红外、近红外光谱-簇类的独立软模式方法识别植物调和油脂  

Combining Infrared,Near Infrared with Soft Independent Modeling of Class Analogy for Identification of Vegetable Blend Oil

作　　者：李娟[1] 范璐[1] 毕艳兰[1] 屈凌波[1] 周展明[1] 吴存荣[1] 

机构地区：[1]河南工业大学,郑州450001

出　　处：《分析化学》2010年第4期475-482,共8页Chinese Journal of Analytical Chemistry

基　　金：现代农业产业技术体系建设专项资金资助项目

摘　　要：用IR,NIR光谱法结合簇类的独立软模式(SIMCA)识别方法对植物油脂进行分类识别,建立了识别二元、三元植物调和油脂的测定方法。应用NIRCal5.2软件的SIMCA技术,分别为所制备的植物调和油脂建立了IR和NIR识别模型,并讨论了光谱处理和数据处理方法来提高模型的分类识别效果。分别以各种植物调和油脂的IR和NIR光谱为变量,随机抽取2/3的样本作训练集,建立了各个调和油的主成分分析(Princi-pal component analysis,PCA)模型;1/3作验证集,对所建模型进行验证识别。用聚类分析-主成分分析(CLU-PCA)方法考察调和油的IR,NIR光谱信息与其纯油的主成分分布。结果显示,在4000～10000cm-1光谱范围内,SIMCA可以对15种二元调和油和2种三元调和油的NIR光谱分别聚类并识别;并对10种二元调和油和2种三元调和油的IR光谱分别聚类并识别。IR以4个波数1099,1119,1746与2855cm-1的吸收值作为分析基础,选择不同的主成分数及数据预处理方法。各种油脂的SIMCA分析的分类精度均为100%,调和油的验证识别准确率100%,最低识别比例为1%,且IR识别灵敏度高于NIR。The analytical methods were developed to discriminate and analyze vegetable binary and ternary blend oil using NIR and IR spectroscopy with the aid of SIMCA.The methods of SIMCA and spectra pretreated by cluster technique of NIRCal5.2 were able to classify the samples of blend oil.The spectra information as variance was used in the processing of spectra pretreated,and 2/3 of samples were selected for calibration and the other for validation.In the cluster-principal component analysis（CLU-PCA） ,the spectra information of blend oil distributes with the pure oils and the spectra have overlapped with the pure oil when the proportion is smaller or greater.The spectral range of NIR is 4000-10000 cm-1,but the subdomain IR is at 1099,1119,1746 and 2855 cm-1 .NIR-SIMCA was applied to identify 15 kinds of binary mixts and 2 kinds of ternary mixts oils.IR-SIMCA was applied to identify 10 kinds of binary mixts oils and 2 kinds of ternary mixts oils. The results show that the identification accuracy are 100%,and the minimum ratio recognited is 1%based on the data of experimental.

关 键 词：红外光谱 近红外光谱 簇类的独立软模式 植物调和油脂 

分 类 号：TS227[轻工技术与工程—粮食、油脂及植物蛋白工程]