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应用高效液相色谱法和化学计量学研究藿香正气水指纹图谱
引用本文:张良圣,倪永年. 应用高效液相色谱法和化学计量学研究藿香正气水指纹图谱[J]. 南昌大学学报(理科版), 2007, 31(1): 93-96
作者姓名:张良圣  倪永年
作者单位:南昌大学,化学系,江西,南昌,330031;南昌大学,化学系,江西,南昌,330031;南昌大学,食品科学教育部重点实验室,江西,南昌,330047
基金项目:国家自然科学基金 , 中国科学院长春应用化学研究所电分析化学重点实验室基金 , 湖南大学化学生物传感和计量学重点实验室基金 , 江西省自然科学基金 , 长江学者及创新团队资助项目
摘    要:采用高效液相色谱获得藿香正气水的色谱指纹图谱,利用基于主成分分析的投影判别法和聚类分析法分析实验结果.结果表明,不同厂家生产的藿香正气水存在显著差异,且主成分分析投影判别法和聚类分析法均能对样品进行正确分类,从而建立了识别不同厂家藿香正气水的方法,能有效地控制中药藿香正气水的质量.

关 键 词:高效液相色谱  指纹图谱  藿香正气水  主成分分析  聚类分析
文章编号:1006-0464(2007)01-0093-04
收稿时间:2005-12-05
修稿时间:2005-12-05

Application of High Performance Liquid Chromatography and Chemometrics to Develop the Fingerprint of Huoxiang Zhengqi Tincture
ZHANG Liang-sheng,NI Yong-nian. Application of High Performance Liquid Chromatography and Chemometrics to Develop the Fingerprint of Huoxiang Zhengqi Tincture[J]. Journal of Nanchang University(Natural Science), 2007, 31(1): 93-96
Authors:ZHANG Liang-sheng  NI Yong-nian
Affiliation:a. Department of Chemistry Nanchang University, Nanchang 330031 ; b. Key Laboratory of Food Science of Ministry of Education, Nanchang University, Nanchang 330047, China
Abstract:High performance liquid chromatography was adopted to develop the fingerprint of Huoxiang Zhengqi Tincture.In this study the technique of projection discriminance based on principal component analysis(PCA) and cluster analysis was applied to investigate the experimental data.The results showed that there was obvious difference among the Huoxiang Zhengqi Tincture samples produced by different manufacturers.The technique of projection discriminance based on principal component analysis(PCA) and cluster analysis can be correctly used to distinguish the classes of different samples,which established a method to distinguish Huoxiang Zhengqi Tincture produced by different manufacturers,and the method developed can be effectively used to control the quality of traditional Chinese medicine Huoxiang Zhengqi Tincture.
Keywords:high performance liquid chromatography  fingerprint   Huoxiang Zhengqi Tincture   principal component analysis    cluster analysis
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