Recently, surface enhanced Raman scattering (SERS) labels have attracted researchers’ attention owing to their high sensitivity, excellent multiplexing ability, insensitivity to photobleaching and good fidelity of molecular fingerprint, and have been successfully applied to sensing analysis and biological imaging. In this review, we summarize the principle of SERS label-based biosensors, and the state of the art in their application for rapid detection of pesticide residues. The focus of this review is on the design and fabrication of SERS labels and the current status of sensing systems based on different recognition elements. Meanwhile, the challenges in this field are discussed and possible solutions to them are proposed. This review is expect to help expand the application of SERS labels in the detection of pesticide residues and food safety.

Molecularly imprinted polymers (MIPs) with high selectivity to 29 sulfonylurea pesticides were synthesized by precipitation polymerization, using metsulfuron methyl and chlorsulfuron methyl as the template molecules, 4-vinylpyridine as the function monomer, divinylbenzene as the cross-linking agent and acetonitrile as the porogen, and they were characterized by scanning electron microscopy (SEM) and equilibrium adsorption experiments. The results showed that the MIPs exhibited specific adsorption for the 29 sulfonylurea pesticides, and the maximum apparent binding capacity was 13.21 mg/g. The synthesized polymers were used as solid phase extraction sorbents to develop a high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method for the determination of the 29 sulfonylurea residues in agricultural products. In this method, the peak area of sulfonylurea herbicides had a good linear relationship with their concentration in the range of 2–100 μg/L with a correlation coefficient (R²) of more than 0.999, and the limit of quantitation (LOQ) was 10 μg/kg. At different spiked levels, the recoveries of sulfonylurea herbicides in samples ranged from 74.8% to 110.5% with a relative standard deviation (RSD) of not more than 5.3%.