Magnetic Fe3O4@COF@Ag SERS substrate combined with machine learning algorithms for detection of three quinolone antibiotics: Ciprofloxacin, norfloxacin and levofloxacin

Zichen Yang; Guoqing Chen; Chaoqun Ma; Jiao Gu; Chun Zhu; Lei Li; Hui Gao

doi:10.1016/j.talanta.2023.124725

Magnetic Fe₃O₄@COF@Ag SERS substrate combined with machine learning algorithms for detection of three quinolone antibiotics: Ciprofloxacin, norfloxacin and levofloxacin

Talanta. 2023 Oct 1:263:124725. doi: 10.1016/j.talanta.2023.124725. Epub 2023 May 23.

Authors

Zichen Yang¹, Guoqing Chen², Chaoqun Ma³, Jiao Gu³, Chun Zhu³, Lei Li³, Hui Gao³

Affiliations

¹ School of Science, Jiangnan University, Wuxi, China; School of Internet of Things Engineering, Jiangnan University, Wuxi, China; Jiangsu Provincial Research Center of Light Industrial Optoelectronic Engineering and Technology, Wuxi, China.
² School of Science, Jiangnan University, Wuxi, China; Jiangsu Provincial Research Center of Light Industrial Optoelectronic Engineering and Technology, Wuxi, China. Electronic address: jncgq@jiangnan.edu.cn.
³ School of Science, Jiangnan University, Wuxi, China; Jiangsu Provincial Research Center of Light Industrial Optoelectronic Engineering and Technology, Wuxi, China.

PMID: 37270860
DOI: 10.1016/j.talanta.2023.124725

Abstract

Quinolone antibiotics have good antibacterial properties and are commonly used antibiotics in the dairy industry. Currently, the problem of excessive antibiotics in dairy products is very serious. As an ultra-sensitive detection technology, Surface-Enhanced Raman Scattering (SERS) was applied to the detection of quinolone antibiotics in this work. In order to classify and quantify three antibiotics (Ciprofloxacin, Norfloxacin, Levofloxacin) with highly similar molecular structures, a combination of magnetic COF-based SERS substrate and machine learning algorithms (PCA-k-NN, PCA-SVM, PCA-Decision Tree) was used. The classification accuracy of the spectral dataset could reach 100% and the results of LOD calculation were: CIP: 5.61 × 10^-9M, LEV: 1.44 × 10^-8M, NFX: 1.56 × 10^-8M. This provides a new method for the detection of antibiotics in dairy products.

Keywords: Dairy products; Magnetic SERS substrate; Quinolone antibiotics; Surface-enhanced Raman scattering (SERS).

MeSH terms

Algorithms
Anti-Bacterial Agents
Ciprofloxacin*
Levofloxacin
Magnetic Phenomena
Norfloxacin*

Substances

Ciprofloxacin
Norfloxacin
Levofloxacin
Anti-Bacterial Agents