A spectroscopic approach to detect and quantify phosmet residues in Oolong tea by surface-enhanced Raman scattering and silver nanoparticle substrate

• Published in: Food chemistry Vol. 312; p. 126016
• Main Authors: Chen, Xi, Wang, Danhong, Li, Jie, Xu, Taotao, Lai, Keqiang, Ding, Qi, Lin, Hetong, Sun, Lin, Lin, Mengshi
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 15.05.2020
• Subjects: Color; Least-Squares Analysis; Limit of Detection; Metal Nanoparticles - chemistry; Oolong tea; Pesticide; Pesticide Residues - analysis; Phosmet; Phosmet - analysis; Silver - chemistry; Silver nanoparticles; Spectrum Analysis, Raman - methods; Surface-enhanced Raman scattering (SERS); Tea - chemistry; Surface-enhanced Raman scattering (SERS); Pesticide; Phosmet; Oolong tea; Silver nanoparticles
• ISSN: 0308-8146; 1873-7072
• DOI: 10.1016/j.foodchem.2019.126016

•Spherical and monodispersed AgNPs were synthesized for SERS measurement.•SERS based on AgNPs generated strong enhancement of Raman signals.•Detection limit of phosmet in Tieguanyin Oolong tea was 0.1 mg/kg.•SERS based on AgNPs is a novel tool for detecting phosmet in Oolong tea. There have been increasing concerns among consumers about pesticide residues in Oolong tea. This study aimed to establish surface-enhanced Raman scattering (SERS) method for rapid measurement of chemical contaminants in Oolong tea. Synthesis of SERS substrate was achieved by synthesizing silver nanoparticles (AgNPs) via a reduction method. AgNPs were spherical and highly monodispersed, which created remarkable electromagnetic fields during SERS activities to measure phosmet in the methanol-water solution and Oolong tea. Partial least squares regression models were established to predict the concentrations of phosmet in the methanol-water solution (r = 0.934; slope = 0.880; RMSEP = 1.001 mg/L) and Oolong tea samples (r = 0.927; slope = 0.938; RMSEP = 1.157 mg/kg) with the detection limit of 0.1 mg/kg. The results indicate that SERS coupled with silver nanoparticles is a fast, sensitive, and reliable method for detection and characterization of pesticide contaminants in Oolong tea products.