Ratiometric fluorescent probe and smartphone-based visual recognition for H₂O₂ and organophosphorus pesticide based on Ce³⁺/Ce⁴⁺ cascade enzyme reaction

Organicphosphorus is a ubiquitous pesticide that has potential hazards to human health and environmental well-being. Therefore, the precise identification of residues of organophosphorus pesticides (OPs) emerges as an urgent necessity. A ratiometric fluorescent sensor for the detection of OPs by leveraging the catalytic activities of Ce³⁺ and Ce⁴⁺ on the two fluorescent substrates 4-Methylumbelliferyl phosphate (4-MUP) and o-phenylenediamine (OPD) correspondingly was designed. Ce³⁺ can not only dephosphorylate 4-MUP to generate 4-methylumbelliferone (4-MU) with blue fluorescence, but it can also react with H₂O₂ to produce Ce⁴⁺ and hydroxyl radicals (·OH), both of which exhibit peroxidase-like activity. These two species can oxidize the colorless substrate OPD into the yellow fluorescent product 2,3-diaminophenazine (DAP). Owing to the inner filter effect, the produced DAP diminishes the blue luminescence of 4-MU. So, with the increase of H₂O₂ concentration, the blue fluorescence of 4-MU decreased while the yellow fluorescence of DAP increased. A ratiometric fluorescent sensor based on Ce³⁺-4-MUP-OPD triple system was established for H₂O₂ detection with the fluorescence color of the solution changes from blue to yellow. OPs inhibit the activity of acetylcholinesterase (AChE) and prevent AChE and choline oxidase (ChOx) from acetylthiocholine chloride (ATChCl) to produce H₂O₂, thereby OPs can diminish DAP generation and reinstating the blue luminescence of 4-MU. The detection limits of H₂O₂ and OPs using fluorescence spectroscopy are 0.03 μM and 0.59 ng/mL, respectively. However, when coupled with a smartphone color recognition application, the visual detection limits for H₂O₂ and OPs are 9.7 μM and 19.6 ng/mL, respectively. The materials used in this ratiometric sensor are cost-effective and readily available, eliminating the need for material synthesis and simplifying the detection process. Additionally, the sensor integrates with a smartphone color recognition application, further streamlining the detection workflow and enabling real-time data analysis and result feedback. This combination provides a straightforward, efficient and economical solution for monitoring OPs in agricultural products.