色谱

色谱 ›› 2019, Vol. 37 ›› Issue (11): 1235-1240.DOI: 10.3724/SP.J.1123.2019.04007

• 研究论文 • 上一篇    下一篇

基于挥发性组分的气相色谱指纹图谱评价沉香化气片质量

青旺旺1, 施宇涛1, 杨林2, 张芮腾1, 张景勍1, 何丹1   

  1. 1.重庆医科大学药学院, 重庆 400016;
    2.重庆医药高等专科学校药学院, 重庆 401331
  • 收稿日期:2019-04-03 出版日期:2019-11-08 发布日期:2020-12-11
  • 通讯作者: 何丹.E-mail:ildoctor@163.com.
  • 基金资助:
    重庆市重点产业共性关键技术创新专项（cstc2016zdcy-ztzx0016）.

Quality evaluation of Chenxianghuaqi tablets by gas chromatographic fingerprint of volatile components

QING Wangwang1, SHI Yutao1, YANG Lin2, ZHANG Ruiteng1, ZHANG Jingqing1, HE Dan1   

  1. 1. College of Pharmacy, Chongqing Medical University, Chongqing 400016, China;
    2. College of Pharmacy, Chongqing Medical and Pharmaceutical College, Chongqing 401331, China
  • Received:2019-04-03 Online:2019-11-08 Published:2020-12-11
  • Supported by:
    Key Technology Innovation Projects of Key Industries in Chongqing (No. cstc2016zdcy-ztzx0016).

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摘要： 建立了沉香化气片的气相色谱指纹图谱，并结合化学模式识别评价20批沉香化气片的质量。乙醇超声提取20批沉香化气片的挥发性成分，以正十八烷为内标，分析了3个主要组分的含量，且以内标计算其他各组分的相对峰面积，建立了沉香化气片的气相色谱指纹图谱，确定了11个共有峰，得到了各批次样品的相似度，并通过气相色谱-质谱法和对照品比对对10个共有峰进行了指认。将获得的峰面积指纹图谱采用系统聚类分析和主成分分析进行化学模式识别研究，实现了不同批次沉香化气片的区分，发现了造成不同批次样品差异的主要标记物。该方法有效且综合性强，为科学评价与有效控制沉香化气片的质量提供了可靠的参考。

关键词: 气相色谱, 质谱, 指纹图谱, 化学模式识别, 沉香化气片

Abstract: A gas chromatographic fingerprint combined with chemical pattern recognition was successfully developed and applied to assess the quality consistency of 20 Chenxianghuaqi tablets. Volatile components from the 20 Chenxianghuaqi tablets were extracted with ethanol under ultrasonic conditions. n-Octadecane was used as the internal standard to calculate the amounts of the three main components and to confirm the relative peak areas of the other components. Gas chromatographic fingerprints of the 20 Chenxianghuaqi tablets were established. There were 11 common peaks in the fingerprints, and the similarity of each batch of samples was obtained. Ten common peaks were identified by gas chromatography-mass spectrometry, with reference comparison. The obtained fingerprints were used for the chemical pattern recognition, including hierarchical cluster analysis and the principal component analysis. Different batches of Chenxianghuaqi tablets could be differentiated effectively, and major markers that led to differences among the sample batches were identified. The method proposed in this study is comprehensive and reliable, and it can be used as a valuable reference to evaluate and control the quality of Chenxianghuaqi tablets.

Key words: gas chromatographic (GC), mass spectrometry (MS), fingerprint, chemical pattern recognition, Chenxianghuaqi tablet

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