Cellulose nanofibers coated with silver nanoparticles as a flexible nanocomposite for measurement of flusilazole residues in Oolong tea by surface-enhanced Raman spectroscopy. (15th June 2020)

• Record Type: Journal Article
• Authors: Chen, Xi; Lin, Hetong; Xu, Taotao; Lai, Keqiang; Han, Xue; Lin, Mengshi
• Is Part Of: Food chemistry. Volume 315(2020)
• Publication Date: 2020-06-15
• Subjects: Hybrid nanocomposites -- Cellulose nanofiber -- Silver nanoparticles -- Surface-enhanced Raman spectroscopy (SERS) -- Flusilazole -- Oolong tea; Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2020.126276
• Languages: English
• ISSNs: 0308-8146

Abstract

Graphical abstract: Highlights: Surface-enhanced Raman spectroscopy (SERS) is a novel tool for detecting pesticide. Hybrid nanocomposites consisted of CNF coated with AgNP were synthesized. CNF-AgNP nanocomposites were uniform, porous, and flexible. The CNF-AgNP nanocomposite was used as a sensitive SERS substrate. The CNF-AgNP substrate can be utilized for detection of flusilazole in Oolong tea. Abstract: Cellulose nanofibers (CNF) coated with inorganic nanoparticles are novel hybrid nanocomposites that have great potential in various areas including agriculture and food science. The objectives of this study were to synthesize nanocomposites consisted of CNF coated with silver nanoparticles (AgNPs), which can be used as a surface-enhanced Raman spectroscopy (SERS) platform for measuring pesticides in Oolong tea. CNF were coated with AgNPs to form uniform CNF-AgNP nanocomposites that were investigated by transmission electron microscopy. Three-dimensional and porous CNF structures were loaded with AgNPs with an average size of 41 nm. CNF-AgNP substrates were applied in characterization and measurement of flusilazole in Oolong tea samples by SERS. A detection limit of 0.5 mg/kg for flusilazole was obtained based on partial least squares (PLS) regression analysis. These results indicate that CNF-AgNP nanocomposites combined with SERS is an accurate, sensitive, and efficient technique for identification and quantification of pesticide residues in Oolong tea.