SERS-activated platforms for chemical contaminants in food: Probes, encoding methods, and detection

被引:22
作者
Li, Huanhuan [1 ]
Haruna, Suleiman A. [1 ,3 ]
Sheng, Wei [1 ]
Bei, Qiyi [1 ]
Ahmad, Waqas [2 ]
Zareef, Muhammad [1 ]
Chen, Quansheng [1 ,2 ]
Ding, Zhen [4 ]
机构
[1] Jiangsu Univ, Sch Food & Biol Engn, Zhenjiang 212013, Peoples R China
[2] Jimei Univ, Coll Ocean Food & Biol Engn, Xiamen 361021, Peoples R China
[3] Kano Univ Sci & Technol, Dept Food Sci & Technol, PMB 3244, Kano, Kano State, Nigeria
[4] Changzhou Jintan Jiangnan Powder Co LTD, Changzhou 213200, Peoples R China
基金
中国博士后科学基金;
关键词
SERS; Enhancement mechanism; Substrate; Raman reporter molecules; Chemical contaminants; Multivariate calibrations; ENHANCED RAMAN-SPECTROSCOPY; MOLECULARLY IMPRINTED POLYMER; LABEL-FREE DETECTION; ULTRASENSITIVE DETECTION; MAGNETIC SEPARATION; PESTICIDE-RESIDUES; RAPID DETECTION; HEAVY-METALS; SURFACE; SUBSTRATE;
D O I
10.1016/j.trac.2023.117365
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Surface-enhanced Raman scattering (SERS) has been proven to be an extremely efficient, reliable, and influential technique to monitor or determine various pollutants in food. It has various advantages, including simplicity, sensitivity, speed, and the ability to create distinguishable analyte fingerprints with minimal interference from water. The goal of this review was to evaluate the SERS-based sensor's progress in detecting and monitoring chemical pollutants in food. Over the last decade, significant progress has been made in the analysis of chemical contaminants, particularly pesticides, heavy metals, and mycotoxins. Several factors leading to improved SERS performance, such as SERS substrate, Raman reporter molecules, antibody, aptamer, lab-on-a-chip, molecularly imprinted polymers, as well as SERS tag techniques such as immunochromatographic assay, colorimetry, and imaging, are briefly discussed. The paper also summarized the theory and application of SERS-based label-free sensors and also emphasized the progress in applying mathematical models to SERS analysis of chemical contaminants.
引用
收藏
页数:23
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