Journal of Analytical Science and Technology (Feb 2024)

Glyphosate detection via a nanomaterial-enhanced electrochemical molecularly imprinted polymer sensor

  • Youssra Aghoutane,
  • Hakan Burhan,
  • Fatih Sen,
  • Benachir Bouchikhi,
  • Nezha El Bari

DOI
https://doi.org/10.1186/s40543-024-00417-5
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 13

Abstract

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Abstract Glyphosate (GLY) is a widely used herbicide with an important role in agriculture. It effectively controls weeds, enhancing agricultural yield and product quality. However, its use raises significant concerns such as potential risks to non-target ecosystems and human health. In response to these concerns, we develop an electrochemical sensor with a molecularly imprinted polymer (MIP) and gold nanoparticles for GLY detection. The sensor includes a screen-printed carbon electrode (SPCE) functionalized with gold nanoparticles and a self-assembled polyvinyl carboxylic acid chloride (PVC-COOH) layer. GLY compounds interact with carboxylic groups and are encapsulated by a polymer of methacrylic acid (MAA) cross-linked with ethylene glycol dimethacrylate (EGDMA). Electrochemical performance was assessed using differential pulse voltammetry (DPV), cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS). Morphological characterization was performed using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and atomic force microscopy (AFM). The sensor exhibits impressive selectivity, detecting GLY within a range of 273–1200 pg/mL with minimal interference from other pesticides. It boasts a low detection limit of 0.8 pg/mL (signal-to-noise ratio S/N = 3) by DPV and 0.001 pg/mL by EIS. The sensor’s versatility extends to various sample types, including surface water, agricultural wastewater, soil, and cucumber, demonstrating high recovery rates (> 96.05%) and low relative standard deviation (RSD) (< 5.7%). The developed MIP sensor is proven to be a valuable tool for rapid and highly sensitive detection of GLY in diverse environmental and agri-food samples.

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