Identification of Dalbergia odorifera and Its Counterfeits by HS-GC-MS
10.13422/j.cnki.syfjx.20240164
- VernacularTitle:基于HS-GC-MS的降香真伪鉴别
- Author:
Li ZHAO
1
;
Xiaowei MENG
1
;
Jiarong LI
1
;
Qing ZHU
1
;
Xianwen WEI
1
;
Ronghua LIU
1
;
Lanying CHEN
2
Author Information
1. School of Pharmacy，Jiangxi University of Chinese Medicine，Nanchang 330004，China
2. National Engineering Research Center for Manufacturing Technology of Solid Preparation of Traditional Chinese Medicine，Jiangxi University of Chinese Medicine，Nanchang 330006，China
- Publication Type:Journal Article
- Keywords:
Dalbergia odorifera;
authentication;
headspace gas chromatography-mass spectrometry（HS-GC-MS）;
volatile components;
principal component analysis（PCA）;
orthogonal partial least squares-discriminant analysis（OPLS-DA）
- From:
Chinese Journal of Experimental Traditional Medical Formulae
2024;30(2):156-163
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveTo screen the differential markers by analyzing volatile components in Dalbergia odorifera and its counterfeits， in order to provide reference for authentication of D. odorifera. MethodThe volatile components in D. odorifera and its counterfeits were detected by headspace gas chromatography-mass spectrometry（HS-GC-MS）， and the GC conditions were heated by procedure（the initial temperature of the column was 50 ℃， the retention time was 1 min， and then the temperature was raised to 300 ℃ at 10 ℃ for 10 min）， the carrier gas was helium， and the flow rate was 1.0 mL·min-1， the split ratio was 10∶1， and the injection volume was 1 mL. The MS conditions used electron bombardment ionization（EI） with the scanning range of m/z 35-550. The compound species were identified by database matching， the relative content of each component was calculated by the peak area normalization method， and principal component analysis（PCA）， orthogonal partial least squares-discrimination analysis（OPLS-DA） and cluster analysis were performed on the detection results by SIMCA 14.1 software， and the differential components of D. odorifera and its counterfeits were screened out according to the variable importance in the projection（VIP） value>2 and P<0.05. ResultA total of 26， 17， 8， 22， 24 and 7 volatile components were identified from D. odorifera， D. bariensis， D. latifolia， D. benthamii， D. pinnata and D. cochinchinensis， respectively. Among them， there were 11 unique volatile components of D. odorifera， 6 unique volatile components of D. bariensis， 3 unique volatile components of D. latifolia， 6 unique volatile components of D. benthamii， 8 unique volatile components of D. pinnata， 4 unique volatile components of D. cochinchinensis. The PCA results showed that， except for D. latifolia and D. cochinchinensis， which could not be clearly distinguished， D. odorifera and other counterfeits could be distributed in a certain area， respectively. The OPLS-DA results showed that D. odorifera and its five counterfeits were clustered into one group each， indicating significant differences in volatile components between D. odorifera and its counterfeits. Finally， a total of 31 differential markers of volatile components between D. odoriferae and its counterfeits were screened. ConclusionHS-GC-MS combined with SIMCA 14.1 software can systematically elucidate the volatile differential components between D. odorifera and its counterfeits， which is suitable for rapid identification of them.
