Development of the sustainable green nanosensor using corn silk extract for nitrate detection in leafy vegetables.

Nitrate is prevalent in environment and present in foods of plant origin as part of nitrogen cycle. It is now one of the most pervasive and persistent contaminants in animal food chain. Present work is focussed on development of a novel green nanosensor using corn silk extract for nitrate detection in leafy vegetables (Spinacia oleracea, Amaranthus viridis and Amaranthus cruentus). The green reduced graphene oxide (rGO) and a nanocomposite (G-FeO@rGO) was synthesized for the first-time using corn silk extract and used for fabrication of the nanosensor. Various characterization techniques were used to expose the optical, crystallographic and surface morphology details of the nanosubstrates. Electrochemical studies of the fabricated nanosensor were conducted using the electrochemical impedance spectroscopy (EIS) technique. The performance of NiR/G-FeO@rGO/ITO green nanosensor was the best, in terms of the electrochemical performance parameters among different fabricated nanosensors in the study. The developed green nanosensor demonstrated high sensitivity of 122.1 Ohm/log(mg/L)/cm and lower limit of detection 0.076 mg/L for detection of nitrate in leafy vegetables. The green nanosensor exhibited higher recovery rates (>86%) and high precision in nitrate detection in leafy vegetables (RSD <5.2%). Validation studies were conducted with HPLC technique also. The results of green nanosensor were found in good agreement with HPLC studies (p < 0.05) highlighting the market acceptability with usefulness and effectiveness of the nanosensor for food quality and safety evaluation.