张碧云^1，2，刘王梅^1，2，程俊文¹，魏海龙¹，吴德平³，林文飞³，王衍彬¹，贺 亮^1*

（1.浙江省森林资源生物与化学利用重点实验室，浙江省林业科学研究院，浙江杭州 310023；

2.浙江科技学院 生物与化学工程学院，浙江杭州 310023；

3 浙江大学 生命科学学院，浙江杭州 310058）

摘要：通过气相色谱-质谱法鉴定不同产地桑黄的挥发性成分，建立桑黄的指纹图谱，并对不同产地桑黄的成分进行比较分析。应用乙醚及乙酸乙酯作萃取剂进行超声提取，采用气相色谱-质谱法对提取物进行鉴定，峰面积法测定各成分的含量；利用聚类分析法和主成分分析法进行分析。气相色谱-质谱法鉴别得到27种桑黄有效成分及其含量，包括酯类、酮类、甾醇类等；聚类分析结果将桑黄大致分为3类；主成分分析提取了两个特征值大于1的主成分，第一主成分特征值为8.943，贡献率为59.619％；第二主成分特征值为3.106，贡献率为20.709％，总共包括了桑黄样品中80.329％的信息，成分得分情况对区分不同地区桑黄的成分提供数据支持。此法简单、准确、有效，峰分离度较好，可以有效鉴别及比较分析不同产地桑黄的成分差异。

关键词：桑黄；气相色谱-质谱；指纹图谱；主成分分析；聚类分析

中图分类号：TS207.3   文献标识码：A   文章编号：1674-506X（2020）04-0091-0008

Cluster Analysis and Principal Component Analysis were Used to Study the Chromatography-mass Spectrometry Fingerprints of Sanghuangporus sanghuang

ZHANG Bi-yun^1，2, LIU Wang-mei^1，2, CHENG Jun-wen¹, WEI Hai-long ¹, WU De-ping ³, LIN Wen-fei ³, WANG Yan-bin¹, HE Liang^1*

（1.Laboratory of Biological and Chemical Utilization of Forest Resources in Zhejiang Province, Zhejiang Forestry Research Institute, Hangzhou Zhejiang 310023, China;

2.College of Biological and Chemical Engineering, Zhejiang Institute of Science and Technology, Hangzhou Zhejiang 310023, China;

3.College of Life Sciences, Zhejiang University, Hangzhou Zhengjiang 310058, China）

Abstract：Through GC-MS to identify different areas of Sanghuangporus sanghuang volatile components, and establish Sanghuangporus sanghuang fingerprints, the composition of different origin of Sanghuangporus sanghuang comparative analysis. Application of ether and ethyl acetate as extraction solvent for ultrasonic extraction, using GC-MS to identify extracts, peak area method for determining the content of each component. The cluster analysis method and principal component analysis method were used to analyze the results. 27 effective components and their contents were identified by GC-MS, including ester ketones, sterols, etc. According to the result of cluster analysis, Sanghuangporus sanghuang can be divided into three categories. The principal component analysis extracted two principal components whose characteristic values were greater than 1. The first principal component characteristic value was 8.943, and the contribution rate was 59.619% . The characteristic value of the second principal component was 3.106, and the contribution rate was 20.709%, which included the information of 80.329% in the samples of Sanghuangporus sanghuang. The score of components provided data support to distinguish the components of Sanghuangporus sanghuang in different regions. This method is simple, accurate and effective, with good peak separation, and can effectively identify and compare the composition differences of Sanghuangporus sanghuang from different producing areas.

Keywords：Sanghuangporus sanghuang; GC-MS; fingerprints; principal component analysis; clustering analysis

doi：10.3969/j.issn.1674-506X.2020.04-019

收稿日期：2020-03-03

基金项目：浙江省省属科研院所扶持专项项目（2019F1065-2）

作者简介：张碧云（1999-），女，本科生。

*通讯作者

引文格式：张碧云,刘王梅,程俊文,等.聚类分析和主成分分析法研究桑黄气相色谱-质谱指纹图谱[J].食品与发酵科技,2020,56(4):91-97,104.