A novel MIP electrochemical sensor based on a CuFe2O4NPs@rGO nanocomposite and its application in breast milk samples for the determination of fipronil

Abstract

Background: fipronil, a widely utilized insecticide in agriculture, has been shown to have potential health implications as it can accumulate in the environment and affect human health. Electrochemical sensors, specifically those incorporating molecularly imprinted polymers (MIPs), provide an efficient way for the detection of fipronil because of their selectivity and specificity. The combination of CuFe₂O₄NPs and reduced graphene oxide (rGO) exhibits a synergistic effect that enhances sensitivity and selectivity. The composite's effective properties provide a robust platform for fipronil determination in various matrices. This study detected fipronil using an electrochemical sensor based on a glassy carbon electrode (GCE) modified with MIP@CuFe₂O₄NPs@rGO. Results: the synthesized MIP@CuFe₂O₄NPs@rGO material was characterized using various techniques such as Fourier transform infrared (FT-IR) spectroscopy, scanning electron microscopy (FESEM), X-ray diffraction (XRD) analysis, energy dispersive X-ray (EDX) analysis, Brunauer–Emmett–Teller (BET) analysis, X-ray photoelectron spectroscopy (XPS) analysis, and electrochemical impedance spectroscopy (EIS). The modified GCE showed enhanced electrochemical behavior for fipronil, as demonstrated by cyclic voltammetry (CV) and square wave voltammetry (SWV) techniques. Optimization of parameters such as pH, pyrrole concentration, and template concentration further improved sensor performance. The sensor exhibited a linear dynamic range of 1 to 6 nM, with a limit of detection (LOD) of 0.30 nM (S/N = 3) and a limit of quantification (LOQ) of 1.08 nM (S/N = 10), highlighting its sensitivity and reliability. The precision of the method was excellent, with a relative standard deviation of less than 4.0%. When applied to quantify fipronil in breast milk samples, the sensor showed high accuracy and precision, with recoveries ranging from 96.24% to 97.75%. Significance: the sensor offers several advantages, including high sensitivity, specificity, and accuracy. Its ability to detect fipronil in complex matrices such as breast milk highlights its potential for real-world applications in environmental and health monitoring. Overall, this research paves the way for the development of efficient, rapid and eco-friendly sensors for detecting pesticide residues in various environmental and biological samples.