## 3 Results and Discussion
### Effects of STL Addition on BT VMs
#### 3.2.3 PLS-DA Analysis  
PLS-DA is widely used in food and agriculture research as a discriminant analytical method [18; 21; 22; 23]. Therefore, we applied PLS-DA to explore the influence of STL addition on VMs and aroma improvements of BT and to clarify the differences in volatile compound contents in the BT, BoS, and STL samples according to the 141 compounds found in dry tea. The three sample types were effectively distinguished by PLS-DA (Figure 2a). The STL samples clustered together in both quadrants on the left side, whereas the BoS and BT samples clustered in the upper-right and lower-right quadrants, respectively. These results were consistent with the sensory quality evaluation (Table 2) and the grouping pattern obtained using the heatmap cluster analysis (Figure 1). The model was verified by cross-validation after selecting three principal components. The related variables were as follows: R\({}^{2}\)X (cum) was 0.955, R\({}^{2}\)Y (cum) was 0.988, and Q\({}^{2}\) (cum) was 0.949, which indicated that this model was reliable and had strong prediction abilities. The loading plot (Figure 2b) clearly illustrates the differences in the volatile compound contents among the BT, STL, and BoS samples. For example, the concentrations of VMs such as hexanal, 1-methyl-1H-1,2,4-triazole, ethylbenzene, 3-octanone, \(o\)-cymene, benzeneateddehyde, lanalool, isobutyl pentyl ester, and neophytadiene were significantly higher in BT (\(p<0.05\)) than in the other two sample types, in which hexanal has a fruity and sweator [2], and benzeneacetaldehyde and lanalool impart a sweet and woody flavor [25]. Meanwhile, the concentrations of VMs such as 1-octen-3-ol, naphthalene, L-\(\alpha\)-terpineol, 2-methoxy-3-(2-methylpropyl)-pyrazine, 5-methyl-tridecane, isophorone, \(n\)-pentadecanol, 1-dodecanol, and \(trans\)-\(\beta\)-ionone were the highest in the STL samples (\(p<0.05\)). These accounted for glutinous rice, woody, floral, or sweet flavors [6; 10; 27; 28] and played important roles in enhancing the aroma of BT. In contrast, the concentrations of VMs such as 2-methoxy-furan, _cis_-2-methyl-cyclopentanol, 1-hexanol, 9-methylheptadecane, 5-ethyl-5-methyl-decane, 3-methyl-tetradecane, and \(O\)-(1-naphthol)-1,2-benzenedi were significantly higher in the BoS (\(p<0.05\)) than in the BT or STL samples. To identify the differential VMs among the BT, STL, and BoS samples, we constructed the S-plot of the PLS-DA model by comparing the BT vs. STL, STL vs. BoS, and BT vs. BoS samples. In Figure 3a-c, we identified 28, 26, and 14 differential VMs when comparing the STL vs. BoS, BT vs. STL, and BT vs. BoS samples, respectively. As shown in Figure 3d, both common and unique metabolites were found among the different sample types paired for comparison. Specifically, the STL vs. BoS, BT vs. STL, and BT vs. BoS samples shared seven common substances, namely, 1-octen-3-ol, (E)-2-hexenal, 1-methyl-1H-1,2,4  
Figure 2: Partial least-squares discriminant analysis score plot (**a**) and loading plot (**b**) for volatile metabolites (VMs) in BT, STL, and BoS samples. STL, _Strobilanthes tonkinensis_ Lindau; BT, black tea; BoS, black tea with added STL. SMI.DA(1), _Strobilanthes tonkinensis_ Lindau (STL); SMI.DA(2), black tea (BT); SMI.DA(3), BT with added STL (BoS). Longitudinal data represent 141 VMs, and horizontal data represent three tea samples. Red represents high metabolite content, and blue represents low metabolite content. triazole, (E)-3-hexen-1-ol, benzeneacetaldehyde, phenylethyll alcohol, and _trans_-\(\beta\)-ionone. The contents of these VMs were significantly different among the BT, STL, and BoS samples, which could be used as key VMs to distinguish tea samples and regulate aroma and flavor.