光谱学与光谱分析, 2013, 33 (3): 690, 网络出版: 2013-03-27
近红外光谱法应用于食用香精中增塑剂的检测研究
Detection of Plasticizers in Edible Essence by Near-Infrared Spectrometry
增塑剂 近红外光谱(NIRS) 主成分分析(PCA) 偏最小二乘法(PLS) 聚类分析(CA) Plasticizer Near-infrared spectrum (NIRS) Principal component analysis (PCA) Partial least-squares(PLS) Cluster analysis (CA)
摘要
借助近红外透射光谱技术得到香精样品的原始光谱, 选取波段范围为8 800~8 540和7 500~5 085 cm-1, 用主成分分析(PCA)法定性识别其中是否添加DEHP或DINP, 正确率100%。 同时测定了DEHP和DINP(浓度范围在0~100 mg·kg-1之间)在食用香精中的含量, 并以偏最小二乘法(PLS)建立定量分析模型, DEHP和DINP预测结果的相对误差分别在-17.6%~15.8%和-7.6%~9.9%之间, 预测均方根误差分别为1.39和0.98。 为检测食用香精中增塑剂的含量提供了一种可同时定性与定量的快速、 简便、 廉价、 准确的分析方法。
Abstract
Based on the initial near-infrared spectrum of edible essence samples and its mixture with DEHP and DINP, we chose the wavelength ranges of 8 800~8 540 and 7 500~5 085 cm-1 to use the principal component analysis (PCA) method to distinguish these three types of samples. The correct rate of the identification is proved to be 100%. Meanwhile, we measured the content of DEHP and DINP (with the concentration ranging between 0 and 100 mg·kg-1) in the edible essence and established the quantitative analysis model by using partial least squares (PLS). It was found that the relative errors of the prediction results of DEHP and DINP are -1.23%~3% and -1%~3.6%, respectively, and the relative root-mean-square errors of prediction (RRMSEP) of them are 1.39 and 0.98, respectively. This study provides a simple, rapid and accurate method to detect the additive dosage of plasticizing agents in edible essence in the food industry.
李祥辉, 杨方, 林振宇, 邱彬, 王丹红. 近红外光谱法应用于食用香精中增塑剂的检测研究[J]. 光谱学与光谱分析, 2013, 33(3): 690. LI Xiang-hui, YANG Fang, LIN Zhen-yu, QIU Bin, WANG Dan-hong. Detection of Plasticizers in Edible Essence by Near-Infrared Spectrometry[J]. Spectroscopy and Spectral Analysis, 2013, 33(3): 690.