Establishment of HPLC Fingerprints of Paeonia tactilora Decoction Pieces and Its Cluster Analysis and Principal Component Analysis
- VernacularTitle:白芍饮片的HPLC指纹图谱建立及聚类分析、主成分分析
- Author:
Xiumin LIN
1
;
Zhenling ZHANG
1
;
Shengchao WANG
1
;
Mengzhen YAN
1
;
Yitian CHEN
1
;
Jiangshan ZHANG
1
Author Information
1. College of Pharmacy，Henan University of TCM，Zhengzhou 450046，China
- Publication Type:Journal Article
- Keywords:
Paeonia tactilora decoction pieces;
HPLC;
Fingerprint;
Cluster analysis;
Principal component analysis
- From:
China Pharmacy
2019;30(24):3375-3382
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE： To establish HPLC fingerprints of Paeonia tactilora decoction pieces， and to conduct its cluster analysis and principal component analysis. METHODS： HPLC method was adopted. The determination was performed on SunFire® C18 column with mobile phase consisted of acetonitril-0.05％ phosphoric acid solution （gradient elution） at the flow rate of 1.0 mL/min. The detection wavelength was set at 230 nm， the column temperature was 30 ℃， the collection time was 70 min，and sample size was 15 μL. Using paeoniflorin as reference， HPLC fingerprints of 26 batches P. tactilora decoction pieces from different habitats and 30 batches by different processed methods were established. The similarity of samples was evaluated by TCM Chromatographic Fingerprint Similarity Evaluation System （2012 edition） to confirm common peak. Cluster analysis and principal component analysis were performed by using SPSS 20.0 software. RESULTS： There were 9 common peaks in HPLC fingerprints of 26 batches of sample from different habitats， the similarity of which was higher than 0.880. Six peaks were identified， including gallic acid， catechin， albiflorin， paeoniflorin， 1，2，3，4，6-pentagalloylglucose and benzoylpaeoniflorin. Cluster analysis showed that 26 batches of samples were clustered into 2 categories when cosine distance was 15. S1-S21 were clustered into one category； S22-S26 were clustered into the other category. By principal component analysis， the accumulative contribution rate of two main components was 81.124％. There were 10 common peaks in HPLC fingerprints of 30 batches of sample by different processed methods， the simi- larity of which was higher than 0.970. Seven peaks were identified， including gallic acid， catechin， aplopaeonoside， albiflorin， paeoniflorin， 1，2，3，4，6-pentagalloylglucose and benzoylpaeoniflorin. Cluster analysis showed that 30 batches of samples were clustered into 2 categories when cosine distance was 25. B1-B10 were clustered into one category； C1-C10 and J1-J10 were clustered into the other category. By principal component analysis， the accumulative contribution rate of four main components was 86.887％. CONCLUSIONS： Established HPLC fingerprint， the results of cluster analysis and principal component analysis can provide reference for quality control of decoction pieces of P. tactilora.
