Abstract: Abstract: Pesticide residues in fruits or vegetables are detrimental to human health seriously. After spraying pesticides, residual pesticides existed on the surface and internal tissues of fruits or vegetables. The surface pesticide residues were few and uneven, being difficult to distinguish quantitatively losslessly and rapidly with simple spectral detection. In order to prevent acute or chronic toxicity to human health through their residues in agricultural products and foodstuffs, monitoring pesticide residues was extremely crucial to ensure that pesticides in agricultural products were in permitted levels. Therefore, it was important to choose rapid and convenient technique with various advantages, like high sensitivity and selectivity, efficiency, and easy to operate for rapid detection of pesticide residues. The surface-enhanced Raman scattering (SERS) spectroscopy is a high sensitive analytical technology in the detection of trace material, and has been widely used in the field of public security, environmental monitoring and food safety, owing to the advantages of sharp bandwidth, effective signal amplification, rich molecular information and molecular level detection accuracy. Developing an SERS substrate which could be applied in rapid efficient sampling and direct detection in on-spot assay has been one of the keys of SERS research. Hence, the research status of SERS technology was summarized in this paper. In particular, the main technical methods to realize the pesticide residues signal enhancement by designing a reasonable surface-enhanced Raman substrate, and the surface-enhanced Raman spectral signal analysis methods were described in detail. By fabricating an ordered array with so-called "hot spot" of reinforced substrates, the SERS detection signal strength was greatly enhanced compared to the original SERS detection technique in controlling excellent uniformity, reproducibility and stability. The qualitative identification method of pesticide residue by SERS was mainly based on the mathematical model of pesticide characteristic peak shift. Then partial least squares were used to build the quantitative model, and the results showed that the qualitative identification based on SERS to detect trace levels of pesticide residues had high accuracy, but the quantitative analysis still needed further efforts. By the way, the frontier hotspots in the research of SERS detection technology for pesticide residues were pointed out in this paper. According to the actual situation of pesticide residues in fruits and vegetables, much attention has been paid to the flexible SERS substrate due to its powerful properties that met the food or vegetable demand. At the same time, it was proposed that SERS detection instruments should be more miniaturized and integrated, possess multi-channel detection, and have wireless communication and higher stability and repeatability in the development of future pesticide residue detection. In addition, the development trends of SERS technology in rapid detection of pesticide residues were discussed and forecasted. The rapid detection of pesticide residues and characterization techniques with high sensitivity, pollution-free and lossless nature based on SERS technology would have broad application prospects for the supervision on pesticides using.