Zhou Zai-Jin, Liu Gang, Ren Xian-Pei
School of Physics and Electronic Information, Yunnan Normal University, Kunming 650092, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2010 Apr;30(4):911-4.
It is hard to differentiate the same species of wild growing mushrooms from different areas by macromorphological features. 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 samples, principal component analysis was conducted on 58 boletus bicolor 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 bicolor samples were divided into five groups with a classification accuracy of 98.3%. The study demonstrated that wild growing boletus bicolor at species level from different areas can be identified by FTIR spectra combined with principal components analysis.
很难通过宏观形态特征区分来自不同地区的同一种野生蘑菇。本文采用傅里叶变换红外（FTIR）光谱结合主成分分析方法对来自五个不同地区的58份双色牛肝菌样本进行鉴别。基于双色牛肝菌样本的指纹红外光谱，使用统计软件SPSS 13.0对58份双色牛肝菌光谱在1350 - 750 cm(-1)范围内进行主成分分析。结果显示，前三个主成分的累计贡献率为88.87%，几乎包含了样本的所有信息。利用第一和第二主成分绘制的二维投影图对双色牛肝菌的分类和鉴别具有良好的聚类效果。所有双色牛肝菌样本被分为五组，分类准确率为98.3%。该研究表明，结合主成分分析的FTIR光谱能够鉴别不同地区物种水平的野生双色牛肝菌。
