An Integrated Platform and Method for Rapid High-Throughput Quantitative Detection of Organophosphorus Pesticide Residues

The degree of harm caused by pesticide residues is closely related to its type and concentration. Current enzyme biosensor technology used for pesticide residue detection has limitations, including lacking a built-in heating mechanism and an integrated platform for electrical impedance measurement technology to perform the qualitative and quantitative analysis. This study proposes a high-throughput detection integrated platform and method based on enzyme sensors. First, a double-layer electrode structure was developed to accommodate enzyme-inhibited biological reactions and temperature control functions. Subsequently, a high-throughput integrated detection platform was established, targeting three organophosphorus pesticides: dichlorvos, diazinon, and malathion. Time-series impedance data obtained during the enzyme inhibition reactions were used as features, combined with machine learning to analyze pesticide residues. The classification decision tree identified pesticide types with a 96.3% accuracy rate. The regression decision tree predicted the concentration range of pesticide residues (0.1 mg/kg) with an average coefficient of determination of 0.953. Moreover, this method can analyze 32 samples within 15 min. Finally, accurate sample analyses were conducted and compared with gas chromatography, demonstrating good consistency. This approach meets the rapid detection requirements of the pesticide residue testing market and offers significant applicability and practicality.