牡丹皮药材的HPLC指纹图谱建立和聚类分析
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篇名: 牡丹皮药材的HPLC指纹图谱建立和聚类分析
TITLE:
摘要: 目的:建立牡丹皮药材的高效液相色谱(HPLC)指纹图谱,并进行聚类分析。方法:采用HPLC法,色谱柱为Ecosil C18,流动相为0.2%甲酸溶液-乙腈(梯度洗脱),流速为1.0 mL/min,柱温为25 ℃,进样量为10 μL。以丹皮酚为参照,绘制69批(S1~S69)药材样品的HPLC图谱,采用《中药色谱指纹图谱相似度评价系统(2004 A)》进行相似度评价,确定共有峰。采用HPLC-质谱(MS)法鉴定共有峰对应成分[HPLC条件同上;MS条件为电喷雾离子源,正、负离子模式检测,扫描范围为m/z 100~1 200,干燥气为N2(纯度:99.999 9%),干燥气流速为15 L/min,干燥气温度为350 ℃,碰撞低能量为4 V,碰撞高能量为10~40 V]。采用SPSS 20.0软件对69批药材样品进行聚类分析。结果:69批药材样品的HPLC图谱有29个共有峰,除6批药材样品外其余样品相似度均大于0.900。采用HPLC-MS法鉴定出29个共有峰的对应成分。69批药材样品可聚为5类,其中,S19、S22、S26、S29、S30、S33、S34、S38、S43、S46、S49~S51、S53、S56、S57、S64、S65聚为Ⅰ类,S4~S6、S41聚为Ⅱ类,S1~S3、S7~S10、S12、S24、S25、S54、S59聚为Ⅲ类,S15、S23、S35~S37、S39、S40、S47、S48、S52、S58、S66、S67、S69聚为Ⅳ类,S11、S13、S14、S16~S18、S20、S21、S27、S28、S31、S32、S42、S44、S45、S55、S60~S63、S68聚为Ⅴ类。结论:所建HPLC指纹图谱、成分鉴定和聚类分析结果可为牡丹皮药材的真伪鉴别和质量评价提供依据。
ABSTRACT: OBJECTIVE: To establish HPLC fingerprint of Paeonia suffruticosa, and to conduct cluster analysis. METHODS: HPLC-MS was adopted. The determination was performed on Ecosil C18 column with mobile phase consisted of 0.2% formic acid solution-acetonitrile (gradient elution) at the flow rate of 1.0 mL/min. The column temperature was 25 ℃. The sample size was 10 μL. With the reference of paeonol, HPLC chromatograms of 69 batches of samples (S1-S69) were determined. The similarity evaluation was conducted by Similarity Evaluation System for Chromatographic Fingerprint of TCM (2004 A edition). The common peaks were further identified. Corresponding compenents of commen peaks were identified by HPLC-MS [same HPLC condition as above; MS condition included ESI, positive and negative ion model, mass scanning range of m/z 100-1 200, dry gas of N2 (99.999 9%), dry gas velocity of 15 L/ min, dry gas temperature of 350 ℃, collision energy of 4 V, and the collision energy of 10-40 V]. Cluster analysis was carried out by using SPSS 20.0 statistical software. RESULTS: There were 29 common peaks in HPLC chromatograms of 69 batches of samples, and the similarity was more than 0.900 cexcept for 6 batches of samples; the corresponding components of 24 peaks were identified totally by using HPLC method. 69 batches of samples were divided into 5 categories. S19, S22, S26, S29, S30, S33, S34, S38, S43, S46, S49-S51, S53, S56, S57, S64, S65 could be grouped into category Ⅰ; S4-S6, S41 could be grouped into category Ⅱ; S1-S3, S7-S10, S12, S24, S25, S54, S59 could be grouped into category Ⅲ; S15, S23, S35-S37, S39, S40, S47, S48, S52, S58, S66, S67, S69 could be grouped into category Ⅳ; S11, S13,S14, S16-S18, S20, S21, S27, S28, S31, S32, S42, S44, S45, S55, S60-S63, S68 could be grouped into category Ⅴ. CONCLUSIONS: The established HPLC fingerprint, component identification and cluster analysis can provide reference for identification and quality evaluation of P. suffruticosa.
期刊: 2018年第29卷第24期
作者: 侯锡鸿,葛梅,张迎春,曾忠良
AUTHORS: HOU Xihong,GE Mei,ZHANG Yingchun,ZENG Zhongliang
关键字: 牡丹皮;高效液相色谱法;指纹图谱;丹皮酚;聚类分析
KEYWORDS: Paeonia suffruticosa; HPLC; Fingerprint; Paeonol; Cluster analysis
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