Materials and chemicals
Forty-five agarwood samples were collected and analyzed. Thirty-one samples were natural agarwood originated from Vietnam, Malaysia, Indonesia, Myanmar, China (Hong Kong, Guangxi, Guangdong, Hainan) and Unknown places; and fourteen samples were artificial agarwood produced from five year-old matured A. sinensis trees. The trees were planted in the experimental base of A. sinensis located in Xinyi, Guangdong, China (22°21′ N, 110°21′ E, height 119 m), and were identified as A. sinensis by Prof. Yan Hanjing (College of Traditional Medicine, Guangdong Pharmaceutical University). The formation of resin in A. sinensis trees was induced by three methods, including physical damage, chemical stimulation and chemical plus fungal stimulation. The physical damage method was carried out by burning. The chemical stimulation was carried out using acetic acid and salicylic acid. The chemical plus fungal stimulation methods were carried out using Fusarium sp. A2, Nigrospora oryzae A8, and Botrysphaeria rhodina A13 (Wang et al., 2009), which were provided and identified by Associate Prof. Li Haohua (Guangdong Institute of Microbiology). Salicylic acid plus fungal liquid fermentation product were slowly injected into the xylem part of the trees according to the method described by Gao et al. . All artificial agarwood samples were harvested after more than 12 months of agarwood induction. The information of all agarwood samples are provided in Supplementary Table A.1.
Chloroform (analytical grade) was purchased from Guangzhou Chemical Reagent Factory (Guangdong Province, China). Alkane standards (C10-C31) were purchased from AccuStandard Inc. (USA)
Sample preparation for E-nose analysis
All agarwood samples were dried at room temperature, smashed into powder and then filtered through 60-mesh sieves. The agarwood powder (10 mg) was weighted and placed in a 20-mL head space bottle. The bottle was sealed and incubated at 100℃ for 30 min; the incense smoke of agarwood generated in the bottle was then used for E-nose analysis.
Apparatus and conditions of E-nose analysis
E-nose analysis was conducted using an ultra-fast gas phase electronic nose Heracles II (Alpha MOS, France) equipped with an MXT-5 nonpolar metallic capillary column ( ), an MXT-1701 polar metallic capillary column ( ), a trap and a flame ionization detector.
The column temperatures were programmed as follows: initial temperature of 50 ℃ was held for 2 s; ramped to 80 ℃ at a rate of 1 ℃/s and held for 5 s; finally ramped up to 250℃ at a rate of 3 ℃/s and held for 21 s. Other operating conditions were as follows: injection volume, 5000 μL; injection speed, 125 μL/s; injector temperature, 200 ℃; trap initial temperature, 40 ℃; trapping duration, 50 s; and FID temperature, 260 ℃.
Processing of E-nose data
To generate the smellprints of agarwood samples, the E-nose data on the incense smokes of 45 agarwood samples were analyzed and processed. The areas of partial chromatographic peaks were used as variables in PCA, which was performed using AlphaSoft statistical software 14.3 (Alpha MOS, France), to obtain the clustering result of 45 agarwood samples.
Sample preparation for GC-MS analysis
All agarwood samples were dried at the room temperature, smashed and then filtered through 60-mesh sieves. The agarwood powder (0.5 g) was extracted with 10 mL of chloroform at room temperature for 24 h. The solvent was evaporated in water bath at 70 ℃ until a viscous semi solid was obtained. The solid was then reconstituted in 1 mL of chloroform in an airtight-sealed vial and stored in darkness at 4 ℃.
Apparatus and conditions of GC-MS analysis
GC-MS analysis were performed using a GCMS QP-2010E (Shimadzu) equipped with an Rtx-5MS capillary fused silica column (30 m × 0.25 mm; I.D. 0.25 μm film thickness; Restek Corp. Bellefonte, USA). Helium was used as the carrier gas and flowed at a flow rate of 1 mL/min. The injection volume was 1 μL, the split ratio was 1:30 and the injector temperature was 260℃. The oven temperatures were programed as follows: initial temperature of 90 ºC was held for 4 min; increased at a rate of 2.5 ºC/min to 160 ºC and held for 5 min; increased at a rate of 0.3 ºC/min to 180 ºC and held for 5 min; increased at a rate of 2.0 ºC/min to 200 ºC; finally increased at a rate of 1º C/min to 230 ºC and held for 120 min. The mass spectra were recorded at a voltage of 70 eV at the m/z range of 50 to 500 amu.
Processing of GC-MS data
The GC-MS data files of all 45 samples were converted into NetCDF files using Shimadzu GCMS Postrun Analysis software. The detection of mass ions, correction of retention time, alignment of mass ions, annotation of the label (mass ions-retention time) of mass ions and calculation of the intensity value of mass ions in the NetCDF files were carried out using XCMS package (R-gui 3.3.1). The XCMS data set containing the label and value of mass ions was saved as “csv” format.
Information value can be used to digitize the importance of variables from binary classification. In this study, The 45 samples were divided based on the clustering result of E-nose, and the information value of the mass ions in the XCMS data set was assigned by Scorecard package (R-gui 3.6.1). The mass ions from the XCMS data set were clustered using ClustOfVar package (R-gui 3.6.1), and the distinct mass ions that had the maximum information value from each cluster were screened. The chromatographic peaks of the featured mass ions were identified based on their retention time in AMDIS. The mass spectral fragmentation patterns were compared with those stored in the NIST Mass Spectral Library (NIST05) to identify compounds that were significant different. The retention index was calculated using a series of n-alkanes (C10-C31).
Decision tree algorithm was used to explain and verify the clustering result of the E-nose data. The classification rule was obtained based on the percentage of the peak area of compounds that were significant different according to the decision tree algorithm. ROC was used to verify the validity of the tree model.