## 4 Materials and Methods
### Detection of Volatile Organic Compounds (VOCs)  
The sample extracts were analyzed using a gas chromatography-mass spectrometry system (GC-MS/MS, 8890-7000D, Agilent, Santa Clara, CA, USA) equipped with a 30 m \(\times\) 0.25 mm \(\times\)0.25 \(\upmu\)m DB-5 MS (5% phenyl-polymethylsiloxane) GC capillary column (Agilent). High purity helium was used as the carrier gas with a constant flow rate of 1.2 mL/min. The injector temperature was maintained at 250 \({}^{\circ}\)C without a shunt, and the solvent delay time was set to 3.5 min. The programmed temperature started at 40 \({}^{\circ}\)C for an initial hold time of 3.5 min, then increased to 100 \({}^{\circ}\)C at a rate of 10 \({}^{\circ}\)C/min, followed by an increase to 180 \({}^{\circ}\)C at a rate of 7 \({}^{\circ}\)C/min, and finally raised to 280 \({}^{\circ}\)C at a rate of 25 \({}^{\circ}\)C/min for a duration of 5 min.  
Mass spectra were recorded in electron impact (EI) ionization mode at 70 eV. The quadrupole mass detector, ion source, and transfer line temperatures were set, respectively, at 150, 230, and 280 \({}^{\circ}\)C. The MS was selected, and the ion monitoring (SIM) mode was used for the identification and quantification of analytes. To ensure the reproducibility of the analytical process, a quality control sample (prepared by blending samples) was incorporated into every 10 test samples during instrumental analysis. Volatile compounds were identified by comparing their mass spectra with the MetWare database ([[http://www.metware.cn/](http://www.metware.cn/)]([http://www.metware.cn/](http://www.metware.cn/)), accessed on 15 November 2023) and linear retention index [71]. The mass spectrum file of the sample was accessed using MassHunter quantitative software B.08.00 for integration and correction. The relative content of metabolites was analyzed using an internal standard semi-quantitative method [72]. 3-Hexanone-2,2,4,4-d4 (CAS No. 24588-54-3) was employed as the isotope internal standard. The calculation of relative content was performed according to the following formula:  
\[X_{i}=\frac{V_{s}\times C_{s}}{V}\times\frac{I_{i}}{I_{s}}\times 10^{-3}\]  
where \(X_{i}\) is the content of compound \(i\) in the sample to be tested (\(\mu\)g/mL); vs. is the volume of internal standard (\(\mu\)L); \(C_{s}\) is the concentration of internal standard (\(\mu\)g/mL); \(V\) is the volume of the sample to be tested (mL); \(I_{i}\) and \(I_{s}\) are the peak areas of the compound and the internal standard in the sample to be tested, respectively. The k-nearest neighbors (KNN) algorithm was employed to impute missing values in quantitative data, followed by the calculation of coefficient of variation (CV) values for quality control (QC) samples. Substances exhibiting CV values below 0.5 were retained. Unsupervised PCA (principal component analysis) was performed by the statistics function promp within R (www.r-project.org, accessed on 1 December 2023). For two-group analysis, differential metabolites were determined by VIP (VIP > 1) and absolute Log2 FC (! Log2 FC! \(\geq\) 1.0). VIP values were extracted from the OPLS-DA result, which also contains score plots, and generated using the R package MetaboAnalystR 4.0 [73].