| 引用本文: | 买吐送·居买,古丽阿曼·居麦,马依努尔·拜克力,买吾兰江·买提努尔.孜然挥发油GC-MS指纹图谱的构建及主成分分析和聚类分析[J].中国现代应用药学,2022,39(3):370-375. |
| JUMAI Maitusong,JUMAIGuli'aman,BAKRI Mahinur,MAITINUER Maiwulanjiang.Construction of GC-MS Fingerprint of Cuminum Cyminum L. Volatile Oil and Principal Component Analysis and Cluster Analysis[J].Chin J Mod Appl Pharm(中国现代应用药学),2022,39(3):370-375. |
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| 摘要: |
| 目的 采用GC-MS指纹图谱并结合多元统计等方法评价不同产地孜然质量。方法 采用气相色谱-四极杆飞行时间质谱（GC-Q-TOF/MS）技术对孜然挥发油进行定性和定量分析，建立20批不同产地孜然的指纹图谱；运用"中药色谱指纹图谱相似度评价系统软件（2012年版）"进行相似度评价，并进行聚类分析和主成分分析。结果 建立的指纹图谱确定了33个共有峰，相似度均>0.961，主要成分包括枯茗醛、γ-松油烯-7-醛、α-松油烯-7-醛、γ-松油烯、o-伞花烃、桧烯、枯茗醇、3-p-孟烯-7-醛等，其相对含量约占总含量的99.7%。通过聚类分析可将20批孜然分为5大类。主成分分析得到4个主成分的累积方差贡献率为88.946%，其结果显示S20号样品综合得分较高。主成分分析与聚类分析结果基本一致。结论 该方法特征性强，仪器精密度、重复性和稳定性良好，可用于孜然挥发油及其相关产品的质量控制和评价。 |
| 关键词: 孜然 挥发油 气相色谱-四极杆飞行时间质谱 指纹图谱 主成分分析 聚类分析 |
| DOI：10.13748/j.cnki.issn1007-7693.2022.03.014 |
| 分类号:R284.1 |
| 基金项目:中国科学院“西部之光”人才培养计划项目（2020-JCTD-001，2018-XBQNXZ-BB-001） |
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| Construction of GC-MS Fingerprint of Cuminum Cyminum L. Volatile Oil and Principal Component Analysis and Cluster Analysis |
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JUMAI Maitusong1,2,3, JUMAIGuli'aman3, BAKRI Mahinur1, MAITINUER Maiwulanjiang1
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1.State Key Laboratory Basis of Xinjiang Indigenous Medicinal Plants Resource Utilization, Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi 830011, China;2.Chinese Academy of Sciences, Beijing 100039, China;3.College of Xinjiang Uyghur Medicine, Hotan 848000, China
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| Abstract: |
| OBJECTIVE To evaluate the quality of Cuminum Cyminum L. from different producing areas by using GC-MS fingerprints combining with multivariate statistical methods. METHODS GC-Q-TOF/MS was used to qualitatively and quantitatively analyze the Cuminum Cyminum L. volatile oil, and the fingerprints of 20 batches of Cuminum Cyminum L. from different origins were established. The "Chinese medicine chromatographic fingerprint similarity evaluation system software(2012 edition)" was used to evaluate the similarity, and perform cluster analysis and principal component analysis were carried out. RESULTS The established fingerprint spectrum identified 33 common peaks. The similarities were all above 0.961, and the main components were cumaldehyde, γ-terpinen-7-al, α-terpinen-7-al, γ-terpinene, o-cymene, sabinene, cumic alcohol, 3-p-menth-7-al, etc. The relative content accounts for about 99.7% of the total content. Through cluster analysis, 20 batches of Cuminum Cyminum L. could be divided into 5 categories, and the cumulative variance contribution rate of 4 principal components obtained by principal component analysis was 88.946%. The results of principal component analysis showed that the comprehensive score of sample S20 was high, and the results of principal component analysis and cluster analysis were basically consistent. CONCLUSION The method has strong characteristics, good precision, repeatability and stability, and can be used for quality control and evaluation of Cuminum Cyminum L. volatile oil and related products. |
| Key words: Cuminum Cyminum L. essential oil GC-Q-TOF/MS fingerprint cluster analysis principal component analysis |
