Abstract: Small detecting zone, long detecting period and limitation to external inspection are included in the deficiencies of singly using computer vision or spectroscopy for non-destructive inspection of fruit quality. 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. As a result, fruit classification based on both internal and external quality attributes could be achieved. Two different methods for acquiring hyperspectral images and the corresponding hardware of hyperspectral imaging system were introduced in this paper. Applications of hyperspectral images to the inspection of bruises, feces or earth contamination, maturity, firmness, SSC(Soluble Solid Content) and other parameters of fruits were reviewed. It mainly focused on the wave band, resolution, image source, data analysis methods and the experimental results. The problems needed to be solved in applying this technique, such as spectral dimensionality reduction, real-time platform building and sample diversity impact, were put forward.