## 3 Results and Discussion
### Identification of VOCs by HS-SPME-GC-Ms  
The volatile organic compounds (VOCs) from four tea sample groups were identified using HS-SPME-GC-MS, revealing a total of 144 distinct VOCs. The number of volatiles detected varied across the groups, with 85, 82, 83, and 100 volatiles identified in WNZ-CK, WNZ-D, FD-CK, and FD-D, respectively. These identified volatiles were categorized into 10 classes, namely esters, alcohols, ketones, aldehydes, terpenoids, acids, alkanes, alkenes, aromatics, and heterocyclics (as detailed in Table S4 and Figure 3B). To provide a clearer visualization of the variations in and characteristics of VOCs between groups, the total content, number, and proportion of VOCs in each category were summarized and presented through chord graphs, bar plots, and Venn diagrams (Figure 3). In terms of total VOC content, WNZ samples exhibited higher levels compared to FD samples (Figure 3A). The primary VOC classes in WNZ-CK and WNZ-D were terpenoids, alcohols, and ketones, accounting for 95% and 89% of the total concentration, respectively (Figure 3C). In contrast, FD-CK and FD-D were dominated by alcohols, terpenoids, and aldehydes, with these three categories comprising 97% of the total concentration (Figure 3D).  
Following drought stress, a decrease in VOC concentration was observed in both the FD and WNZ cultivars (Figure 3A). Regarding VOC diversity, FD exhibited a greater increase in component richness after drought stress, whereas the variation in WNZ was less pronounced (Figure 3B). In both cultivars, terpenoids, alcohols, ketones, aldehydes, and esters were the predominant VOC classes, collectively contributing 85%, 85%, 87%, and 90% in FD-CK, FD-D, WNZ-CK, and WNZ-D, respectively. In the FD cultivar, drought stress led to an increase in the number of alcohols, aldehydes, and ketones, while the numbers of terpenoids and esters decreased. In comparison, the WNZ cultivar experienced a rise in aldehydes and ketones, but a reduction in alcohols, terpenoids, and esters under drought conditions (Figure 3D).  
Furthermore, 44 volatiles were found to be common across all four groups, while 5, 26, 12, and 8 volatiles were exclusively detected in FD-CK, FD-D, WNZ-CK, and WNZ-D, respectively (Figure 3E). It is noteworthy that while the total VOC content in WNZ-CK exceeded that in FD-CK, the difference in VOC variety between these groups was marginal. Under drought stress, although both cultivars showed a reduction in total VOC content, FD-D exhibited a smaller decrease, along with a notable increase in component richness. By contrast, WNZ-D displayed only a slight reduction in VOC variety but experienced a more significant decline in total VOC content.  
These findings are not entirely congruent with those obtained through HS-GC-IMS, likely due to differences in the target compounds and detection principles of the two methodologies. Therefore, employing a complementary, multi-technique approach is essential for achieving a more comprehensive and nuanced characterization of sample attributes [31; 44].  
Figure 3: Volatile profiles across the four groups detected by HS-SPME-GC-MS. (**A**) Chord plot of aggregate VOC concentrations by category; (**B**) chord plot of total VOC numbers in each category; (**C**) 100% stacked graph of concentration proportions for different VOC categories; (**D**) 100% stacked graph of number proportions for different VOC categories; and (**E**) Venn diagram depicting VOC differences across the four groups.