月季花的二维相关红外光谱研究  

Discrimination of Chinese Rose by Two-Dimensional Correlation Infrared Spectroscopy

作　　者：于海超[1] 刘刚[1] 欧全宏[1] 马殿旭 李会梅[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19期4995-5000,5107,共7页Hubei Agricultural Sciences

基　　金：国家自然科学基金项目(30960179);云南省高校科技创新团队支持计划项目

摘　　要：利用傅里叶红外光谱（FTIR）技术、化学计量学（主成分分析、聚类分析）结合二维相关红外光谱对不同品种月季花进行鉴别分析。不同品种的月季花瓣的红外光谱整体相似,主要由脂类、苷类及多糖类化合物的振动吸收组成。二阶导数光谱在1 800-700 cm-1区域有较大差异,选取该范围二阶导数光谱用SPSS软件实现主成分分析（PCA）以及系统聚类分析（HCA）。主成分分析中,前3个主成分占总方差的献率为97.40%;系统聚类分析中,每一种月季花各自聚为一类,准确率达到100%。在二维相关光谱中,在1 330-1 700 cm-1和950-1 300 cm-1范围内,不同品种月季花的自动峰、交叉峰的强度和位置具有显著的差异。结果表明,应用傅里叶红外光谱技术、化学计量学及二维相关红外光谱技术可以快速有效的区分不同品种的月季。Fourier transform infrared（FTIR） spectroscopy,two-dimensional correlation infrared spectroscopy and chemometrics（principal component analysis,hierarchical cluster analysis） was applied to identify Chinese rose.Different varieties of infrared spectroscopy as a whole rose broadly similar,mainly made up of lipids and vibration absorbing compounds composed of polysaccharides. Chinese rose second derivative spectra are quite different in 1 800-700 cm-1area,select the second derivative spectra of 1 800-700 cm-1in the region as a major research area combining SPSS software principal component analysis（PCA）and hierarchical cluster analysis（HCA）,The classification accuracy of PCA and HCA were 97.40% and 100% respectively.Two-dimensional correlation infrared spectroscopy technology was applied to study Chinese rose. The significant differences in the position,intensity of auto-peaks and cross peaks were observed in the range of 1 330-1 700 cm-1and 950-1 300 cm-1. It is demonstrated that Fourier transform infrared spectroscopy,two-dimensional correlation infrared spectroscopy and chemometrics is a rapid and effective method for discriminating Chinese rose.

关 键 词：傅里叶红外光谱 月季花(Rosa CHINENSIS Jacq.) 聚类分析 主成分分析 二维相关红外光谱 

分 类 号：O657.3[理学—分析化学]