Optimization and performance evaluation of a fluorescent sensor for residual sulfonamide antibiotics in honey samples

Author:

Cao Lingling1,Ying Haiqin1,Zhang Baolin2,Cao Yang2,Li Sumin1,Huang Weihong3,Yang Wenming1ORCID

Affiliation:

1. School of Materials Science and Engineering Jiangsu University Zhenjiang China

2. Zhenjiang Ecological Environment Technology Consulting Center Zhenjiang China

3. School of the Environment and Safety Engineering Jiangsu University Zhenjiang China

Abstract

AbstractIn the quest to address the mounting concerns over sulfonamide antibiotic residues in food, which pose significant threats to public health and food safety, this study introduces a cutting‐edge detection method. Surface molecular imprinting on silicon nanoparticles is harnessed to fabricate a novel fluorescent sensor that exploits the luminescent properties of cadmium telluride (CdTe) quantum dots. This innovative approach aims to detect residual sulfonamide antibiotics with high specificity and sensitivity. At the heart of this research is the development of a core‐shell nanostructure, where silicon dioxide serves as the core, and a molecularly imprinted polymers (MIPs) layer, tailored to recognize sulfamethazine (SM2), forms the shell. The pivotal advancement in this sensor design is the integration of highly fluorescent CdTe quantum dots within the MIPs layer, which significantly enhances the signal response, enabling the detection of SM2 with remarkable precision. The synthesis of this sensor employs a novel strategy, utilizing 3‐aminopropyltriethoxysilane as the functional monomer, while tetraethyl orthosilicate and ammonium hydroxide act as catalysts to facilitate the polymerization reaction. This meticulous process yields a stable core‐shell structure with active fluorescent properties. Experimental results reveal that under optimal conditions, the sensor exhibits a robust linear response to SM2 concentrations ranging from 10 to 60 μmol L−1, with a detection limit as low as 0.78 μmol L−1. Furthermore, when applied to real food samples, such as honey, the sensor not only demonstrates high recovery rates of 92.3%–98.1%, but also maintains a low relative standard deviation of less than 2.5%. The implications of this study are far‐reaching, offering a promising avenue for the rapid and reliable monitoring of antibiotic residues in the food supply chain, thereby safeguarding consumer health and upholding food safety standards.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Publisher

Wiley

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