地瓜藤的UPLC指纹图谱建立及聚类分析、主成分分析
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篇名: 地瓜藤的UPLC指纹图谱建立及聚类分析、主成分分析
TITLE:
摘要: 目的:建立地瓜藤的超高效液相色谱(UPLC)指纹图谱。方法:采用UPLC法。色谱柱为Waters ACQUITY UPLC BEF C18,流动相为0.2%乙酸水溶液-乙腈(梯度洗脱),检测波长为254 nm,流速为0.1 mL/min,柱温为25 ℃,进样量为2 μL。以14号峰为参照,绘制10批地瓜藤药材样品及2批混淆品的UPLC指纹图谱;采用《中药色谱指纹图谱相似度评价系统》(2012版)进行相似度评价,确定共有峰;采用SPSS 20.0 软件进行聚类分析,运用SIMCA 13.1软件进行主成分分析和正交偏最小二乘法判别分析。结果:10批地瓜藤药材样品共有28个共有峰,相似度在0.839~0.935之间,2批混淆品的相似度分别为0.503、0.173,表明本方法可区别地瓜藤与混淆品。聚类分析和主成分分析结果均显示,10批地瓜藤药材样品可聚为2类,S3~S5、S9、S10聚为一类,其余聚为一类。正交偏最小二乘法判别分析结果显示,共筛选出变量投影值>1的7个成分,这7个成分可能是引起10批地瓜藤药材样品质量差异的主要成分。结论:所建指纹图谱及聚类分析、主成分分析、正交偏最小二乘法判别分析可用于地瓜藤药材的鉴别和质量控制。
ABSTRACT: OBJECTIVE: To establish a UPLC fingerprint of Ficus tikoua. METHODS: UPLC method was adopted. The determination was performed on Waters ACQUITY UPLC BEF C18 column with mobile phase consisted of 0.2% aqueous acetic acid-acetonitrile (gradient elution); the detection wavelength was 254 nm; the flow rate was 0.1 mL/min; the column temperature was 25 ℃, and sample size was 2 μL. UPLC fingerprints of 10 batches of samples and 2 batches of adulterants were determined by using No. 14 peak as reference. The similarity evaluation was carried out by using the TCM Chromatographic Fingerprint Similarity Evaluation System (2012 edition) so as to determine common peak. The cluster analysis was performed by using SPSS 20.0 software. SIMCA 13.1 software was used to conduct the principal component analysis and orthogonal partial least squares discriminant analysis (OPLS-DA). RESULTS: There were 28 common peaks in UPLC fingerprint of 10 batches of F. tikoua. The similarity of 10 batches of F. tikoua was between 0.839 and 0.935, and the similarities of the 2 batches of adulterants were 0.503 and 0.173 respectively, which indicated that F. tikoua could be distinguished from adulterants. 10 batches of F. tikoua could be divided into 2 categories by cluster analysis and principle component analysis, and S3-S5, S9 and S10 were grouped into one category, and the remaining batches were grouped into one category. 7 components with a variable importance in projection (VIP) value >1 were screened by OPLS-DA analysis. These 7 components may be the main components that caused the quality difference of 10 batches of F. tikoua samples. CONCLUSIONS: Established fingerprint, cluster analysis, principle component analysis and OPLS-DA can be used for the identification and quality control of F. tikoua.
期刊: 2019年第30卷第24期
作者: 徐锋,杨澜,成婷婷,黄旭龙,范东生,吴红梅,王祥培
AUTHORS: XU Feng,YANG Lan,CHENG Tingting,HUANG Xulong,FAN Dongsheng,WU Hongmei,WANG Xiangpei
关键字: 地瓜藤;指纹图谱;超高效液相色谱法;聚类分析;主成分分析;正交偏最小二乘法判别分析
KEYWORDS: Ficus tikoua; Fingerprint; UPLC; Cluster analysis; Principle component analysis; OPLS-DA
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