4.7 Article

Silver nanoparticle-decorated TiO2 nanotube array for solid-phase microextraction and SERS detection of antibiotic residue in milk

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.saa.2021.119652

关键词

Surface-enhanced Raman scattering (SERS) spectroscopy; Nanotube array; TiO2; Silver; Solid-phase microextraction (SPME)

资金

  1. National Natural Science Foundation of China [21503021]
  2. Science and Technology Projects in the 13th Five-year Plan of the Education Department of Jilin Province, China [JJKH20200650KJ]

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The excessive use or abuse of antibiotics in dairy cows can lead to residues in milk, posing a potential risk to public health. In response to the ineffectiveness of traditional antibiotic detection methods, there is an urgent need for the development of multi-analyte analysis techniques for detecting antibiotic residues.
The excessive use or abuse of antibiotics on dairy cows leads to residues in milk, which can represent a public health risk. However, in recent years the beta-Lactamase was illegally used to degrade residual antibiotics in milk, which makes the traditional antibiotic detection methods ineffective. Therefore, there is an extremely urgent need for multi-analyte analysis techniques for the detection of antibiotic residues. Herein, we reported an ultra-fast, facile, and sensitive solid-phase microextraction (SPME)-surface enhanced Raman scattering (SERS) platform for the detection of degraded antibiotics-2-mercapto- 5-m ethyl-1,3,4-thiadiazole (MMT). The results showed that the log-log plot of SERS intensity to MMT concentration exhibits a superior linear relationship (R-2 = 0.992) in the concentration range of 0.5-1000 mu M, with a detection limit of 0.11 mu M. The silver nanoparticle-decorated TiO2 nanotube array was successfully used as an all-in-one SPME-SERS substrate in the extraction and identification of the antibiotic degradation products in real milk. Due to the rapid pre-treatment, good reproducibility, and self-cleaning, the proposed SPME-SERS method has a great promise to be applied as a powerful tool for on-site detection in the field of food safety. (C) 2021 Elsevier B.V. All rights reserved.

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