摘要
Objective: To compare the chemical characters of Sparganii Rhizoma from different areas via chromatographic analysis and to establish a sensitive LC/MS method for quality assessment of Sparganii Rhizoma.Methods: Under the optimised HPLC-PDA chromatographic conditions,twenty batches of Sparganii Rhizoma were analyzed by HPLC fingerprints.Principal component analysis(PCA),orthogonal projections to latent structures discriminant analysis(OPLS-DA)and hierarchical cluster analysis(HCA)were performed based on all peak areas of Sparganii Rhizoma fingerprints.Meanwhile,part of common peaks were subsequently quantified by UFLC-QTRAP-MS.Results: The similarity values of HPLC fingerprints fluctuated in a wide range of 0.511–0.973,which showed variable differences of chemical characters among Sparganii Rhizoma from twenty habitats.PCA,OPLS-DA and HCA indicated that samples could be divided into five groups with different chemical characters,which generally corresponded with their geographical distributions.A total of 31 peaks in HPLC fingerprints were marked,and eight of them were identified and quantified.The quantitative result was generally in agreement with the classifications based on HPLC fingerprints,which indicated that Sparganii Rhizoma samples from eastern China mostly contained more contents including phenolic acids and flavonoids.Conclusion: This study not only proved that there were relationships between geographic distributions and internal chemical compositions of plants,which could provide evidence to the traditional Chinese medicine concept "geo-authentic",but also supplied a sensitive and rapid simultaneous quantitive method for the quality estimation of Sparganii Rhizoma.
Objective: To compare the chemical characters of Sparganii Rhizoma from different areas via chromatographic analysis and to establish a sensitive LC/MS method for quality assessment of Sparganii Rhizoma.Methods: Under the optimised HPLC-PDA chromatographic conditions,twenty batches of Sparganii Rhizoma were analyzed by HPLC fingerprints.Principal component analysis(PCA),orthogonal projections to latent structures discriminant analysis(OPLS-DA)and hierarchical cluster analysis(HCA)were performed based on all peak areas of Sparganii Rhizoma fingerprints.Meanwhile,part of common peaks were subsequently quantified by UFLC-QTRAP-MS.Results: The similarity values of HPLC fingerprints fluctuated in a wide range of 0.511–0.973,which showed variable differences of chemical characters among Sparganii Rhizoma from twenty habitats.PCA,OPLS-DA and HCA indicated that samples could be divided into five groups with different chemical characters,which generally corresponded with their geographical distributions.A total of 31 peaks in HPLC fingerprints were marked,and eight of them were identified and quantified.The quantitative result was generally in agreement with the classifications based on HPLC fingerprints,which indicated that Sparganii Rhizoma samples from eastern China mostly contained more contents including phenolic acids and flavonoids.Conclusion: This study not only proved that there were relationships between geographic distributions and internal chemical compositions of plants,which could provide evidence to the traditional Chinese medicine concept "geo-authentic",but also supplied a sensitive and rapid simultaneous quantitive method for the quality estimation of Sparganii Rhizoma.
作者
Meng-ru Sang
Xiao-long Zhang
Qi-nan Liu
Chan-chan Liu
Yi-ming Xu
Ling-ling Zhao
Qi-nan Wu
Wei Yue
Chuan Chai
Meng-ru Sang, Xiao-long Zhang, Qi-nan Liu, Chan-chan Liu, Yi-ming Xu, Ling-ling Zhao, Qi-nan Wu, Wei Yue, Chuan Chai(a Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, National and Local Collaborative Engineering Center of Chinese Medicinal Resources lndustrializatl"on and Formulae Innovative Medicine, School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023, China b Lianyungang Institute for Drug Control, Lianyungang 222006, Chin)
基金
supported by National Natural Science Foundation of China (81073002)
a Basic Research Program of the Ministry of S&T of China (2015FY111500-110)