Nanomolar detection of essential amino acid in dairy products using a novel electrochemical sensor based on zinc cobaltite nanoflowers embedded porous 3D reduced graphene oxide
{"title":"Nanomolar detection of essential amino acid in dairy products using a novel electrochemical sensor based on zinc cobaltite nanoflowers embedded porous 3D reduced graphene oxide","authors":"Neethu Sebastian , Wan-Chin Yu , Deepak Balram , Ashish Patel , Deepak Kumar , Virendra Kumar Yadav","doi":"10.1016/j.sintl.2023.100256","DOIUrl":null,"url":null,"abstract":"<div><p>L-tryptophan (L-Trp) is a vital amino acid that sways neuronal function, immunity, and gut homeostasis, and its accurate detection in food samples is crucial. The aim of this study is to integrate zinc cobaltite (ZCO) nanoparticles and 3D porous reduced graphene oxide (rGO) on a screen-printed carbon electrode (SPCE) surface for building a novel electrochemical sensor to sensitively detect L-Trp in food products. A low-temperature aqueous solution method was employed in ZCO nanoflower synthesis and a hydrothermal approach was utilized to prepare 3D rGO. SEM, elemental mapping, XRD, Raman spectroscopy, XPS, and EIS characterizations were performed on the prepared nanocomposite, ZCO/3DrGO. Electrochemical experiments conducted with the cyclic and differential pulse voltammetric techniques were used for effectively assessing the catalytic power of ZCO/3DrGO/SPCE. With a low detection limit of 3 nM, high sensitivity of 19.53 μAμM<sup>−1</sup>cm<sup>−2</sup>, and a broad linear range of 0.08–5.93; 5.93–87.18 μM, the sensor demonstrated promising electrocatalytic activity towards L-Trp. Further, the reliability of the sensor was proved by analyzing its stability, repeatability, reproducibility, and selectivity towards L-Trp. The successful detection of L-Trp in dairy products (yogurt, milk, and cottage cheese) using the proposed sensor evinced its practical feasibility with high recovery of 98.16%–101.16% and low RSD of 2.8%.</p></div>","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":"5 ","pages":"Article 100256"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266635112300030X/pdfft?md5=e43171bae834ffd389b709f234a83c28&pid=1-s2.0-S266635112300030X-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sensors International","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S266635112300030X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
L-tryptophan (L-Trp) is a vital amino acid that sways neuronal function, immunity, and gut homeostasis, and its accurate detection in food samples is crucial. The aim of this study is to integrate zinc cobaltite (ZCO) nanoparticles and 3D porous reduced graphene oxide (rGO) on a screen-printed carbon electrode (SPCE) surface for building a novel electrochemical sensor to sensitively detect L-Trp in food products. A low-temperature aqueous solution method was employed in ZCO nanoflower synthesis and a hydrothermal approach was utilized to prepare 3D rGO. SEM, elemental mapping, XRD, Raman spectroscopy, XPS, and EIS characterizations were performed on the prepared nanocomposite, ZCO/3DrGO. Electrochemical experiments conducted with the cyclic and differential pulse voltammetric techniques were used for effectively assessing the catalytic power of ZCO/3DrGO/SPCE. With a low detection limit of 3 nM, high sensitivity of 19.53 μAμM−1cm−2, and a broad linear range of 0.08–5.93; 5.93–87.18 μM, the sensor demonstrated promising electrocatalytic activity towards L-Trp. Further, the reliability of the sensor was proved by analyzing its stability, repeatability, reproducibility, and selectivity towards L-Trp. The successful detection of L-Trp in dairy products (yogurt, milk, and cottage cheese) using the proposed sensor evinced its practical feasibility with high recovery of 98.16%–101.16% and low RSD of 2.8%.