A simple and efficient alginate hydrogel combined with surface-enhanced Raman spectroscopy for quantitative analysis of sodium nitrite in meat products

作者：Fengnian Liang, Yiqun Huang, Junjian Miao, Keqiang Lai · 发表于：The Analyst · 年份：2024 · DOI：10.1039/d3an01771k · 被引用次数：11 · 研究领域：Advanced Chemical Sensor Technologies、Spectroscopy Techniques in Biomedical and Chemical Research、Biosensors and Analytical Detection

, with low interference from the food matrix. The support vector machine algorithm was utilized to train and predict the data, which proved to be more accurate (98.6%-99.8% recovery) than the traditional linear regression model (81.9%-112.7% recovery) in predicting the spiked samples. The application of hydrogel-based surface-enhanced Raman spectroscopy (SERS) substrates for nitrite detection in food, combined with machine learning for regression prediction in data processing, collectively augmented the potential of SERS technology in the field of food analysis.