基于表面增强拉曼的饮料中山梨酸钾快速定量检测方法

发布时间：2018-05-17 22:09

本文选题：表面增强拉曼技术 + 山梨酸钾　；参考：《光谱学与光谱分析》2017年11期

【摘要】：基于实验室自行搭建的拉曼光谱点扫描系统,利用表面增强拉曼技术对橙味饮料中山梨酸钾的含量进行了定量快速检测研究。通过与山梨酸钾标准品拉曼光谱及其水溶液表面增强拉曼光谱等比较分析,确定了山梨酸钾1 648.4,1 389.3和1 161.8cm~(-1)处的表面增强特征拉曼位移。通过山梨酸钾橙味饮料平行样品的拉曼位移峰强重现性实验并计算其峰强的相对标准偏差证实了该表面增强拉曼方法具有较好的重复性。采集了山梨酸钾浓度范围为1.706~0.180 7g·kg-1的33个橙味饮料样品的表面增强拉曼光谱,所有原始光谱经S-G 5点平滑及Baseline基线去除荧光背景预处理后分别用一元线性回归分析、多元线性回归分析和偏最小二乘回归分析方法,建立了山梨酸钾的定量预测模型。经比较,选取三个山梨酸钾拉曼特征位移1 161.8,1 389.3和1 648.4cm~(-1)所建立的多元线性回归模型校正集的相关系数(R2C)和均方根误差(RMSEC)分别为0.983 7和0.051 7g·kg~(-1),验证集的相关系数(R2P)和均方根误差(RMSEP)分别为和0.969 9和0.052 8g·kg-1,比一元线性回归模型和偏最小二乘回归模型误差小、精度高。基于表面增强拉曼完全可以实现橙味饮料中山梨酸钾的定量快速预测,为各类食品中山梨酸钾含量的快速监测奠定了技术基础。
[Abstract]:The quantitative and rapid determination of potassium sorbate in orange beverage by surface-enhanced Raman technique was studied based on the Raman spot scanning system. The surface-enhanced Raman shift of potassium sorbate at 1 648.4 cm ~ (-1) and 1 161.8 cm ~ (-1) was determined by comparison with Raman spectra of potassium sorbate standard and surface enhanced Raman spectra of aqueous solution. The reproducibility of Raman shift intensity of parallel beverage samples of potassium sorbate orange and the relative standard deviation of calculating its peak strength proved that the surface-enhanced Raman method had good reproducibility. The surface enhanced Raman spectra of 33 orange beverage samples with potassium sorbate concentration ranging from 1.706 to 0.1807 g kg-1 were collected. All the original spectra were smoothed by S-G 5 point and the fluorescence background was removed by Baseline baseline. The quantitative prediction model of potassium sorbate was established by multivariate linear regression analysis and partial least square regression analysis. By comparison, Three Raman characteristic shifts of potassium sorbate (1 161.8 cm ~ (389.3) and 1 648.4 cm ~ (-1) were used to verify the correlation coefficient R _ (2C) and root mean square error (RMS) of the calibration set were 0.983 7 and 0.051 7 g kg 路kg ~ (-1), respectively. The correlation coefficient R2P) and root mean square error (RMS) of the set were verified. The difference RMS EPs are 0.969 9 and 0.052 8 g kg -1, respectively, which are smaller than that of linear regression model and partial least square regression model. High precision. Based on surface-enhanced Raman, the quantitative and rapid prediction of potassium sorbate in orange beverage can be realized, which lays a technical foundation for rapid monitoring of potassium sorbate in all kinds of foods.
【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】：国家科技支撑项目(2014BAD04B05)资助
【分类号】：O657.37;TS27

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