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花椒HPLC指纹图谱建立及指标性成分的测定
引用本文:张萌萌,李朝敏,吴博,卢烽,吴纯洁.花椒HPLC指纹图谱建立及指标性成分的测定[J].中国调味品,2019(3):152-155,184.
作者姓名:张萌萌  李朝敏  吴博  卢烽  吴纯洁
作者单位:成都中医药大学药学院
基金项目:四川省特色经济林资源平台建设与共享(2018TJPT0038)
摘    要:文章采用HPLC法建立多批次花椒指纹图谱,并测定其主要成分含量。指纹图谱的色谱条件为Wondasil C18色谱柱(250mm×4.6mm,5μm),乙腈-水梯度洗脱,检测波长268nm,柱温30℃,流量0.8mL/min。以其指纹图谱为特征,进行相似度和聚类分析。指纹图谱确定了12个共有峰,所有样品的相似度均大于0.9,表明各产地花椒具有较好的一致性;当类间距离为10时,16批次花椒样品被分成3大类;花椒的2个主要成分羟基-α-山椒素的含量在0.323%~1.570%,羟基-β-山椒素的含量在0.03%~0.622%。花椒样品各批次间指纹图谱和主要成分含量均有一定的差异。建立的花椒HPLC指纹图谱及主要成分含量测定方法可为花椒食品质量控制和评价提供科学依据。

关 键 词:花椒  HPLC指纹图谱  相似度  聚类分析  质量评价

Establishment of HPLC Fingerprint of Z.bungeanum and Determination of Main Components
ZHANG Meng-meng,LI Chao-min,WU Bo,LU Feng,WU Chun-jie.Establishment of HPLC Fingerprint of Z.bungeanum and Determination of Main Components[J].China Condiment,2019(3):152-155,184.
Authors:ZHANG Meng-meng  LI Chao-min  WU Bo  LU Feng  WU Chun-jie
Affiliation:(School of Pharmacy,Chengdu University of Traditional Chinese Medicine,Chengdu 611137,China)
Abstract:The fingerprint of Zanthoxylum bungeanum is established using HPLC method,and the content of main components is determined.The chromatographic conditions of fingerprint are as follows:Wondasil C18 column(250 mm×4.6 mm,5μm),gradient elution with acetonitrile-water,detection wavelength is 268 nm,temperature is 30℃and flow rate is 0.8 mL/min.The similarity and cluster analysis are conducted by fingerprints.12 common peaks are identified by fingerprints,and the similarity of various batches of Z.bungeanum all reaches 0.9;all samples are divided into 3 categories by cluster analysis when the distance between groups is10;the content of the main components hydroxy-α-sanshool is 0.323%~1.570%and hydroxy-β-sanshool is 0.03%~0.622%.There are some differences in fingerprints and main components among pepper samples.The HPLC fingerprint of Z.bungeanum is simple and fast,and the fingerprint and content determination has provided a scientific basis for the quality control and evaluation of Z.bungeanum.
Keywords:Z  bungeanum  HPLC fingerprint  similarity  hierarchical cluster  quality control
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