近红外光谱-偏最小二乘法非破坏分析酱油的主要成分  

Nondestructive Analysis of the Quality Properties of Soy Sauce by Near Infrared Spectroscopy with Partial Least Squares

作　　者：包春芳[1] 刘彤[1,2] 王彬[1] 赵羚志[1] 任玉林[1] 

机构地区：[1]吉林大学化学学院,长春130021 [2]哈尔滨市疾病预防控制中心,哈尔滨150056

出　　处：《吉林大学学报（理学版）》2009年第2期362-366,共5页Journal of Jilin University:Science Edition

基　　金：吉林省科技厅项目基金(批准号:20050123);哈尔滨市科技创新人才专项科研基金(批准号:RC2006QN020015)

摘　　要：将近红外光谱技术与偏最小二乘法(PLS)相结合建立数学校正模型,对酱油中的氨基酸态氮、总酸以及食盐进行快速、无损定量分析,并对酱油的色度进行预测,同时讨论了光谱预处理方法和主成分数对PLS模型预测精度的影响.结果表明,采用一阶导数预处理光谱建立的数学校正模型能得到最佳的预测效果,在对预测集18个样本中的氨基酸态氮、总酸、食盐的含量和色度进行预测时,所得的预测集相对标准偏差分别为1.516%,1.811%,1.798%,1.893%.实验结果具有较高的预测精度,可以用于酱油中主要成分含量的测定.Near-infrared spectroscopy combined with partial least squares （PLS） method was applied to establishing an optimal mathematic calibration model, by which the concentrations of amino nitrogen, total acid and salt content in the soy sauce were predicted, and the color ratio of the soy sauce was determined. Furthermore, the influences of spectral preprocessing methods and the numbers of principal components on the prediction ability of the PLS model were discussed. The results show that the calibration model established with first-derivative preprocessing spectra was the best, 18 samples of tested set were predicted with this model, the relative standard errors for the prediction of amino nitrogen, total acid, salt content and color ratio were I. 516%, 1. 811%, 1. 798% and 1. 893%, respectively. Experimental results demonstrate that this method is fast and convenient, and it has a high ability of prediction, thus it is promising for the non-destructive quality control of soy sauce.

关 键 词：近红外光谱 偏最小二乘 酱油 非破坏分析 

分 类 号：O657.33[理学—分析化学]