基于表面增强拉曼的鸡尾酒中苯甲酸钠和山梨酸钾的同时快速检测

基于实验室自行搭建的拉曼点扫描系统，以市售鸡尾酒为研究对象柠檬酸钠还原硝酸银配制的银溶胶作为表面增强剂，探讨了鸡尾酒中苯甲酸钠和山梨酸钾两种防腐剂的同时快速检测方法。首先确定鸡尾酒中苯甲酸钠拉曼特征峰为846.1，1 007和1 605 cm-1，山梨酸钾拉曼特征峰为1 164，1 389和1 651 cm-1，进而对它们拉曼特征位移强度稳定性及鸡尾酒中两种防腐剂对拉曼特征位移强度的相互影响进行了分析。结果表明，利用该方法采集的鸡尾酒中苯甲酸钠和山梨酸钾表面增强拉曼特征位移强度具有较高的稳定性，而且鸡尾酒中苯甲酸钠和山梨酸钾的拉曼特征位移强度相互影响并不大，具有较高的稳定性。分别制备苯甲酸钠浓度范围为0.154 3~1.5 g·kg-1的42个鸡尾酒样品及山梨酸钾浓度范围为0.062~1.5 g·kg-1的45个鸡尾酒样品，分别建立了苯甲酸钠和山梨酸钾的线性回归模型。选用最佳的苯甲酸钠1 007和1 605 cm-1二元线性回归预测模型与山梨酸钾的1 164和1 651 cm-1二元线性回归预测模型，对不同浓度苯甲酸钠和山梨酸钾43个鸡尾酒样品进行了苯甲酸钠和山梨酸钾同时预测验证。结果显示，鸡尾酒中苯甲酸钠和山梨酸钾预测值与实际值相关系数(r)分别为0.949 3和0.921 8，均方根误差(RMSE)分别为0.088 2和0.142 9 g·kg-1。基于银溶胶表面增强拉曼完全可以实现鸡尾酒中苯甲酸钠和山梨酸钾两种防腐剂的快速同时检测，为液态食品中防腐剂的同时快速监测提供了技术支撑。

Rapid and Simultaneous Detection of Sodium Benzoate and Potassium Sorbate in Cocktail Based on Surface-Enhanced Raman Spectroscopy

This paper established an optimal analytical model for rapid and simultaneous detection of sodium benzoate and potassium sorbate in cocktail by using surface-enhanced Raman technique, based on the self-built laboratory Raman point scanning system. Silver colloidal nanoparticles were prepared by reduction of silver nitrate with sodium citrate. In addition, the Raman spectra of sodium benzoate and potassium sorbate standard were compared with surface-enhanced Raman spectroscopy of cocktail samples containing sodium benzoate and potassium sorbate. 846.1，1 007 and 1 605 cm-1 were surface-enhanced Raman characteristic shifts of sodium benzoate. 1 164，1 389 and 1 651 cm-1 were surface-enhanced Raman characteristic shifts of potassium sorbate. At the same time, the stability of the peak in the Raman characteristic shift and the interrelation of Raman shift peak strength of two kinds of preservatives in the cocktail were analyzed. The detection method was of high stability, and the two kinds of preservatives were basically no interaction. Moreover, 42 sodium benzoate concentrations of 0.154 3~1.5 g·kg-1 and 45 potassium sorbate concentrations of 0.062~1.5 g·kg-1 were prepared to establish a linear regression model in cocktail. The best prediction models for sodium benzoate and potassium sorbate were two respective linear regression model established by 1 007，1 605 and 1 164 1 651 cm-1. Besides, 43 different concentrations of sodium benzoate and potassium sorbate cocktail samples were predicted by the best prediction models. The result showed that the correlation coefficients (r) of sodium benzoate and potassium sorbate were 0.949 3，0.921 8, root mean square error (RMSE) were respectively 0.088 2 and 0.142 9 g·kg-1, respectively. The rapid and quantitative determination of sodium benzoate and potassium sorbate in commercial cocktail can be realized by surface enhanced Raman spectroscopy. The results provides technical support for simultaneous and real-time online monitoring of preservatives in liquid food.