A portable wireless intelligent electrochemical sensor based on layer-by-layer sandwiched nanohybrid for terbutaline in meat products. (1st March 2022)

• Record Type: Journal Article
• Authors: Ge, Yu; Liu, Peng; Xu, Lanjiao; Qu, Mingren; Hao, Wenxue; Liang, Huan; Sheng, Yingying; Zhu, Yifu; Wen, Yangping
• Is Part Of: Food chemistry. Volume 371(2022)
• Publication Date: 2022-03-01
• Subjects: Electrochemical sensor -- Sandwiched nanohybrids -- Terbutaline -- Artificial neural network -- Wireless intelligence; Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2021.131140
• Languages: English
• ISSNs: 0308-8146

Abstract

Highlights: A portable wireless intelligent nanosensor for terbutaline in meat was developed. Layer-by-layer sandwiched nanohybrid based on Pt-Pd NPs/COOH-Gr/MoS2 was prepared. Artificial neural network was used to multivariate simultaneous optimization. Abstract: The aim of this study is to develop a portable wireless intelligent nanosensor (PWIN) for rapid cost-effective on-site determination of terbutaline (TRA) residue in meat products outdoors in comparison with traditional nanosensor and high-performance liquid chromatography (HPLC). The layer-by-layer sandwiched nanohybrid fabricated by platinum-palladium nanoparticles, carboxylated graphene and graphene-like molybdenum disulfide displayed a wide linear range of 0.55–14.9 μmol/L using the portable potentiostat with smartphone, and the result was almost close to the linear range (0.4–14 μmol/L) using the traditional potentiostat with desktop computer for TRA. The limit of detections were identified as 0.44 μmol/L and 0.18 μmol/L, respectively. PWIN displayed satisfactory recovery (91%−98.43%) of TRA in samples by the standard addition method and in comparison with both traditional sensor (93.79%−98%) and HPLC (93.4%–98.6%), revealing that PWIN for rapid cost-effective on-site analysis in the food safety field is feasible.