ABSTRACT Extensive antibiotic use has raised concerns over residues in food, necessitating rapid and accurate detection. This study integrates smartphone‐assisted deep learning with aptamer‐functionalized MIL‐101(Fe) nanozymes to build a dual‐recognition biosensor capable of simultaneously identifying and quantifying kanamycin (KAN) and kanamycin B (KMB). MIL‐101(Fe) exhibited strong adsorption energies and high Langmuir‐fitted capacities (28.39 mg/g for KAN; 31.36 mg/g for KMB), indicating monolayer binding at Fe─OH sites that partially suppressed catalytic activity. Aptamer modification enabled selective molecular recognition and accelerated electron transfer, synergistically enhancing nanozyme performance. Coupled with a ResNet‐based multitask model, smartphone imaging achieved accurate classification of single and mixed samples and precise quantification over 5–1000 nM. Tests in honey and beef showed recoveries of 84.71%–111.50%, confirming stability and practicality. Overall, the aptamer‐enhanced MIL‐101(Fe) nanozyme combined with deep learning provides a sensitive, portable approach for on‐site monitoring of antibiotic residues in food.
Qin et al. (Fri,) studied this question.