摘要
本文采用GC-MS建立8个不同产地22种陈皮挥发油的指纹图谱,选取了其中的7个色谱峰作为共有模式图的特征峰(左旋-alpha-蒎烯、β-蒎烯、β-月桂烯、邻异丙基甲苯、D-柠檬烯、萜品烯和异松油烯),并将指纹图谱的共有特征峰和一些微量成分作为主成分分析法(PCA)的分析数据源,应用相似度分析法和PCA统计分析法找出22种陈皮挥发油之间的相似性及差异性。结果表明,22种陈皮挥发油的相似度在0.886~1之间,来自广东四会、四川、江西南丰、广东新会和广西-桂林的样品获得了良好的区分,而来自广东云浮、广西梧州和广东清远这3个产地的样品聚成了一类,最终确定共有峰中左旋-α-蒎烯、α-法尼烯、β-蒎烯和微量组分中的大根香叶烯为显著贡献的主成分组分。根据主成分组分的含量变化能显著区分陈皮挥发油的不同产地,本研究可对陈皮挥发油质量的整体控制及其制剂的质量评价有一定的指导作用。
The chromatographic fingerprints of 22 types of tangerine peel volatile oils from eight different regions were established by gas chromatography-mass spectrometry(GC-MS) in this study.Seven volatile components(L-α-pinene,β-pinene,β-myrcene,o-cymene,D-limonene,terpinene,and terpinolene) were identified as common characteristic peaks.These seven identified peaks and some trace elements were used as the data sources for principal component analysis(PCA).PCA and semblance analysis methods were applied to assess similarities and differences among 22 types of tangerine peel volatile oils.The results showed that the similarities of the oils ranged between 0.886-1.The samples from Sihui,Szechwan,Nanfeng,Xinhui,and Guiling were well distinguished,and the samples from Yunfu,Wuzhou,and Qingyuan were grouped in one cluster.The L-α-pinene,α-farnesene,and β-pinene common characteristic peaks and germacrene from the trace composition in the fingerprints were determined as the principal components with a significant contribution.The changes in the content of the main components could be used to distinguish the origin of the samples,and this study provides guidance for the overall quality control of tangerine peel volatile oils and the quality evaluation of their preparation.
作者
陈彤
曹庸
刘飞
郭斌
CI-IEN Tong CAO Yong LIU Fei GUO Bin(Engineering Research Center for Natural Actives, College of Food Science, South China Agricultural University, Guangzhou 510642, China)
出处
《现代食品科技》
EI
CAS
北大核心
2017年第2期217-222,216,共7页
Modern Food Science and Technology
基金
广东省科技厅应用型科技研发专项资金项目(2015B020230008)
关键词
陈皮挥发油
GC-MS指纹图谱
主成分分析法
质量评价
volatile oil of tangerine peel
gas chromatography mass spectrometry fingerprint
principal component analysis
quality evaluation