A smartphone-integrated colorimetric microbial assay using glucose metabolism for residual antibiotic detection in foods.

The rapid and accurate detection of residual antibiotics in food is critical for ensuring food safety and public health. In this study, we developed a smartphone-integrated colorimetric sensor array capable of precise, on-site detection of residual antibiotics in food products. The sensor array was designed to monitor glucose metabolism in four distinct bacterial species, each showing different responses to antibiotic exposure. Phenol red, a pH-sensitive indicator, visualized metabolic acidification, generating unique colorimetric fingerprint patterns corresponding to eight antibiotics. The resulting colorimetric changes were analyzed using smartphone-based red/green/blue signal processing, enabling precise antibiotic identification and quantification at low concentrations (0.5-1 μg/mL). The sensor array successfully distinguished all eight antibiotics in real food matrixes, including milk, chicken, pork, and beef. The biosensing platform was implemented as a smartphone application, enabling antibiotic detection without specialized equipment. This smartphone-assisted colorimetric biosensor offers a simple, portable solution for enhancing food safety.