Abstract：
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-Fe3O4@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-Fe3O4@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)/cm2 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.
摘要：
硝酸盐在环境中普遍存在，并作为氮循环的一部分存在于植物来源的食物中。它现在是动物食物链中最普遍和最持久的污染物之一。目前的工作重点是开发一种新型的绿色纳米传感器，该传感器使用玉米丝提取物检测叶类蔬菜中的硝酸盐（Spinaciaoleracea，Amaranthusviridis和Amaranthuscruentus）。使用玉米丝提取物首次合成了绿色还原氧化石墨烯（rGO）和纳米复合材料（G-Fe3O4@rGO），并用于制造纳米传感器。各种表征技术被用来暴露光学，纳米衬底的晶体学和表面形貌细节。使用电化学阻抗谱（EIS）技术对制造的纳米传感器进行电化学研究。NiR/G-Fe3O4@rGO/ITO绿色纳米传感器的性能最好,在研究中不同制造的纳米传感器之间的电化学性能参数方面。开发的绿色纳米传感器具有122.1欧姆/log（mg/L）/cm2的高灵敏度和0.076mg/L的检测下限，用于检测叶类蔬菜中的硝酸盐。绿色纳米传感器在叶类蔬菜硝酸盐检测中具有较高的回收率（>86％）和较高的精度（RSD<5.2％）。验证研究也用HPLC技术进行。发现绿色纳米传感器的结果与HPLC研究非常吻合（p<0.05），突出了纳米传感器在食品质量和安全性评估中的有用性和有效性。
