首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于改进标准加入法的碳酸饮料中防腐剂和甜味剂高通量筛查分析
引用本文:王素方,刘云,弓丽华,董春红,符德学,王国庆.基于改进标准加入法的碳酸饮料中防腐剂和甜味剂高通量筛查分析[J].光谱学与光谱分析,2016,36(2):482-486.
作者姓名:王素方  刘云  弓丽华  董春红  符德学  王国庆
作者单位:1. 郑州轻工业学院材料与化学工程学院,河南 郑州 450001
2. 河南出入境检验检疫局检验检疫技术中心,河南 郑州 450003
3. 焦作大学怀药工程研究中心,河南 焦作 454003
基金项目:国家自然科学基金,国家质量监督检验检疫总局科技计划项目,河南省基础与前沿技术研究项目
摘    要:利用正交设计分别配制含有三种防腐剂、四种甜味剂的模拟水样,采用核独立成分分析(KICA)处理模拟水样与加入不同含量标准品的饮料样品的紫外光谱(UV)数据,得到其中待测添加剂或背景成分的UV轮廓的独立组分(IC)信息,以IC的系数矩阵进行支持向量回归(SVR)分析,建立模拟样品中防腐剂与甜味剂的UV-KICA-SVR预测模型。添加不同含量水平添加剂的碳酸饮料样品,采用KICA处理其测试得到的UV光谱数据,得到与添加剂对应的IC信息及量,加入量与预测量线性回归方程截距即为饮料中添加剂含量。利用化学计量学“盲源信号分离”方法提取饮料样品中的待测添加剂IC信息与样品基质信息,利用SVR对解析得到的IC信号回归分析建模,改进传统单一组分测定的标准加入法,建立了碳酸饮料样品中防腐剂和甜味剂高通量筛查分析的新方法。方法用于测定碳酸饮料中山梨酸钾,苯甲酸钠、对羟基苯甲酸甲酯钠三种防腐剂与糖精钠、安赛蜜,阿斯巴甜和甘草酸铵四种甜味剂含量,检测限(LOD)为0.2~1.0 mg·L-1,测定结果与传统的色谱方法相当。

关 键 词:独立成分分析  支持向量回归  标准加入法  防腐剂  甜味剂  碳酸饮料    
收稿时间:2014-08-31

High Throughput Screening Analysis of Preservatives and Sweeteners in Carbonated Beverages Based on Improved Standard Addition Method
WANG Su-fang,LIU Yun,GONG Li-hua,DONG Chun-hong,FU De-xue,WANG Guo-qing.High Throughput Screening Analysis of Preservatives and Sweeteners in Carbonated Beverages Based on Improved Standard Addition Method[J].Spectroscopy and Spectral Analysis,2016,36(2):482-486.
Authors:WANG Su-fang  LIU Yun  GONG Li-hua  DONG Chun-hong  FU De-xue  WANG Guo-qing
Institution:1. School of Materials and Chemical Engineering, Zhengzhou University of Light Industry, Zhengzhou 450001, China2. Inspection & Quarantine Technology Centre, Henan Entry-Exit Inspection & Quarantine Bureau of China, Zhengzhou 450003, China3. Research Center of Huaiqing Chinese Medicine, Jiaozuo University, Jiaozuo 454003, China
Abstract:Simulated water samples of 3 kinds of preservatives and 4 kinds of sweeteners were formulated by using orthogonal de-sign .Kernel independent component analysis (KICA) was used to process the UV spectra of the simulated water samples and the beverages added different amounts of the additive standards ,then the independent components (ICs) ,i .e .the UV spectral profiles of the additives ,and the ICs' coefficient matrices were used to establish UV-KICA-SVR prediction model of the simula-ted preservatives and sweeteners solutions using support vector regression (SVR) analysis .The standards added beverages sam-ples were obtained by adding different amounts level of additives in carbonated beverages ,their UV spectra were processed by KICA ,then IC information represented to the additives and other sample matrix were obtained ,and the sample background can be deducted by removing the corresponding IC ,other ICs' coefficient matrices were used to estimate the amounts of the additives in the standard added beverage samples based on the UV-KICA-SVR model ,while the intercept of linear regression equation of predicted amounts and the added amounts in the standard added samples is the additive content in the raw beverage sample .By utilization of chemometric"blind source separation" method for extracting IC information of the tested additives in the beverage and other sample matrix ,and using SVR regression modeling to improve the traditional standard addition method ,a new method was proposed for the screening of the preservatives and sweeteners in carbonated beverages . The proposed UV-KICA-SVR method can be used to determine 3 kinds of preservatives and 4 kinds of sweetener in the carbonate beverages with the limit of de-tection (LOD) are located with the range 0.2~1.0 mg · L -1 ,which are comparable to that of the traditional high performance liquid chromatographic (HPLC) method .
Keywords:Independent component analysis  Support vector regression  Standard addition method  Preservative  Sweetener  Carbonate beverage
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《光谱学与光谱分析》浏览原始摘要信息
点击此处可从《光谱学与光谱分析》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号