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1.齐鲁工业大学(山东省科学院) 山东省分析测试中心 山东省大型精密分析仪器应用技术重点实验室,山东 济南 250014
2.齐鲁工业大学(山东省科学院) 药学院 山东省高等学校天然药物活性成分研究重点实验室, 山东 济南 250014
赵恒强,博士,副研究员,研究方向:中药分析与质量控制研究,E-mail:hqzhao2007@163.com
纸质出版日期:2024-11-15,
收稿日期:2024-03-12,
修回日期:2024-04-29,
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胡思萌,郭焕滢,卢恒,刘伟,王晓,赵恒强.基于GC-IMS联合多元统计分析的泰山黄精真实性评估[J].分析测试学报,2024,43(11):1843-1850.
HU Si-meng,GUO Huan-ying,LU Heng,LIU Wei,WANG Xiao,ZHAO Heng-qiang.Authenticity Evaluation of Polygonatum Sibiricum from Mount Tai Based on GC-IMS Combined with Multivariate Statistical Analysis[J].Journal of Instrumental Analysis,2024,43(11):1843-1850.
胡思萌,郭焕滢,卢恒,刘伟,王晓,赵恒强.基于GC-IMS联合多元统计分析的泰山黄精真实性评估[J].分析测试学报,2024,43(11):1843-1850. DOI: 10.12452/j.fxcsxb.24031203.
HU Si-meng,GUO Huan-ying,LU Heng,LIU Wei,WANG Xiao,ZHAO Heng-qiang.Authenticity Evaluation of Polygonatum Sibiricum from Mount Tai Based on GC-IMS Combined with Multivariate Statistical Analysis[J].Journal of Instrumental Analysis,2024,43(11):1843-1850. DOI: 10.12452/j.fxcsxb.24031203.
采用气相色谱-离子迁移谱(GC-IMS)对泰山黄精的挥发性成分进行鉴定,并利用多元统计分析对泰山黄精和来源于秦岭的黄精进行区分。通过仪器自带的LAV插件生成样品的Gallery Plot可视化指纹图谱,利用气相色谱保留指数数据库(NIST)和迁移时间数据库(IMS)进行定性分析。通过主成分分析(PCA)和正交偏最小二乘分析(OPLS-DA)对60批不同产地的黄精样品
进行区分,采用变量投影重要性(VIP)和
t
-检验筛选差异成分。从泰山黄精中共鉴定出72个挥发性成分,包括19个醛类、13个酯类、12个酮类、13个醇类、9个萜类及6个其他类成分。采用多元统计分析实现了泰山黄精和秦岭黄精的有效区分,并筛选出20种差异成分(VIP
>
1.2,
P
<
0.05),主要为醛类及酮类化合物。聚类热图分析表明,上述20种差异成分可以体现泰山、秦岭来源黄精的特征性,有望作为标记物用于其产地区分。该研究为泰山黄精的真实性评估及质量控制提供了方法和数据支持。
The volatile components of
Polygonatum sibiricum
from Mount Tai were identified by gas chromatography-ion mobility spectrometry (GC-IMS),and 60 batches
Polygonatum sibiricum
from Mount Tai and Qinling Mountains were distinguished by GC-IMS combined with multivariate statistical analysis. The volatile components visible fingerprint of the samples were generated by LAV plug-in of the instrument,and qualitative analysis was carried out by the built-in NIST gas chromatography retention index database and IMS migration time database. The principal component analysis (PCA) and orthogonal partial least squares analysis(OPLS-DA) were employed to distinguish
Polygonatum sibiricum
samples from different regions,and VIP and
t
-test were used to screen the differential components. A total of 72 volatile components were identified from
Polygonatum sibiricum
,including 19 aldehydes,13 esters,12 ketones,13 alcohols,9 terpenoids and 6 others. Among the identified volatile components,the number of aldehydes is large,accounting for 26.4% of the known substances detected. PCA analysis showed that
Polygonatum sibiricum
from Mount Tai could be well clustered together,which indicated that the volatile components in
Polygonatum sibiricum
samples from this area were similar. The
Polygonatum sibiricum
samples from Mountain Tai and Qinling Mountains could be well classified via combining GC-IMS and OPLS-DA method,and 20 differential components (VIP
>
1.2,
P
<
0. 05) were screened out,mainly aldehydes and ketones. The contents of 2-methylbutyric
acid,2-methyl-1-propanol,hydroxyacetone,2-methyltetrahydrofuran-3-one and 3-hydroxy-2-butanone are higher in
Polygonatum sibiricum
from the Mount Tai. The results of clustering heat map analysis verified that these 20 components in
Polygonatum sibiricum
from different regions could reflect the characteristics of
Polygonatum sibiricum
from Mount Tai and Qinling Mountains,which are expected to be used as markers for the identification of
Polygonatum sibiricum
from Mount Tai. At the same time,the experimental results show that GC-IMS technology has the characteristics of simple sample pretreatment and strong visualization,and it can more intuitively represent the composition and content difference of volatile components. This study provided method and data support for the authenticity evaluation and quality control of
Polygonatum sibiricum
from Mount Tai.
气相色谱-离子迁移谱黄精挥发性成分产地区分多元统计分析
gas chromatography-ion mobility spectrometryPolygonatum sibiricumvolatile componentsorigin distinctionmultivariate statistical analysis
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