Study on Rhizome Crops by Fourier Transform Infrared Spectroscopy Combined with Wavelet Analysis  

FTIR结合小波变换分析鉴别8种根茎类作物（英文）

作　　者：任静[1] 刘刚[1] 赵兴祥[1] 赵帅群 欧全宏[1] 徐娟[1] 胡见飞 

机构地区：[1]云南师范大学物理与电子信息学院,云南昆明650500

出　　处：《Agricultural Science & Technology》2015年第7期1522-1526,共5页农业科学与技术（英文版）

基　　金：Supported by National Natural Science Foundation of China(30960179);Program for Innovative Research Team in Science and Technology in University of Yunnan Province~~

摘　　要：In order to distinguish 8 kinds of rhizome crops, the 40 samples were studied by Fourier transform infrared spectroscopy （FTIR） combined with wavelet transform （WT）, principal component analysis （PCA） and hieramhical cluster analysis （HCA）. The results showed that the infrared spectra were similar on the whole, but there were differences in peak position, peak shape and peak absorption intensity in the range of 1 800-700 cm-1. The infrared spectra in the range of 1 800-700 cm-1 were selected to perform continuous wavelet transform （CWT） and discrete wavelet transform （DWT）. The 15th-Ievel decomposition coefficients of CWT and the 5=-level detail coefficients of DWT were classified by PCA and HCA. The cumulative contri- bution rates of the first three principal components of CWT and DWT were 93.12% and 89.78%, respectively. The accurate recognition rates of PCA and HCA were all 100%. It is proved that FTIR combined with WT can be used to distinguish different kinds of rhizome crops.为了区分鉴别8种根茎类作物,通过采用傅里叶变换红外光谱（FTIR）结合小波变换（WI）、主成分分析（PCA）和聚类分析（HCA）的方法,测试研究了8种根茎类作物40个样品的红外光谱。结果表明：8种样品红外图谱相似,但在1800~700 cm-1范围内,红外光谱的峰位、峰形及吸收强度差异明显。对此范围内的原始红外光谱进行连续小波和离散小波变换。提取连续小波变换的第15层系数和离散小波变换的第5尺度细节系数数据,进行主成分分析和聚类分析。连续小波和离散小波的前3个主成分的累计贡献率分别为93.12%、89.78%,主成分分析和聚类分析正确率为100%。研究结果显示：傅里叶变换红外光谱技术结合小波变换的方法可以区分鉴别不同种的根茎类作物。

关 键 词：FTIR Rhizome crop Wavelet transform Principal component analysis Hierarchical cluster analysis 

分 类 号：Q949[生物学—植物学]