Detection of Heavy Metals in Food and Agricultural Products by Surface-enhanced Raman Spectroscopy

ABSTRACT

Heavy metals accumulating in the human body produce physiological toxicity by interfering with the transport of human proteins and enzymes. Heavy metals detection is significant for food safety assurance. This review focuses on recent advances of heavy metals detection of food and agricultural products by surface-enhanced Raman spectroscopy (SERS). The article covers the SERS basic principles and advances in heavy metals detection, including mercury, arsenic, cadmium, lead, chromium among others. Insights in the potential of combining chemometrics and multivariate analysis with SERS and the exploration of novel SERS substrate platforms from both macro and micro scale are discussed. Finally, future application of SERS in heavy metal detection are prospected. SERS is a powerful and promising technique offering the advantages of simple sampling, rapid data collection and non-invasiveness. The findings of this study can allow better understanding of the heavy metals’ occurrence and the possibility of its detection using SERS.

KEYWORDS:

• Food safety
• heavy metal
• surface-enhanced raman spectroscopy
• nanoparticles
• chemometrics
• substrate platforms

Abbreviations

2-MPy, 2-Mercaptopyridine; 4-MBA, 4-Mercaptobenzoic acid; AAS, Atomic absorption spectroscopy; air-PLS, Adaptive iteratively reweighted penalized least squares; ANN, Artificial neural network; ARS, Alizarin red; CART, Classification and regression trees; CDC, Centers for Disease Control and Prevention; DFA, Discriminant function analysis; DFT, Density functional theory; DMA(v), Dimethyl arsenic acid; DPA-TAM, Di-2-picolylamine- conjugated Triaryl methine; EA, Evolutionary algorithm; EF, Enhancement factor; EM, Electromagnetic; EP, Evolutionary programming; FDTD, Finite difference time domain; GA, Genetic algorithm; GC-MS, Gas chromatography-mass spectrometer; GO, Graphene oxide; GSH, Glutathione; HDL, High-density lipoproteins; HPLC, High performance liquid chromatography; ICP-MS, Inductively coupled plasma mass spectrometry; LC-MS, Liquid chromatography-mass spectrometer; LFIAs, Lateral flow immunoassays; LOD, Limit of detection; MLP, Multilayer perceptron; MMA(V), Monomethyl arsenic acid; MPBA, 4-mercaptophenylboronic acid; MWPLS, Moving windows partial least squares; NHMs, Nano hybrid materials; pAsA, P-Arsanilic acid; PCL, Polycaprolactone; PCR, Principal components regression; PDMS, Polydimethylsiloxane; PLS, Partial least squares; PLS-DA, Partial least-squares followed by a discriminant analysis; PLSR, Partial least square regression; PMMA, Polymethylmethacrylate; PMTTP4, (4-Phenylmethanethiol)-2,2’:6’,2 ‘‘-terpyridine; RF, Random forests; Rox, Roxarsone; RRS, Rayleigh scattering; SELEX, Systematic evolution of ligands by exponential enrichment; SERS, Surface-enhanced Raman spectroscopy; SNV, Standard normal variance; SVM, Support vector machine; TDS, Total diet study;TERS, Tip-enhanced raman spectroscopy; THQ, Target hazard quotient; TMBOX, 3, 3′, 5, 5′-Tetramethylbenzidine diimine; USEPA, United states environmental protection agency; VFA, Volatile fatty acids; WHO, World Health Organization.

Credit author statement

Zhiming Guo: Conceptualization, Supervision, Funding acquisition, Project administration. Ping Chen and Nermeen Yosri: Writing - original draft. Quansheng Chen: Resources. Hesham R. El-Seedi, Xiaobo Zou and Hongshun Yang: Writing - review & editing. All authors read and approved the final manuscript.

Declaration of competing interest

The authors declare no conflict of interest.

Acknowledgments

The authors acknowledge the financial support provided by the National Natural Science Foundation of China (31972151), National Key R&D Program of China (2018YFC1604401), Key R&D Project of Jiangsu Province (BE2018307, BE2019359), China Scholarship Council (CSC) (201908320217), the Postgraduate Research and Practice Innovation Program of Jiangsu Province (SJCX20_1429), and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [31972151]; National Key R&D Program of China [2018YFC1604401]; Key R&D Project of Jiangsu Province [BE2018307,BE2019359]; China Scholarship Council (CSC) [201908320217]; the Postgraduate Research and Practice Innovation Program of Jiangsu Province [SJCX20_1429], and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).