Rapid Identification of Different Parts of Nardostachys jatamansi Based on HS-SPME-GC-MS and Ultra-fast Gas Phase Electronic Nose
10.13422/j.cnki.syfjx.20241262
- VernacularTitle:基于HS-SPME-GC-MS与超快速气相电子鼻的甘松不同部位快速鉴别
- Author:
Tao WANG
1
;
Xiaoqin ZHAO
2
;
Yang WEN
1
;
Momeimei QU
1
;
Min LI
1
;
Jing WEI
1
;
Xiaoming BAO
3
;
Ying LI
1
;
Yuan LIU
1
;
Xiao LUO
2
;
Wenbing LI
1
Author Information
1. College of Pharmacy，College of Grassland Resources，Tibetan Plateau Ethnic Medicinal Resources Protection and Utilization Key Laboratory of National Ethnic Affairs Commission of the People's Republic of China， Sichuan Provincial Qiang-yi Medicinal Resources Protection and Utilization Technology Engineering Laboratory，Southwest Minzu University，Chengdu 610225，China
2. Key Laboratory for Quality Monitoring and Evaluation of Traditional Chinese Medicine， National Medical Products Administration，Chengdu Institute for Drug Control，Chengdu 610045，China
3. Shimadzu Enterprise Management（China） Co. Ltd.，Chengdu 611900，China
- Publication Type:Journal Article
- Keywords:
Nardostachys jatamansi;
differential markers;
rapid identification;
headspace solid-phase microextraction（HS-SPME）;
gas chromatography-mass spectrometry（GC-MS）;
electronic nose
- From:
Chinese Journal of Experimental Traditional Medical Formulae
2025;31(2):182-191
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveTo establish a model that can quickly identify the aroma components in different parts of Nardostachys jatamansi， so as to provide a quality control basis for the market circulation and clinical use of N. jatamansi. MethodsHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） combined with Smart aroma database and National Institute of Standards and Technology（NIST） database were used to characterize the aroma components in different parts of N. jatamansi， and the aroma components were quantified according to relative response factor（RRF） and three internal standards， and the markers of aroma differences in different parts of N. jatamansi were identified by orthogonal partial least squares-discriminant analysis（OPLS-DA） and cluster thermal analysis based on variable importance in the projection（VIP） value >1 and P<0.01. The odor data of different parts of N. jatamansi were collected by Heracles Ⅱ Neo ultra-fast gas phase electronic nose， and the correlation between compound types of aroma components collected by the ultra-fast gas phase electronic nose and the detection results of HS-SPME-GC-MS was investigated by drawing odor fingerprints and odor response radargrams. Chromatographic peak information with distinguishing ability≥0.700 and peak area≥200 was selected as sensor data， and the rapid identification model of different parts of N. jatamansi was established by principal component analysis（PCA）， discriminant factor alysis（DFA）， soft independent modeling of class analogies（SIMCA） and statistical quality control analysis（SQCA）. ResultsThe HS-SPME-GC-MS results showed that there were 28 common components in the underground and aboveground parts of N. jatamansi， of which 22 could be quantified and 12 significantly different components were screened out. Among these 12 components， the contents of five components（ethyl isovalerate， 2-pentylfuran， benzyl alcohol， nonanal and glacial acetic acid，） in the aboveground part of N. jatamansi were significantly higher than those in the underground part（P<0.01）， the contents of β-ionone， patchouli alcohol， α-caryophyllene， linalyl butyrate， valencene， 1，8-cineole and p-cymene in the underground part of N. jatamansi were significantly higher than those in the aboveground part（P<0.01）. Heracles Ⅱ Neo electronic nose results showed that the PCA discrimination index of the underground and aboveground parts of N. jatamansi was 82， and the contribution rates of the principal component factors were 99.94% and 99.89% when 2 and 3 principal components were extracted， respectively. The contribution rate of the discriminant factor 1 of the DFA model constructed on the basis of PCA was 100%， the validation score of the SIMCA model for discrimination of the two parts was 99， and SQCA could clearly distinguish different parts of N. jatamansi. ConclusionHS-SPME-GC-MS can clarify the differential markers of underground and aboveground parts of N. jatamansi. The four analytical models provided by Heracles Ⅱ Neo electronic nose（PCA， DFA， SIMCA and SQCA） can realize the rapid identification of different parts of N. jatamansi. Combining the two results， it is speculated that terpenes and carboxylic acids may be the main factors contributing to the difference in aroma between the underground and aboveground parts of N. jatamansi.
