Rapid Detection and Prediction of Norfloxacin in Fish Using Bimetallic Au@ Ag Nano-Based SERS Sensor Coupled Multivariate Calibration.

Abstract

Norfloxacin is an antibiotic in the fluoroquinolone family licenced for use in animals. However, residues in animal products can have negative consequences for consumers. As a result, residue detection in various food matrices must be considered. Norfloxacin accumulates in animal-derived foods, causing deleterious consequences in humans such as foetal deformity, renal failure and drug resistance. A built-in SERS-Au@Ag nanosensor coupled with GA-PLS was used to rapidly detect norfloxacin in the specimen of the spiked fish muscles due to the threat to human lives. A detection limit of 2.36 × 10⁻⁵ μg/mL was realized in the spiked fish muscle sample for norfloxacin compared to the European Commission’s maximum threshold level of 100 μg/kg, indicating the sensor’s ability to detect and quantify norfloxacin at a relatively lower level. The recovery rates (RC) and coefficient of variation (CV) measured in the spiked fish muscle samples for norfloxacin analytes and their standard solutions were between 99.70–105.00% and 0.17–5.21%, respectively. The low CV values imply the reproducibility of the obtained data. The constructed model recorded residual predictive deviations (RPD) greater than three (3), demonstrating the robustness and resilience of the developed genetic algorithm-partial least squares (GA-PLS) model. GA-PLS-built models predicted all results within 4.07 s, which indicates the nanosensor’s ability to rapidly detect norfloxacin in fish to guarantee safety and public health. The SERS probe holds promise for rapid quantification of norfloxacin at microgram per milliliter level in fish to guarantee safety in commerce.