Comprehensive SERS–LFIA Platform for Ultrasensitive Detection and Automated Discrimination of Chloramphenicol Residues in Aquatic Products
Shuai Zhao, Chenglong Lin, Meimei Xu, Weida Zhang, Dan Li, Yusi Peng, Qing Huang, Yong Yang
Abstract
With the increasing misuse of antibiotic drugs, the convenient and ultrasensitive detection of chloramphenicol (CAP) is essential for ensuring food safety and human health. In this study, a comprehensive platform was developed integrating detection and discrimination capabilities by combining surface-enhanced Raman scattering (SERS) with lateral flow immunoassay (LFIA) technology, along with a support vector machine (SVM) model for data analysis, to detect CAP residues in aquatic products. The CAP-specific antibody-modified gold nanostars (Au NSs) were synthesized as SERS–LFIA nanoprobes, achieving an ultralow limit of detection (LOD) of 10 pg/mL and a theoretical LOD of 1.6 pg/mL for simulated aquatic samples. This sensitivity surpasses that of the currently available commercial strips and demonstrates high specificity. Additionally, the automated discrimination model exhibited high sensitivity (95.83%) and specificity (96.43%) as well as an accuracy of 96% on the test set, marking an 8% improvement over traditional Raman intensity discrimination methods. This developed platform is a simple, fast, and automated technique that eliminates the need for sample pretreatment, offering a promising approach for the trace detection of CAP in aquatic products.