## 3 Results
### Volatile Components of NGBTs
#### 3.2.2 Screening for Volatile Substances  
Multivariate analysis using PCA and OPLS-DA was conducted to elucidate volatile compound disparities among the five NGBTs. Both PCA and OPLS-DA score plots revealed clear separation among all samples (Figure 5A,B), confirming significant inter-group differences in volatile profiles. Permutation testing (200 iterations, Q2-intercept = \(-\)0.827) validated the OPLS-DA model's reliability without overfitting (Figure 5C).  
Fourteen compounds exhibited VIP > 1, identifying them as primary discriminants: Geraniol, Methyl salicate, Linalool, (_E_)-Geranic acid methyl ester, (_E_)-Pyranoid linalool oxide, \(\beta\)-Myrrene, (_E_)-Furan linalool oxide, Phenylacetaldehyde, Benzyl alcohol, (_Z_)-Linalool oxide, Linalool oxide pyranoid, Phenethyl alcohol, Geranic acid, and (_Z_)-Jasmone. Among these, eight compounds demonstrated dual significance by satisfying both VIP > 1 and OAV > 1 criteria (Figures 6 and S1)--namely Geraniol, Methyl salicate, Linalool, \(\beta\)-Myrrene, Benzyl alcohol, (_Z_)-Linalool oxide, Phenethyl alcohol, and (_Z_)-Jasmone--suggesting their joint role as chemical and sensory discriminants (Tables 1 and 2).  
Figure 4: Aroma profile in the 5 NGBTs. (**A**) Volatile substances (left) and proportion (right) stack chart of 5 NGBTs. (**B**) Volatile substance Venn diagram of 5 NGBTs. (**C**) Heat map of 13 common volatile substances.  
Figure 5: Multivariate statistical analysis of volatile components in the 5 NGBTs. (**A**) PCA score plot, the dashed circle represents the 95% confidence range; (**B**) OPLS\(-\)DA score plot; (**C**) cross\(-\)validation results: the intercept of the Q2 regression line of the cross-validation model with 200 tests of alignment was less than 0, indicating that the OPLS\(-\)DA discriminant model was not overfitted and the model was relatively reliable.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**No.** & **Volatile Compound** & **Odor Type** & **VIP 1** & _p-Value 2_ &
\begin{tabular}{c} **OT 3** \\ **(ug/kg)** \\ \end{tabular} \\ \hline
1 & Geraniol & sweet, floral, fruity, rose, waxy, citrus & 5.36 & 0.000 ** & 1 \\
2 & Methyl salicate & pepppermit, wintergreen mint & 3.80 & 0.000 ** & 40 \\
3 & Linalool & floral, green, fruity & 3.76 & 0.000 ** & 1 \\
4 & (_E_)-Geranic acid methyl ester & n.f. & 2.24 & 0.000 ** & n.f. \\
5 & (_E_)-pyramid linalool oxide & w woody & 2.15 & 0.000 ** & 320 \\
6 & \(\beta\)-Myrence & musty, basamic, spice & 2.04 & 0.000 ** & 15 \\
7 & (_E_)-Furan linalool oxide & flowery & 1.94 & 0.000 ** & 320 \\
8 &henylacetaldehyde & floral, honey, rose, cherry & 1.79 & 0.001 ** & 6.3 \\
9 & Benzyl alcohol & floral, rose, phenol, basamic & 1.62 & 0.000 ** & 100 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Volatile compounds with VIP \(>\) 1 in OPLS-DA.  
Figure 6: Key compounds with both OAV \(>\) 1 and VIP \(>\) 1 in the 5 NGBTs, different letters indicate statistically significant differences according to one-way ANOVA.  
Sample-specific patterns emerged with JSH, exhibiting significantly elevated Geraniol, \(\beta\)-Myrcene, Benzyl alcohol, and Phenethyl alcohol (\(p<0.01\) versus other NGBTs), DXY showing dominant Methyl salicylate levels, DXE containing the highest (\(Z\))-Linalool oxide, and YHJ characterized by exceptionally high Linalool abundance. These differentially abundant compounds are robust discrimination markers for NGBTs' authentication and flavor profiling.