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

Abstract

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 30 mg/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 5.177 mg/L. Enhanced Raman signals of phosmet over a concentration range of 10 to 80 mg/L were acquired with Klarite substrates. The PLS model was validated by leave-one-out cross validation. The results showed that the RP was 0.963, and the RMSEP was 6.424 mg/L. This study indicated ...