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

被引:0
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作者
Youssra Aghoutane
Hakan Burhan
Fatih Sen
Benachir Bouchikhi
Nezha El Bari
机构
[1] Moulay Ismaïl University,Biosensors and Nanotechnology Group, Department of Biology, Faculty of Sciences
[2] Moulay Ismaïl University of Meknes,Biosensors and Nanotechnology Group, Department of Physics, Faculty of Sciences
[3] Kutahya Dumlupinar University,Sen Research Group, Department of Biochemistry
关键词
Glyphosate; Gold nanoparticles; Molecularly imprinted polymer; Screen-printed carbon electrode; Agricultural wastewater; Cucumber;
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摘要
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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