Abstract

A high-sensitivity fluorescence visualization paper-based sensor is developed and used to achieve specific detection and analysis of three organophosphorus pesticides (OPPs: dimethoate, dichlorvos, and demeton) in a "Turn-off-on" detection mode. The fluorescence visualization paper-based sensor is established through combining double quantum dots (QDs) with high-activity nanoporphyrins (QDs-nanoporphyrin), realizing double nanometer signal amplification and producing different color change responses to these three OPPs. In particular, this approach is based on Partial least squares discriminant analysis (PLSDA) for fingerprint spectrum analysis of three kinds of organophosphorus pesticides in complex matrix (apple and cabbage). Therefore, different concentrations of pesticide residues can be quickly identified at the same time with 100% accuracy for both training set and prediction set. In summary, this method has high selectivity and stability, and thus provides a new approach for the identification of organophosphorus residues in complex systems.

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