An electrochemical green PC/IL@GCE sensor for trace-level detection of hazardous triclopyr herbicide in serum and fruits

Abstract

The present work reports a green approach for the development of a new electrochemical sensor based on a pectin and ionic liquid composite (PC/IL) for sensitive detection of triclopyr (TCP), which is a useful pesticide. The fabricated sensor was characterized using microscopic (Scanning Electron Microscopy (SEM)), spectroscopic (Energy Dispersive X-ray (EDX) spectroscopy, ultraviolet-visible (UV-vis) spectroscopy, X-ray diffraction (XRD), Fourier Transform Infrared (FTIR) spectroscopy, Electrochemical Impedance Spectroscopy (EIS)), and cyclic voltammetric methods. The sensor displayed a large surface area, high conductivity, and rich porosity, which contributed to achieving high electrochemical performances toward sensing applications. Experimental parameters, including pH, solvent, concentration, frequency, and amplitude, were optimized for the detection of TCP at PC/IL@GCE using voltammetric techniques. The developed sensor exhibited high sensitivity, selectivity and reproducibility for TCP detection with the detection limit (LOD) and quantification limit (LOQ) as low as 223 pg mL−1 and 745 pg mL−1, respectively. The electrode also exhibited satisfactory recovery in the range of 99.64–101.92%, 99.44–100.87%, and 99.02–101.40% for the detection of TCP in real samples of human serum, tomato, and apple, respectively. Additionally, the environmental sustainability of the developed sensor was assessed, demonstrating a 92% greener aspect.

Graphical abstract: An electrochemical green PC/IL@GCE sensor for trace-level detection of hazardous triclopyr herbicide in serum and fruits

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Article information

Article type
Paper
Submitted
27 Mar 2025
Accepted
26 May 2025
First published
15 Jul 2025

Anal. Methods, 2025, Advance Article

An electrochemical green PC/IL@GCE sensor for trace-level detection of hazardous triclopyr herbicide in serum and fruits

P. Tomar, N. Jadon and S. Shrivastava, Anal. Methods, 2025, Advance Article , DOI: 10.1039/D5AY00516G

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