采用拉曼光谱技术结合QuEChERS(Quick Easy Cheap Effective Rugged and Safe)样本前处理建立了黄瓜上吡虫啉残留量的快速检测方法.以进行了不同前处理步骤(乙腈提取、去水萃取、褪色除杂)的三批黄瓜样本作为实验对象,利用780 nm激光器采集样本的拉曼光谱图,并分别采取偏最小二乘(PLS)和主成分回归(PCR)算法建立了六个黄瓜中吡虫啉含量预测模型.结果表明,仅进行了乙腈(C2H3N)提取一步前处理的样本建模效果最优,校正集及预测集的相关系数均在0.99以上,其中PLS的预测集相对分析误差(RPD)达到5.52,说明模型具有一定的预测精度,此结果可为后续前处理简化研究提供有力依据.“,”Raman spectroscopy has been more and more frequently used for pesticide residue detection research in recent years, but the development of sample pretreatment technology is relatively lagging behind. In the study, a rapid method had been developed for the determination of imidacloprid residue in cucumbers with the application of Raman spectroscopy technology and Quick Easy Cheap Effective Rugged and Safe (QuEChERS) sample preparation. Three batches of cucumber samples (the concentration of imidacloprid was within the range of 0.2-5 mg/kg) with different preparation steps (acetonitrile extraction, dehydrate extraction, and fading removing impurity) were chosen as experimental objects. Confocal micro Raman spectrometer was utilized with a 780 nm laser to collect three batches of samples of Raman spectra. Six quantitative prediction models of imidacloprid residue were established based on PLS and PCR methods. The results showed that in addition to the PCR model of the samples by two steps preparation, the residual predictive deviation (RPD) of the other five models was higher than 3. The samples which were only extracted with acetonitrile got the best modeling effect. The correlation coefficient of the calibration set and the prediction set were all above 0.99. The root mean square error of prediction (RMSEP) of PLS method was 0.148 mg/kg, and the RPD was 5.52, which obtained the highest precision of the six predictive models. The results could provide a strong basis for the following-up studies.