Li_2025_Int.J.Biol.Macromol_311_143900

Recently, the integration of advanced nanomaterials with conventional enzymatic inhibition methods offered a promising strategy for the development of efficient organophosphate pesticides (OPs) discrimination methods. Herein, we proposed to design a sensitive sensor array based on the fluorescence "turn-off" detection model of carbon dots (CDs) - MnO(2) nanosheets (NSs) and three biogenic cholinesterase enzymes (ChEs) as recognition elements for six popular and typical OPs detection. The three ChEs can be inhibited to a different extent by the OPs, leading to diverse fluormetric signal output pattern of each pesticide. Subsequently, linear discriminant analysis (LDA) and hierarchical cluster analysis (HCA) was used to accurately investigate the effectiveness of the sensor array in screening pesticides at 0.1-20 microg/mL. The sensor array displayed high sensibility and well storage stability. More importantly, the sensor array's strong immunity to various interference and the precise recognizing of OPs spiked in grape and pepper samples highlighted its practical feasibility. This promising fluormetric sensor array provides a significant advance for the identification and recognition of OPs residues in cops matrices.