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The possibility of using near-infrared microscopic imaging to discriminate meat and bone meal (MBM) in concentrate supplement was investigated. Samples of MBM and dairy concentrate supplement were collected, and the sediment particles were prepared and arranged on polytetrafluoroethene (PTFE) background plate for near infrared imaging. Image size was 5000 μm×5000 μm, using 50 μm pixel resolution (10000 spectra were obtained). Each spectrum was across the wavelength range 7800~4000 cm-1 , with 8 cm-1 data resolution. Both principal component analysis and fuzzy clustering analysis were used to extract and present relevant information from NIR microscopic imaging data sets. The results showed that MBM could be distinguished from dairy concentrate supplement by the scores from principal component analysis, and the samples were subdivided by using fuzzy C-means clustering based on the PCA analysis. It is demonstrated that NIR microscopic imaging approach is one of the most promising methods for detecting MBM. 