小米的傅里叶变换红外光谱研究  

Study of Millet by Fourier Transform Infrared Spectroscopy

作　　者：王小龙[1] 刘刚[1] 赵兴祥[1] 欧全宏[1] 郝建明[1] 

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：《光散射学报》2014年第4期406-410,共5页The Journal of Light Scattering

基　　金：国家自然科学基金项目(30960179);云南省教育厅科学研究基金项目(2012J096)资助

摘　　要：本文利用傅里叶变换红外光谱（FTIR）结合主成分分析和聚类分析对白小米、黄小米、糯小米、青小米、陈黄小米、黑小米和大黄米进行鉴别研究。所有样品的傅里叶变换红外光谱整体相似,二阶导数光谱存在明显的差异。选取1800-1400cm-1范围内的二阶导数光谱数据对52份小米样品做多变量分析,结果显示,主成分分析的分类准确率为84.6%,系统聚类分析的分类准确率为92.3%。结果表明傅里叶变换红外光谱技术结合化学计量学能有效地区分不同品种的小米,为不同小米的分类鉴定提供新的方法与途径。Fourier transform infrared spectroscopy （FTIR） combined with principal compo nents analysis （PCA） and hierarchical cluster analysis （HCA） was used to study white millet, yellow millet, glutinous millet, green millet, black millet, stale yellow millet and proso millet. The results showed that the spectra of samples were similar, but the second derivative spectra in 1800-1400 cmI range were significant different. The second derivative spectral data were selected to evaluate multivariate analysis. Results showed that the classification accuracy of principal component analysis （PCA） and hierarchical cluster analysis（HCA） were about 84.6%and 92.3% respectively. This study demonstrated that FTIR techniques combined with chemometrics could be applied to distinguish different kinds of millet accurately, which will provide new method and approach for classifying and identifying different millets .

关 键 词：傅里叶变换红外光谱 小米 主成分分析 聚类分析 

分 类 号：O657.3[理学—分析化学]