A triple-mode strategy for ultrasensitive and accurate point-of-care detection of glyphosate based on the carved bimetallic prussian blue nanozyme and gold polyhedra

Abstract

Food safety has become a significant global concern, with particular attention on pesticide residues in agricultural products. Glyphosate, as a pesticide, poses a serious threat to human health and the environment when present as residue in agricultural products. In this study, we utilized MOF as a framework to prepare concave-structured bimetallic prussian blue nanozyme@silver (Co-Fe PBA@Ag). This nanozyme with sunken surface and synergistic effect of Ag nanoparticles exhibited high catalytic activity than common nanozyme and could catalyze TMB to generate oxTMB under the action of hydrogen peroxide, resulting in a color change from colorless to blue in the solution. However, when the target glyphosate was present, it could inhibit the activity of OH· and consequently blocked the color change reaction, causing the solution to turn from blue to colorless. Based on this principle, we established a triple-mode detection system: colorimetry, smartphone app analysis, and SERS for detecting glyphosate residues in agricultural products such as honey, potatoes, and tea leaves. This triple-mode sensor integrated point-of-care detection capability via colorimetry, sensitive monitoring through smartphone app and accurate detection using Raman technology. It showed potential for the implementation of practical on-site monitoring of pesticide residues in agricultural products.