基于表面增强拉曼光谱快速定量检测碳酸饮料中苯甲酸钠的方法

发布时间：2018-02-28 21:03

本文关键词： 光谱学表面增强拉曼光谱快速检测银溶胶碳酸饮料苯甲酸钠　出处：《光学学报》2017年09期 　论文类型：期刊论文

【摘要】：利用实验室自行搭建的拉曼光谱检测系统,确定了苯甲酸钠位于843.5cm-1、1007cm-1和1605cm-1处的3个拉曼特征峰;以柠檬酸钠还原硝酸银配制的银溶胶作为表面增强剂,设计了快速检测市售碳酸饮料中苯甲酸钠含量的方法。将44个苯甲酸钠浓度不同的碳酸饮料的原始光谱曲线进行Savitzky-Golay平滑降噪及基线背景扣除预处理,然后随机分为32个校正集和12个验证集,采用一元线性回归、多元线性回归、偏最小二乘回归、主成分回归和支持向量机回归等方法进行建模。结果表明,以843.5cm-1、1605cm-1处的2个特征峰建立的二元线性回归模型的建模结果最好,验证集相关系数为0.9603,验证集的均方根误差为0.0867×10-3。该二元线性回归模型可以实现市售碳酸饮料中苯甲酸钠的快速定量检测,为食品中的苯甲酸钠含量的实时在线检测提供了技术支撑。
[Abstract]:Three Raman characteristic peaks of sodium benzoate at 843.5 cm ~ (-1) ~ (-1) ~ 1007cm ~ (-1) and 1605 cm ~ (-1) cm ~ (-1) were determined by the Raman spectroscopic system, and the silver sol prepared by reducing silver nitrate by sodium citrate was used as the surface intensifier. A method for rapid determination of sodium benzoate in carbonated beverages was designed. The original spectral curves of 44 carbonated beverages with different concentrations of sodium benzoate were smoothed by Savitzky-Golay and pretreatment with baseline background subtraction. Then it is randomly divided into 32 correction sets and 12 verification sets. The methods of linear regression, multivariate linear regression, partial least square regression, principal component regression and support vector machine regression are used to model the model. The binary linear regression model with two characteristic peaks at 843.5 cm ~ (-1) ~ (-1) and 1605 cm ~ (-1) is the best. The correlation coefficient of the verification set is 0.9603, and the root mean square error of the verification set is 0.0867 脳 10 ~ (-3). The binary linear regression model can be used to detect sodium benzoate in carbonated drinks. It provides technical support for real-time on-line detection of sodium benzoate in food.
【作者单位】：中国农业大学工学院国家农产品加工技术装备研发分中心;
【基金】：中央高校基本科研业务费专项资金(2017GX001)
【分类号】：O657.37;TS275.3

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