Research on identification and determination of mixed pesticides in apples using surface enhanced Raman spectroscopy

Abstract

Residual pesticides in fruits and vegetables have become one of the major food safety concerns around the world. At present, routine analytical methods used for the determination of pesticide residue on the surface of fruits and vegetables are destructive, complex, time-consuming, high cost and not environmentally friendly. In this study, a novel Surface Enhanced Raman Spectroscopy (SERS) method with silver colloid was developed for fast and sensitive nondestructive detection of residual pesticides in fruits and vegetables by using a self-developed Raman system. SERS technology is a combination of Raman spectroscopy and nanotechnology. SERS can greatly enhance the Raman signal intensity, achieve single-molecule detection, and has a simple sample pre-treatment characteristic of high sensitivity and no damage; in recent years it has begun to be used in food safety testing research. In this study a rapid and sensitive method was developed to identify and analyze mixed pesticides of chlorpyrifos, deltamethrin and acetamiprid in apple samples by SERS. Silver colloid was used for SERS measurement by hydroxylamine hydrochloride reduced. The advantages of this method are seen in its fast preparation at room temperature, good reproducibility and immediate applicability. Raman spectrum is highly interfered by noise signals and fluorescence background, which make it too complex to get good result. In this study the noise signals and fluorescence background were removed by Savitzky-Golay filter and min-max signal adaptive zooming method. Under optimal conditions, pesticide residues in apple samples can be detected by SERS at 0.005 μg/cm2 and 0.002 μg/cm2 for individual acetamiprid and thiram, respectively. When mixing the two pesticides at low concentrations, their characteristic peaks can still be identified from the SERS spectrum of the mixture. Based on the synthesized material and its application in SERS operation, the method represents an ultrasensitive SERS performance in apple samples detection without sample pre-treatment, which indicates that it could be served as a useful means in monitoring pesticide residues.