Abstract: Image cubes containing continuous spectral waveband information, in which the image information could be used for external attribute inspection while the spectral information could be applied to the internal attribute inspection,could be obtained from implementing a hyperspectral image technology which combines the advantages of computer vision and spectroscopy． Apples were adopted as the experimental object. A hyperspectral imaging system with the wavelength range of 400-1 000 nm was built for detecting bruises. The hyperspectral imaging system was used as a powerful tool to determine the effective wavelengths that could be used for the detection of bruises on apples. The optimal wavelength region 550-950 nm for bruise detection was selected by the Principal component analysis (PCA), which is a very effective method for data dimension reduction and feature extraction of the hyperspectral data cube. The effective wavelengths 714 nm with weighing coefficients at peaks was determined using the loading coefficients of the PC4 image of PCA on 400-1 000 nm.