# Development of Assessment Criteria for Managing the Quality of Taishan Black Tea
## 3 Results
### Aroma Analysis of Taishan Black Tea
#### 3.3.2 Screening of Key Volatile Components in Taishan Black Tea  
Screening of Key Volatile Components Based on the OPLS-DA Model  
In this experiment, we evaluated 45 Taishan black tea samples by employing the OPLS-DA model. To ensure robustness, 200 random arrangement and combination experiments were conducted on the data. The strength of the evaluation model was determined by assessing the fitting parameters, with a focus on R\({}^{2}\) values approaching 1 and Q\({}^{2}\) values exceeding 0.5, indicating stronger predictive ability. As shown in Figure 4, the fitting parameters demonstrated high values: R\({}^{2}\)Y = 0.985, Q\({}^{2}\) = 0.996, and both Q\({}^{2}\) and R\({}^{2}\)Y \(p\)-values were below 0.005, indicating the high prediction accuracy of the model established in this experiment. Utilizing the outcomes of the OPLS-DA model, the variable importance projection (VIP) value was employed to identify the key volatile components in Taishan black tea. As shown in Table S4, 91 volatile components had a VIP value exceeding 1, including 18 alcohols, 15 aldehydes, 12 ketones, 8 esters, 10 alkanes, 10 olefins, 3 aromatic hydrocarbons, 5 terpen, and 9 heterocyclic compounds. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Taste Quality Index**} & \multicolumn{3}{c}{**Principal Component**} \\ \cline{2-4}  & **PC1** & **PC2** & **PC3** \\ \hline Catechin & 0.93 & 0.04 & 0.23 \\ Tea polyphonies & 0.93 & 0.05 & 0.15 \\ Amino acids & \(-\)0.05 & 0.94 & 0.13 \\ Water extracts & 0.40 & 0.64 & \(-\)0.01 \\ Caffeine & 0.21 & 0.11 & 0.96 \\ Contribution rate/\% & 51.16 & 22.21 & 15.77 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Eigenvectors of first three principal components and their contribution rates to the total variance. Key Volatile Component Screening Based on Principal Component Analysis  
Volatile substances with VIP values exceeding 1 were utilized for the cluster analysis of 15 tea companies. Notably, 10 tea companies (LXG, QRB, DXB, JSY, LYB, JQB, TZF, JQX, JKB, DXY) exhibited similar characteristics (Figure 5), indicating that the Taishan black tea samples from these companies shared a relatively similar volatile profile. Conversely, the black tea samples from the remaining five companies displayed significant differences. Moreover, the sample size of the 10 companies accounted for 66.67% of the total sample size, surpassing the 50% mark. Consequently, the samples from these 10 companies were selected for the PCA, aiming to further identify and screen the key volatile components. The cumulative contribution rate of the initial six principal components was 86.29% (Table 4), indicating that these principal components effectively captured and represented the overall sample information. Consequently, the weight coefficients of the rotation matrix were calculated specifically for these six principal components (Table S5). The weight coefficient of the rotation matrix was >0.4, as is the standard for screening; 31 volatile compounds played important roles in the 6 principal components, respectively. Figure 4: OPLS-DA prediction model. (**A**), OPLS-DA S-plot; (**B**), prediction model. The red dots indicate that the VIP values of these volatile substances were greater than or equal to 1, and the green dots indicate that the VIP values of these volatile substances were less than or equal to 1. Figure 5: Cluster analysis of volatile substances based on VIP values exceeding 1. The numbers in the figure correspond to the numbers of volatile substances in Table S4. The odor activity value (OAV) serves as a tool for assessing the overall flavor of foods dominated by a single odor component. Key aroma compounds with an OAV greater than 1 are generally considered significant contributors to the overall aroma [12]. In our analysis, we calculated the OAVs for volatile components with VIP values greater than 1.