Carbon-dot-encapsulated molecularly imprinted polymer as a selective optical sensor for the monitoring of tebuconazole in food samples.

Abstract

Tebuconazole (Tbz) is one of the most widely used fungicides in the agricultural field due to its high efficacy, systemic properties, and broad-spectrum activity. However, the presence of excessive Tbz residues can pose a serious threat to both human and animal health. Conventional detection techniques used to monitor Tbz have drawbacks, including the need for costly equipment and laborious processes. Here, we report a simple and efficient fluorescent sensor based on green-synthesized carbon dot (CD)-encapsulated molecularly imprinted polymers (MIPs) for the rapid detection of Tbz. The experimental parameters, including the solvent, sensor amount, pH, and temperature, were systematically optimized. The sensor demonstrated a strong anti-interference capability in the presence of structurally similar pesticides and common metal ions, indicating its reliability in complex environmental systems. Mechanistic investigations revealed that the fluorescence quenching followed a dynamic quenching mechanism driven by charge-transfer interactions, as supported by UV-vis analysis and temperature-dependent studies. Additionally, the sensor demonstrated good stability during prolonged storage and maintained performance after multiple reuse cycles, highlighting its durability and cost-effectiveness. The sensor demonstrated a linear dynamic range of 1-20 nM and a detection limit of 1.09 nM. An imprinting factor of 5.12 was achieved, indicating the high molecular selectivity and strong sensing specificity of CDs@SiO2@MIPs. A smartphone-based fluorescence sensing system enabled the sensitive and reliable detection of Tbz, along with a linear RGB (G/B ratio) response. Tbz was successfully determined using the proposed approach in wheat, corn, and water samples, with recoveries ranging from 96% to 100%. The developed CDs@SiO2@MIP sensor represents a promising platform for advancing on-site, real-time sensing applications.