为满足农药残留多组分含量测定的要求，对荧光光谱法测量农药残留得到的混合光谱进行分离，基于偏最小二乘法建立荧光光谱测量系统校正模型，并预测啶虫脒残留量。选择20个特征波长，采用交互验证方法，以预测残差平方和为评价指标，确定最优主成份数，获得了最佳分析模型。通过对预测集进行测试，滤纸带和西红柿表面啶虫脒残留浓度为100，220，450 mg/kg的预测值分别是101.45，222.91，440.08 mg/kg和98.67，208.56，419.22 mg/kg，预测值和真实值的相关系数分别达到0.996和0.988。实验显示，采用偏最小二乘法结合荧光光谱测定啶虫脒农药残留，具有快速、无损、测量精度高等特点，并表明该方法用于定量分析复杂多组分体系是有效的。

To achieve the detection of multi-component pesticide residues, the Partial Least Square(PLS) method was applied to establishing a calibration model of fluorescence spectral measurement systems, and to predict the pesticide residues of acetamiprid by separating the overlapped spectrum in fluorescence spectroscopy of pesticide residues.By taking the predicted residual error square sum as an evaluating criterion, twenty characteristic wavelengths were selected and then the optimal number of principal components and the optimal analysis model were determined by the cross verification method. According to the test of prediction sets (100, 220, 450 mg/kg), predictive values of acetamiprid residues are 101.45, 222.91 and 440.08 mg/kg on the surface of filter paper, and 98.67, 208.56 and 419.22 mg/kg on the surface of tomato. The correlation coefficients between predictive values and true values respectively reach 0.996 and 0.988. The results demonstrate that the method using PLS in fluorescence spectral analysis for measuring the acetamiprid residue has good performance in shorter measuring time, nondestructive testing and higher accuracy and can effectively implement quantitive analysis for complex and multi-component systems.