FTIR结合DWT鉴别研究六种不同植物来源的淀粉  

Identification for Starches from Six Different Plants by Fourier Transform Infrared Spectroscopy Combined with Discrete Wavelet Transform

作　　者：任静[1] 刘刚[1] 欧全宏[1] 赵帅群 徐娟[1] 

机构地区：[1]云南师范大学物理与电子信息学院,昆明650500

出　　处：《湖北农业科学》2016年第5期1277-1280,共4页Hubei Agricultural Sciences

基　　金：国家自然科学基金项目(30960179)

摘　　要：利用傅里叶变换红外光谱（FTIR）结合离散小波变换（DWT）、主成分分析（PCA）和聚类分析（HCA）方法对甘薯、马铃薯、薯蓣、莲藕、豌豆、玉米淀粉进行鉴别研究,测试淀粉样品的红外光谱。结果表明,6种淀粉样品红外光谱相似,但在1 700～800 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离散小波变换,提取离散小波变换的第五尺度细节系数数据,进行主成分分析和聚类分析。离散小波的前3个主成分的累计贡献率为94.43%,主成分分析和聚类分析正确率为100%。研究表明,傅里叶变换红外光谱技术结合离散小波变换的方法可以鉴别不同植物来源的淀粉。Starches from six different plants were identified by Fourier transform infrared（FTIR） spectroscopy combined with discrete wavelet transform（DWT）, principal component analysis（PCA） and hierarchical cluster analysis（HCA）, to test infrared spectrum in starch samples. The results showed that the infrared spectrum of six starch samples were similar on the whole, but with obvious differences in the position, shape and absorption intensity of peaks in the range of 1 700～800 cm-1.Selecting infrared spectrum in this range to perform DWT, extracting the fifth level detail coefficients of discrete wavelet transform to perform PCA and HCA. The first three principal components＇ cumulative contribution rate of discrete wavelet was94.43%, the accurate rates of HCA and PCA were 100%. It proved that method of FTIR spectroscopy combined with discrete wavelet transform could be used to identify different kinds of starches.

关 键 词：淀粉来源 鉴别 傅里叶变换红外光谱(FTIR) 离散小波变换(DWT) 主成分分析(PCA) 聚类分析(HCA) 

分 类 号：O657.3[理学—分析化学] TS231[理学—化学]