化学计量学
偏最小二乘回归
苯并咪唑
化学
分析化学(期刊)
拉曼光谱
色谱法
多菌灵
定量分析(化学)
表面增强拉曼光谱
数学
有机化学
拉曼散射
生物
植物
杀菌剂
统计
光学
物理
作者
Tianyao Wang,Chuangjie Xie,Qian You,Xingguo Tian,Xiaoyan Xu
出处
期刊:Food Chemistry
[Elsevier BV]
日期:2023-05-27
卷期号:424: 136479-136479
被引量:11
标识
DOI:10.1016/j.foodchem.2023.136479
摘要
In this study, surface-enhanced Raman spectroscopy (SERS) combined with chemometric methods were developed for qualitative and quantitative analysis of four benzimidazole (BMZs) residues in corn. Sulfhydryl functionalized Fe3O4@SiO2@Ag-SH magnetic SERS substrates were prepared to obtain the SERS spectra of four BMZs for chemometric analysis. The partial least squares regression discrimination analysis (PLS-DA) model performed best, with a recall rate upwards 99.17%, and could successfully distinguish four BMZs. Under the support vector machine regression (SVR) model, the detection limits of carbendazim, benomyl, thiophanate-methyl and thiabendazole were 0.055 mg/L, 0.056 mg/L, 0.067 mg/L and 0.093 mg/L, respectively; the average recovery was in the range of 85.6%–107.5%. Furthermore, the method verified by HPLC, and the results showed that there was no significant difference between two methods (p > 0.05). Therefore, the strategy based on SERS coupling chemometrics can be served as a promising tool for rapid determination of BMZs residues in food.
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