## 3 Results
### PCA and OPLS-DA of Compounds in Berries and in Wine  
PCA was employed to delineate aroma compound profiles across grape graft combinations. The analysis revealed no significant segregation among rootstock treatments but demonstrated pronounced interannual variation (Figure 4A), indicating vintage constitutes the predominant differentiating factor for berry volatile composition. Principal component 1 (PC1) accounted for 49.2% of total variance, while PC2 explained 35.1% of the variance, collectively representing 84.3% of dataset variability. It was obvious to distinguish the three vintages, but it was difficult to distinguish between different rootstock combinations, and the vintage played a decisive role in the aroma. To mitigate confounding effects from vintages and rootstock-specific contributions to scion metabolite profiles, OPLS-DA was employed. The model was constructed using 70% of the dataset for training and 30% for validation, with predictive validity further assessed through 200 permutation tests to prevent overfitting. When we tried to fit the model with data from three vintages, the model was over-fitted and unreliable, so we fitted the model with data from two vintages, 2019 and 2020, and obtained a reliable model. As shown in Figure 4B, PC1 first distinguishes between the CS and CS/1103P combinations, and PC2 distinguished between years. Their key compounds included (E)-3-hexen-1-ol, isobutyl octanoate, 1-octen-3-ol, nonanal, ethyl decanoate, (E)-2-octenal, hexanoic acid, phenylethyl alcohol, (Z)-3-hexen-1-ol, benzyl alcohol, 1-hexanol, and (E, Z)-2,6-nonadien (Figure 4B and Table S8). Unfortunately, even after fitting the model with two vintages of aroma compounds, we were still unable to obtain a reliable model for comparing CS/SO4 to CS and CS/5A to CS. This further indicated that the two graft combinations, CS/SO4 and CS/5A, did not differ significantly from the overall aroma profile of CS, while 1103P had a clearer effect on the concentration of aroma substances in the scion. The vintage had a much greater effect than the rootstocks, which could mask the differences caused by rootstocks in the grape aroma. From another perspective, those aroma compounds that were more influenced by vintage are precisely the more plastic compounds, while these more plastic compounds tended to be false-positive marker compounds in single vintage experiments. Therefore, for cultivation experiments  
Figure 3: Aroma compound (C6/C9 compounds, higher alcohols, terpenes, C13-norisopenroids, acids, volatile phenolic, benzenes, esters) concentrations of different grafted combinations of Cabernet Sauvignon in wines (**A**–**H**). Note: different letters mean significant differences among the four treatments on the basis of [PERSON]’s multiple range test as \(p\) < 0.05.  
in the field, it was necessary to conduct more than two consecutive vintages of experiments to ensure the reliability of the results. PCA was also utilized in wines to categorize the various graft combinations and CS in two vintages. PC1 separated the two vintages by accounting for 49.3% of the total variance (Figure 5A). Wine in 2020 included more C6/C9 alcohols and volatile phenolics, and wine in 2019 included more terpenoids. In addition, OPLS-DA was used again to search for differential compounds imparted to wines by different rootstock combinations. PC1 differentiates between CS/1103P and CS, and PC2 differentiates between the two vintages; there were 26 different types of differential compounds (VIP > 1) between the CS/1103P combination and CS (Figure 5B and Table S8). Furthermore, PC1 differentiated between CS/SO4 and CS, whereas PC2 differentiated between the two vintages; there were 29 different types of differential compounds (VIP > 1) between the CS/SO4 combination and CS (Figure 5C and Table S8). When it came to the CS/5A combination, the mode was overfitted.