detected in IBW, it was present in FBW. Further studies are needed to validate this result and reveal possible underlying mechanisms. However, our results showed a different trend