Detection of Phosmet Residues on Navel Orange Skin by Surface-enhanced Raman Spectroscopy

摘要

Residual pesticides such as phosmet in fruit have become a public concern in recent years. In this study, surface-enhanced Raman spectroscopy (SERS) with silver colloid and Klarite substrates was used to detect and characterize phosmet pesticides extracted from the navel orange surfaces. Enhanced Raman signals of phosmet over a concentration range of 5 to 30mg/L were acquired with silver colloid. Partial least squares (PLS) regression combined with different data preprocessing methods was used to develop quantitative models. With the 2nd derivative data preprocessing, the best prediction model of phosmet pesticide was achieved with a correlation coefficient(r) of 0.852 and the root mean square error of prediction (RMSEP) of 5.177mg/L. Enhanced Raman signals of phosmet over a concentration range of 10 to 80mg/L were acquired with Klarite substrates. The PLS model was validated by leave-one-out cross validation. The results showed that the R-P was 0.963, and the RMSEP was 6.424mg/L. This study indicated that SERS is a potential tool for analysis of phosmet pesticide residues.