A portable wireless intelligent electrochemical sensor based on layer-by-layer sandwiched nanohybrid for terbutaline in meat products

•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. The aim of this study is to develop a portable wireless...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Food chemistry 2022-03, Vol.371, p.131140-131140, Article 131140
Hauptverfasser: Ge, Yu, Liu, Peng, Xu, Lanjiao, Qu, Mingren, Hao, Wenxue, Liang, Huan, Sheng, Yingying, Zhu, Yifu, Wen, Yangping
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:•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. 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.
ISSN:0308-8146
1873-7072
DOI:10.1016/j.foodchem.2021.131140