title: Combinative Method Using Multi-components Quantitation and HPLC Fingerprint for Comprehensive Evaluation ofGentiana crassicaulis.
abstract: BACKGROUND
  Gentiana crassicaulis() is an important traditional Chinese herb. Like other herbs, its chemical compounds vary greatly by the environmental and genetic factors, as a result, the quality is always different even from the same region, and therefore, the quality evaluation is necessary for its safety and effective use. In this study, a comprehensive method including HPLC quantitative analysis and fingerprints was developed to evaluate the quality of Cujingqinjiao and to classify the samples collected from Lijiang City of Yunnan province. A total of 30 common peaks including four identified peaks, were found, and were involved for further characterization and quality control of Cujingqinjiao. Twenty-one batches of samples from Lijiang City of Yunnan Province were evaluated by similarity analysis (SA), hierarchical cluster analysis (HCA), principal component analysis (PCA) and factor analysis (FA) according to the characteristic of common peaks.
  
  
  RESULTS
  The obtained data showed good stability and repeatability of the chromatographic fingerprint, similarity values were all more than 0.90. This study demonstrated that a combination of the chromatographic quantitative analysis and fingerprint offered an efficient way to quality consistency evaluation of Cujingqinjiao. Consistent results were obtained to show that samples from a same origin could be successfully classified into two groups.
  
  
  CONCLUSIONS
  This study revealed that the combinative method was reliable, simple and sensitive for fingerprint analysis, moreover, for quality control and pattern recognition of Cujingqinjiao.
  
  
  CONCLUSIONS
  HPLC quantitative analysis and fingerprints was developed to evaluate the quality ofGentiana crassicaulisSimilarity analysis, hierarchical cluster analysis, principal component analysis and factor analysis were employed to analysis the chromatographic dataset.The results of multi-components quantitation analysis, similarity analysis, hierarchical cluster analysis, principal component analysis and factor analysis were consistent.All samples could be classified into two groups, which could to some extent reflect the quality differences of theses samples.Abbreviations used:SA: Similarity analysis, HCA: Hierarchical cluster analysis, PCA :Principal component Analysis, FA :Factor analysis.
authors.affiliation: College of Chemistry, Leshan Normal University, Leshan, P.R. China.
authors.forename: Jiuhua
authors.initials: J
authors.lastname: Song
authors.affiliation: College of Chemistry, Leshan Normal University, Leshan, P.R. China.
authors.forename: Fengzheng
authors.initials: F
authors.lastname: Chen
authors.affiliation: College of Agronomy, Sichuan Agriculture University, Wenjiang, P.R. China.
authors.forename: Jiang
authors.initials: J
authors.lastname: Liu
authors.affiliation: College of Agronomy, Sichuan Agriculture University, Wenjiang, P.R. China.
authors.forename: Yuanfeng
authors.initials: Y
authors.lastname: Zou
authors.affiliation: College of Chemistry, Leshan Normal University, Leshan, P.R. China.
authors.forename: Yun
authors.initials: Y
authors.lastname: Luo
authors.affiliation: College of Agronomy, Sichuan Agriculture University, Wenjiang, P.R. China.
authors.forename: Xiaoyan
authors.initials: X
authors.lastname: Yi
authors.affiliation: College of Agronomy, Sichuan Agriculture University, Wenjiang, P.R. China.
authors.forename: Jie
authors.initials: J
authors.lastname: Meng
authors.affiliation: College of Agronomy, Sichuan Agriculture University, Wenjiang, P.R. China.
authors.forename: Xingfu
authors.initials: X
authors.lastname: Chen
keywords: Gentiana crassicaulis; HPLC fingerprint; multi-components quantitation; quality evaluation