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不同产地双色牛肝菌FTIR光谱鉴别研究
引用本文:周在进,刘刚,任先培.不同产地双色牛肝菌FTIR光谱鉴别研究[J].光谱学与光谱分析,2010,30(4).
作者姓名:周在进  刘刚  任先培
作者单位:1. 云南师范大学物理与电子信息学院,云南昆明,650092;淮阴工学院计算科学系,江苏淮安,223001
2. 云南师范大学物理与电子信息学院,云南昆明,650092
基金项目:国家自然科学基金项目 
摘    要:同一种蕈菌子实体,由于外观形貌相似,凭传统外观形貌特征难以鉴别产地来源。应用傅里叶变换红外光谱(FTIR)法测定了云南省5个不同地区58个野生双色牛肝菌子实体样品的红外光谱。借助于红外光谱具有的指纹特性,利用SPSS 13.0统计软件对1 350~750 cm-1范围光谱数据进行主成分分析(PCA),根据前三个主成分累积贡献率已达到88.87%以及主成分载荷分析,表明前三个主成分能够反映样品在该段光谱的主要信息。对前三个主成分作投影显示并进行比较,发现以主成分1和主成分2作二维线形投影,对不同产地的双色牛肝菌有较好的聚类和鉴别作用,所有样品被划分为5个区域,98.3%的样品被正确归类。研究结果提示,傅里叶变换红外光谱结合主成分分析方法可以快速、方便地对不同产地的同一种野生双色牛肝菌进行鉴别分类。

关 键 词:双色牛肝菌  傅里叶变换红外光谱  主成分分析  鉴别分类

A Study of Boletus Bicolor from Different Areas Using Fourier Transform Infrared Spectrometry
ZHOU Zai-jin,LIU Gang,REN Xian-pei.A Study of Boletus Bicolor from Different Areas Using Fourier Transform Infrared Spectrometry[J].Spectroscopy and Spectral Analysis,2010,30(4).
Authors:ZHOU Zai-jin  LIU Gang  REN Xian-pei
Abstract:It is hard to differentiate the same species of wild growing mushrooms from different areas by macromorphological fea-tures. In this paper, Fourier transform infrared (FTIR) spectroscopy combined with principal component analysis was used to identify 58 samples of boletus bicolor from five different areas. Based on the fingerprint infrared spectrum of boletus bicolor sam-ples, principal component analysis was conducted on 58 boletusbicolor spectra in the range of 1 350-750 cm~(-1) using the statistical software SPSS 13. 0. According to the result, the accumulated contributing ratio of the first three principal components accounts for 88. 87%. They included almost all the information of samples. The two-dimensional projection plot using first and second principal component is a satisfactory clustering effect for the classification and discrimination of boletus bicolor. All boletus bicol-or samples were divided into five groups with a classification accuracy of 98. 3 %. The study demonstrated that wild growing bo-letus bicolor at species level from different areas can he identified by FTIR spectra combined with principal components analysis.
Keywords:Boletus bicolor  Fourier transform infrared spectroscopy  Principal component analysis  Identification
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