A hyperspectral imaging system is developed to detect dichlorvos residue on the surface of navel orange. After acquiring hyperspectral images of 400 navel oranges, the actual content of dichlorvos residue is measured by gas chromatography. Optimal wavelengths are extracted using the regression coefficients of partial least squares (PLS), and a PLS model with 12 factors is established. In the prediction set of 0.2282?11.652-mg/kg pesticide residue, the correlation coefficient and the root mean standard error are 0.8320 and 1.3416, respectively. The hyperspectral imaging technology can meet the requirement of online fast nondestructive detection.