With the extensive consumption of pesticides, health risk associated with residual pesticides on farm products surface has attracted great attention. However, current detection techniques usually require long testing time and high cost, which could not fulfill the need of rapid detection of random sampling in daily practice. Thus, it is important to develop a rapid in situ method for the detection of residual pesticides on the agriculture products surface. Through preparation of SERS-active nanoparticles, optimization of flexible transparent SERS substrates, and influencing factors analysis of in situ detection, this project focusing on analyzing the influencing factors of nanoparticles assembly, optimizing nanoparticles assembling parameter, constructing nanoparticles assembled structure with high Raman enhancement factor, discussing the relationship between nanoparticles assembled structure and Raman enhancement factor, exploring the method of improving the adsorption capacity for pesticides, and explaining the interface process between SERS substrates and pesticides during the in situ detection the process. By analyzing the influencing factors in the in situ detection the process, optimizing detection technique, elaborating the associated mechanism in detection the process, the project aims to provide theoretical guidance and data support for in situ detection of pesticide residues. The successful implementation of this project could enable the development of a novel simple, rapid, highly sensitive and cost-effective testing method for residual pesticides on irregular shaped farm product surfaces. This novel method could be applied in widespread applications as an onsite rapid random sampling and detection method.