Detection of systemic pesticide residues in tea products at trace level based on SERS and verified by GC-MS.

Abstract

Surface-enhanced Raman spectroscopy (SERS) has the potential to detect pesticide residues in agricultural products. However, some systemic pesticides, such as chlorpyrifos, can enter the plant tissue, and not just stay on the surface. Consequently, many SERS studies halted at practical application because of its complexity. In this work, SERS technology was used to detect chlorpyrifos residues in tea products at the semiquantitative level. A simple pretreatment method effectively avoided interference of other fluorescent substances, and all major peaks could be distinguished on the basis of a novel substrate. A principal component analysis algorithm was applied to form a regression model, and a nanogram detection limit was obtained. Furthermore, chlorpyrifos residues in the same tea products were also measured by gas chromatography-mass spectrometry, and the results show a small range of errors. From the comparative study of the two detection methods, the results suggest the great promise of SERS technology for rapid inspection of agricultural products.