Rapid Quantitative Analysis of Dimethoate Pesticide Using Surface-enhanced Raman Spectroscopy

Pesticides are widely used in agriculture, and pesticide residues have become a public concern. So far, no analytical method has been available for the rapid and quantitative analysis of most food pesticides. In this study, the application of micro-surface-enhanced Raman spectroscopy (SERS) for analysis of the typical organophosphorus pesticide dimethoate is demonstrated. Huge enhanced Raman signals of pesticides at low concentrations of 0.5 to 10 μg mL were acquired by confocal Raman micro-spectrometry with Klarite substrate. The observed spectra were analyzed by comparison with the normal Raman spectra of dimethoate. Partial least squares (PLS) regression combined with different data preprocessing methods and wavelength selection was applied to develop quantitative models for dimethoate solutions. The best model, with the highest correlation coefficient (0.969) and the lowest root mean square error of predictions (0.626), was achieved with the first derivative combined with standard normalized variate (SNV) spectra and the wavelength bands of 1845.5±1186.9 cm and 1023±199.5 cm. This study indicated that SERS coupled with a nanosubstrate is a potential tool for rapid quantification of pesticide residues at 10 concentration levels.