Research on residue detection of prohibited drugs in shrimp based on the thin-layer chromatography-surface-enhanced Raman spectroscopy combined method.

IF 2.2
Ailing Tan, Yunhao He, Haoyu Wang, Zixuan Zhang, Rongxuan Zhao, Wei Ma, Yong Zhao
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Abstract

In recent years, the detection of prohibited drug residues in seafood has become a critical aspect of ensuring food safety and public health. This study presents a novel analytical method combining thin-layer chromatography (TLC) and surface-enhanced Raman spectroscopy (SERS) for the detection of chloramphenicol (CAP) and malachite green (MG) in shrimp samples. Both substances are subject to strict regulation in China due to their adverse health effects and potential carcinogenic risks. Theoretical computations were performed using density functional theory to obtain the Raman and SERS spectra of CAP and MG. This enabled the extraction of their characteristic peaks in experimentally obtained TLC-SRES spectra and the explanation of the frequency shifts and selective enhancement effects of the Raman spectra that may occur under SERS conditions. The optimised TLC conditions were found to effectively separate the target compounds from complex sample matrix backgrounds, with the use of chloroform-methanol-water and ethyl acetate-anhydrous ethanol-water-ammonium hydroxide as mobile phases. This resulted in successful separation with retention factors Rf of 0.63 and 0.66, respectively. Subsequent SERS measurements achieved detection limits of 0.05 μg · kg-1 for CAP and 0.47 μg · kg-1 for MG in shrimp tissue. A machine learning approach that combined principal component analysis with support vector regression was developed for quantification of the residues from their TLC-SERS spectra. The quantitative models for CAP and MG in spiked shrimp samples demonstrated outstanding performance with high R2 values of 0.9673 and 0.9847, and low root mean square error of prediction (RMSEP) values of 4.3802 and 5.4271, respectively. The findings demonstrated the effectiveness of the TLC-SERS method for rapid, sensitive and accurate detection of prohibited drug residues in seafood, with significant implications for food safety monitoring.

基于薄层色谱-表面增强拉曼光谱联合方法的对虾违禁药物残留检测研究。
近年来,海产品中违禁药物残留的检测已成为保障食品安全和公众健康的一个重要方面。建立了一种结合薄层色谱(TLC)和表面增强拉曼光谱(SERS)检测虾样品中氯霉素(CAP)和孔雀石绿(MG)的新方法。由于这两种物质对健康的不良影响和潜在的致癌风险,在中国都受到严格的监管。利用密度泛函理论进行理论计算,得到了CAP和MG的拉曼光谱和SERS光谱。这使得在实验得到的TLC-SRES光谱中提取出它们的特征峰,并解释了在SERS条件下可能发生的拉曼光谱的频移和选择性增强效应。以氯仿-甲醇-水和乙酸乙酯-无水乙醇-水-氢氧化铵为流动相,优化的TLC条件能有效分离目标化合物。这导致分离成功,保留因子Rf分别为0.63和0.66。随后的SERS检测在虾组织中CAP的检出限为0.05 μg·kg-1, MG的检出限为0.47 μg·kg-1。开发了一种结合主成分分析和支持向量回归的机器学习方法,用于定量其TLC-SERS光谱中的残留物。所建立的加标对虾样品中CAP和MG的定量模型具有较好的预测效果,R2值分别为0.9673和0.9847,均方根预测误差(RMSEP)值分别为4.3802和5.4271。结果表明,TLC-SERS方法能够快速、灵敏、准确地检测海产品中违禁药物残留,对食品安全监测具有重要意义。
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