## 3 Results and Discussion
### Analysis of Volatile Component Concentrations in the Three Tea Samples  
HS-SPME-GC-MS was used to identify the volatile components of the three tea samples, and 94 major volatile components were detected (Table S2). To provide an insightful overview of the variation in volatile components, a PCA score plot was constructed on the integrated GC-MS datasets of the three tea samples. The volatile components of the three tea samples were well discriminated, all replicates from each sample clustered together and were separated from other tea samples, as shown in Figure 4A (PC1 = 62.0% and PC2 = 35.2%). In brief, the tea samples (GT, QLC, and QDC) were grouped into three distinct areas, indicating that the types and component ratios of the volatile components in the three tea samples were remarkably different. The volatile components in the three tea samples (GT, QLC, and QDC) were compared using a Venn diagram (Figure 4B). In total, 94 major volatile components were detected, and 25 were detected in all the samples; thus, they were deemed common volatile components. The number of differential volatile components found exclusively in each tea sample was 19 for GT, 10 for QLC, and 12 for QDC. These components were considered as the defining volatile components for each sample.  
The difference in volatile component varieties, contents and component ratios in tea has a direct influence on the aroma characteristics. As shown in Figure 4, the 94 volatile components were 24 aldehydes, 13 alcohols, 10 esters, 18 alkenes, 9 aromatic hydrocarbons, 7 ketones, and 13 other components, and the concentrations of volatile component types varied substantially among the three tea samples. The levels of volatile components of  
Figure 4: Analysis of volatile components of the three tea samples. (**A**). PCA score plot derived from the concentrations of volatile components of the three tea samples. (**B**). Venn diagram of the volatile components from the three tea samples. (**C**). The volatile component types of the three tea samples.  
GT were similar to those in _C. sinensis_ green tea of previous studies [16; 17], whereas they have significant differences in QLC and QDC. In QLC, aldehydes, alcohols, and alkenes were the most prevalent of the volatile component types, and accounted for 54.68 \(\pm\) 1.32%. Linalool, geraniol, and nonanal were the major parts of the volatile components in QDC, and previous studies have shown linalool, nonanal, and geraniol as the main substances that emit a floral or fruity flavor in GT [37; 38]. Furthermore, the levels of dimethyl sulfide and _cis_-jasmone in QDC were relatively high, and accounted for 21.13 \(\pm\) 0.58% and 5.90 \(\pm\) 0.28%, respectively. Dimethyl sulfide was a crucial and unique substance in the volatile component with a clean aroma of fresh GT [17], and _cis_-jasmone exhibits a strong floral aroma and significantly contributes to the profile of oologne tea [39]. Alcohols and alkenes were the major parts of the volatile component types in QDC, and accounted for 79.95 \(\pm\) 1.95% of the volatile components. Linalool, 3,7-dimethyl-6-octen-3-ol, and (-)-terpinen-4-ol were the main alcohols in QDC, and shown a strong floral aroma with a low odor detection threshold [17; 27]. \(\alpha\)-terpinene, \(\gamma\)-terpinene, \(\alpha\)-ocimene, and terpinolene were the main alkenes in QDC, and most terpen have floral aroma [27; 38; 40].