A Recycled-Material-Based Electrochemical Eco-sensor for Sensitive Detection of Antischistosomal Drug Residues in Bovine-Derived Food Samples

Abstract

Veterinary drug residues in food have emerged as an urgent threat to consumer safety. Herein, we present the first square wave voltammetric method for the trace-level detection of cinnarizine residues, a recently used antischistosomal drug, in bovine food samples. The method depends on the electrochemical oxidation after modification of the carbon paste sensor with recycled Al₂O₃-NPs functionalized multi-walled carbon nanoparticles. The produced sensor (Al₂O₃-NPs/ MWCNTs/CPE) was characterized using the transmission electron microscope, scanning electron microscope, Fourier-transform infrared spectroscopy, energy-dispersive spectrometer, and X-ray diffractometer that confirm the successful incorporation of the Al₂O₃-NPs/MWCNTs composite into the modified electrode. As expected, the active surface area and electron transfer processes were accelerated by the modification, which was evidenced by cyclic voltammetry, chronoamperometric studies, scan rate studies, and electrochemical impedance spectroscopy. Compared to previous techniques, this facile sensor demonstrated enhancements across critical analytical criteria including the detection limit of 0.17 nM, linear response across 5–100 nM (r² = 0.998), accuracy ranging from 96.5 to 103.2%, precision below 0.81% relative standard deviation, reproducibility within 0.36% range, 20 s response time and applicability in spiked food matrices. In addition, five different greenness and whiteness tools quantified exceptional environmental friendliness, economic feasibility and waste reduction of 63%–93%, reaffirming alignment with sustainability paradigms. These advantages support practical adoption in quality control especially laboratories lacking expensive instrumentation. Overall, the ingenious sensor reconciles nanotechnology innovation with the circular economy ethos to tackle an urgent food safety challenge, guided holistically by sustainability metrics.