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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.
Zhao et al. (Thu,) studied this question.