近红外光谱技术识别烤烟香气风格的研究  

A study of recognition of tobacco aroma style using near infrared spectroscopy

作　　者：张秋菊[1] 田旷达[2] 李祖红[1] 吕亚琼[1] 熊艳梅[2] 闵顺耕[2] 

机构地区：[1]云南省烟草公司曲靖市公司,曲靖655000 [2]中国农业大学,北京100193

出　　处：《现代仪器与医疗》2014年第4期66-68,共3页Modern Instruments & Medical Treatment

基　　金：中国烟草总公司资助项目(2010YN65)

摘　　要：目的 :研究烤烟香气风格中焦香、辛香、甜香等香韵的识别技术。方法:采用近红外光谱技术结合最小二乘支持向量机(LS-SVM)模式识别方法。烟叶粉末的近红外漫反射光谱经过波长范围选择和多种预处理优化后输入模型,使用k折交互验证和多层网格法优化LSSVM模型参数,建立三种香韵识别模型。结果:焦香、甜香、辛香的识别准确率CR分别为94.7%、88.9%、94.8%,ROC曲线下面积AUC分别为0.99、0.99、1.00。结论:说明使用近红外光谱技术结合LS-SVM方法可有效识别烤烟香气风格。A method combined with near infrared （NIR） spectroscopy and least squares-support vector machine （LS-SVM） was applied to study identiifcation technology of tobacco aroma styles. The NIR spectrum of the tobacco powder were preprocessed by a wavelength selection technique and several pretreatment methods including smoothing, multiplicative scatter correction and standard normal variate transformation. The LS-SVM identiifcation models for three kinds of tobacco aroma styles were built, after optimizing parameters by k-fold cross validation and multilayer grid search. The values of accuracy rate of burnt aroma, spice aroma and sweetness aroma model were 94.7%, 88.9% and 94.8%, respectively. And the area under AOC curve were 0.99, 0.99 and 1.00, respectively. The overall results show that NIR spectroscopy combined with LS-SVM can be efifciently utilized for rapid and accurate identiifcation of tobacco aroma styles.

关 键 词：近红外 最小二乘支持向量机 香气风格 焦香 辛香 甜香 

分 类 号：O657[理学—分析化学]