Rapid and ultrasensitive detection of food contaminants using surface-enhanced Raman spectroscopy-based methods

分析物 生化工程 食品安全 纳米技术 表面增强拉曼光谱 拉曼光谱 材料科学 污染 环境科学 环境化学 拉曼散射 化学 色谱法 食品科学 生物 光学 工程类 物理 生态学
作者
Yahui Guo,Mogos Girmatsion,Hung‐Wing Li,Yunfei Xie,Weirong Yao,He Qian,Bereket Abraha,Abdu Mahmud
出处
期刊:Critical Reviews in Food Science and Nutrition [Informa]
卷期号:61 (21): 3555-3568 被引量:53
标识
DOI:10.1080/10408398.2020.1803197
摘要

With the globalization of food and its complicated networking system, a wide range of food contaminants is introduced into the food system which may happen accidentally, intentionally, or naturally. This situation has made food safety a critical global concern nowadays and urged the need for effective technologies capable of dealing with the detection of food contaminants as efficiently as possible. Hence, Surface-enhanced Raman spectroscopy (SERS) has been taken as one of the primary choices for this case, due to its extremely high sensitivity, rapidity, and fingerprinting interpretation capabilities which account for its competency to detect a molecule up to a single level. Here in this paper, we present a comprehensive review of various SERS-based novel approaches applied for direct and indirect detection of single and multiple chemical and microbial contaminants in food, food products as well as water. The aim of this paper is to arouse the interest of researchers by addressing recent SERS-based, novel achievements and developments related to the investigation of hazardous chemical and microbial contaminants in edible foods and water. The target chemical and microbial contaminants are antibiotics, pesticides, food adulterants, Toxins, bacteria, and viruses. In this paper, different aspects of SERS-based reports have been addressed including synthesis and use of various forms of SERS nanostructures for the detection of a specific analyte, the coupling of SERS with other analytical tools such as chromatographic methods, combining analyte capture and recognition strategies such as molecularly imprinted polymers and aptasensor as well as using multivariate statistical analyses such as principal component analysis (PCA)to distinguish between results. In addition, we also report some strengths and limitations of SERS as well as future viewpoints concerning its application in food safety.

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