The NDF (Neutral Detergent Fiber) and ADF (Acid Detergent Fiber) concentrations in maize stalk were analyzed with 147 samples selected from 600 samples of different eco-environments, hybrids and inbred lines, development stages, and various parts of the plants in two years. The technique of near infrared reflectance spectroscopy (NIRS) and partial least square (PLS) regression were used to establish the models. The results showed that the calibration models developed by the spectral data pretreatment of the first derivative + vector normalization, and the first derivative + multivariate scattering correction were the best for NDF and ADF with the same spectral regions (7501.7-5449.8 cm(-1) and 4601.3-4246.5 cm(-1)). All these models yielded coefficients of determination of calibration (R2(cal)) for NDF and ADF that are higher than 0.94, while R2(cv) and R2(val) ranged from 0.92 to 0.96 for cross and external validation. The root mean square error of estimation, root mean square error of cross validation, and root mean square error of prediction (RMSEE, RMSECV and RMSEP) for NDF and ADF ranged from 1.49% to 1.81%. The models can be used to measure various samples in screening and evaluating quality constituents of silage maize.