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食用牛肝菌不同部位紫外指纹图谱鉴别分析
引用本文:杨天伟,崔宝凯,张霁,李涛,李杰庆,刘鸿高,王元忠.食用牛肝菌不同部位紫外指纹图谱鉴别分析[J].菌物学报,2014,33(2):262-272.
作者姓名:杨天伟  崔宝凯  张霁  李涛  李杰庆  刘鸿高  王元忠
作者单位:云南农业大学农学与生物技术学院 云南 昆明 650201;北京林业大学微生物研究所 北京 100083;云南省农业科学院药用植物研究所 云南 昆明 650200;玉溪师范学院资源环境学院 云南 玉溪 653100;云南农业大学农学与生物技术学院 云南 昆明 650201;云南农业大学农学与生物技术学院 云南 昆明 650201;云南省农业科学院药用植物研究所 云南 昆明 650200
基金项目:国家自然科学基金(No. 31260496,No. 31160409);云南省自然科学基金(No. 2011FB053,No. 2011FZ195)
摘    要:采用紫外光谱技术结合主成分分析法,建立快速鉴别牛肝菌的不同部位及不同种类、产地的方法。通过单因素实验确定提取牛肝菌特征成分的最佳条件,制备测试液并进行紫外光谱测定。结果表明,牛肝菌样品的重现性、精密度和10h内稳定性的RSD(%)分别在0.09–1.81、0.11–1.92、0.06–2.33之间;牛肝菌不同部位紫外指纹图谱具有明显的指纹特性;主成分分析(PCA)表明菌盖和菌柄前3个主成分累积贡献率分别为94.797%和92.961%,能够反映样品的主要信息;SIMCA软件分析显示牛肝菌菌盖和菌柄化学成分积累不同。根据牛肝菌不同部位紫外光谱信息和主成分分析能区分同一牛肝菌的不同部位,鉴别不同种类、不同产地的食用牛肝菌。

关 键 词:牛肝菌  紫外光谱  主成分分析  鉴别  

Identification of different parts of edible bolete mushrooms by UV fingerprint
Authors:YANG Tian-Wei  CUI Bao-Kai  ZHANG Ji  LI Tao  LI Jie-Qing  LIU Hong-Gao and WANG Yuan-Zhong
Institution:College of Agronomy and Biotechnology, Yunnan Agricultural University, Kunming, Yunnan 650201, China;Institute of Microbiology, Beijing Forestry University, Beijing 100083, China;Institute of Medicinal Plants, Yunnan Academy of Agricultural Sciences, Kunming, Yunnan 650200, China;College of Resources and Environment, Yuxi Normal University, Yuxi, Yunnan 653100, China;College of Agronomy and Biotechnology, Yunnan Agricultural University, Kunming, Yunnan 650201, China;College of Agronomy and Biotechnology, Yunnan Agricultural University, Kunming, Yunnan 650201, China;Institute of Medicinal Plants, Yunnan Academy of Agricultural Sciences, Kunming, Yunnan 650200, China
Abstract:An ultraviolet spectrum technology combined with principal component analysis (PCA) was used to rapidly identify different parts of fruiting body of several bolete species from different areas of Yunnan Province, Southwest China. Based on the single factor experiment, the optimal extraction conditions of characteristic components of boletes were determined, and the preparation of the test liquid was determined by UV spectroscopy. The results showed that, within 10h, the RSDs (%) of stability, repeatability and accuracy of bolete samples were 0.06–2.33, 0.09–1.8 and 0.11–1.92, respectively. UV fingerprint spectra of different parts of boletes have obvious fingerprint features. The first three principal components’ cumulating contributions of cap and stipe of boletes by PCA were 94.797% and 92.961%, respectively, being able to reflect the most information of the samples. SIMCA analysis showed that the accumulation of chemical components of cap and stipe of boletes were different. UV spectrum information and principal component analysis could distinguish the different parts of fruiting body of boletes and identify the different species from different producing areas.
Keywords:boletes  ultraviolet spectrum  principal component analysis  identification
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