Nanocomposite enhanced molecularly imprinted polymer for electrochemical detection of naringenin in plant-based samples

Abstract

A novel molecularly imprinted polymer (MIP)-based electrochemical sensor has been developed for the selective detection of naringenin (NAR) in various real-world samples, including plant extracts, wine, and herbal supplements. To enhance the active surface area and porosity of the glassy carbon electrode (GCE), a 2D/0D nanocomposite composed of graphene oxide (GO) and cobalt ferrite (CFO) nanoparticles, CFO_GO, was incorporated into the sensor design. 4-aminobenzoic acid (4-ABA) was selected as the functional monomer to prepare the MIPs. The polymerization process was performed using ethylene glycol dimethacrylate (EGDMA) as the crosslinking agent, 2-hydroxyethyl methacrylate (HEMA) as the basic monomer, and 2-methylpropiophenone as the initiator. The developed MIP-based sensor was designed for the electrochemical detection of NAR in real samples such as Solanum lycopersicum L. (tomato) fruit, Citrus × limon (L.) Osbeck (lemon), oak (Quercus) bark, red wine, and herbal supplements demonstrate their potential for practical applications in analyzing food and herbal products. Morphological and electrochemical characterizations of the designed NAR/CFO_GO/4-ABA@MIP-GCE sensor were performed using scanning electron microscopy (SEM), cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS). The linear range for the determination of NAR using the indirect method (5.0 mM [Fe(CN)6]-3/-4) was found to be 1.0 × 10-13 M-1.0 × 10-12 M, and the limit of detection (LOD) and limit of quantification (LOQ) for standard solutions were 2.84 × 10-14 and 9.47 × 10-14 M, respectively. As a result of the study, the developed MIP-based electrochemical sensor was suitable for detecting NAR with high specificity, selectivity, and sensitivity. Additionally, recovery studies were performed to determine the practical applicability of the sensor, and the results were satisfactory. The developed sensor platform can be considered a reliable and sensitive analytical tool for determining NAR.