Selective electrochemical determination of norfloxacin in food samples using template-derived recognition cavities and conductive nanostructured networks.

Norfloxacin (NFC) residues in food products remain a concern because of their potential contribution to antimicrobial resistance and adverse health effects. This study presents a disposable electrochemical method for the selective determination of NFC based on template-derived molecular recognition cavities integrated with a conductive AgNWs/MWCNTs nanostructured network on a screen-printed electrode. The conductive scaffold provided an enlarged electroactive surface and facilitated interfacial charge transfer, whereas the molecular recognition cavities enabled selective rebinding of NFC and improved discrimination against matrix interferences. The synergistic integration of molecular recognition and signal transduction generated a sensitive analytical interface for NFC determination in processed extracts from complex food matrices. Under optimized conditions, the proposed sensor exhibited a linear concentration range of 0.16-25.00 µM, with a detection limit of 0.04 µM. The analytical applicability of the method was evaluated using fortified processed extracts of milk, egg, and shrimp, yielding recoveries of 90.1-107.0%, 91.6-106.0%, and 91.7-106.0%, respectively, with relative standard deviations below 8.9%. A limited comparison with HPLC showed no statistically significant differences for the milk extracts at all investigated concentrations or for the egg and shrimp extracts at 25.0 µM; however, significant differences were observed at lower concentrations in the egg and shrimp extracts. The proposed approach demonstrates the potential of molecular recognition cavity-based electrochemical sensing as a rapid, selective, and cost-effective strategy for screening NFC in processed food-sample extracts.