近红外光谱分析烟叶中的多酚类物质  

Determination of polyphenols in tobacco by Near Infrared Spectroscopy

作　　者：吕亚琼[1] 张秋菊[1] 李祖红[1] 闵顺耕[2] 

机构地区：[1]云南省烟草公司曲靖市公司,曲靖6550001 [2]中国农业大学理学院,北京100193

出　　处：《现代仪器与医疗》2014年第4期63-65,共3页Modern Instruments & Medical Treatment

基　　金：中国烟草总公司项目(项目编号:No.2010YN65)

摘　　要：多酚类物质是烟叶香气产生的重要前体物质。采用近红外光谱结合偏最小二乘算法建立了烟叶中总多酚含量的回归模型。采用建立的模型对检验集进行预测,预测集决定系数R2为0.8671,模型误差SEP为1.4287。结果表明近红外光谱分析技术可以成功应用于烟叶中总多酚含量的检测。此外,为消除烟叶近红外光谱中无效波长变量,采用无消息变量消除算法对所建近红外模型进行优化。结果表明采用该算法后,剩余变量数得到减少,模型维数显著降低,预测性能有所提高。Polyphenols are important aroma precursors in tobacco. In this paper, near-infrared spectroscopy combined with partial least squares algorithm was used for establishing regression model of total polyphenol content in tobacco. For test set, model R2 is 0.8671, SEP is 1.4287. Results show that near-infrared spectroscopy technology can be successfully applied to the total polyphenol content detection in tobacco. In order to eliminate interference variables in tobacco near infrared spectrum, Uninformative Variables Elimination algorithm was used. Experimental results show that after the algorithm used, remaining number of variables is reduced, modeling dimension is significantly reduced, and prediction performance is improved.

关 键 词：近红外光谱 烟叶 总多酚 偏最小二乘算法 无消息变量消除算法 

分 类 号：O657[理学—分析化学]