A nondestructive testing based on visible/near-infrared reflectance spectroscopy was put forward for the common high pesticide residues of green plants in the wavelength range from 600 to 1 100 nm. Firstly, spectral features were extracted by wavelet transform from original spectral data. Secondly,the principal component analysis (PCA) was done in the further analysis of spectral characteristics. Thirdly, the two PCs were applied as inputs of artificial neural network, and a multi-neuron perceptron neural network was established. Finally, It was proved that the type of pesticide residues was effectively identified and showed by classification results. In short, the study provides a new approach to the detection of pesticide residues in vegetables and fruits.