The objectives of the present study were to explore new sensitive spectral bands and ratio spectral indices based on precise analysis of ground-based hyperspectral information, and then develop regression model for estimating leaf N accumulation per unit soil area (LNA) in winter wheat (Triticum aestivum L.). Three field experiments were conducted with different N rates and cultivar types in three consecutive growing seasons, and time-course measurements were taken on canopy hyperspectral reflectance and LNA under the various treatments. By adopting the method of reduced precise sampling, the detailed ratio spectral indices (RSI) within the range of 350-2 500 nm were constructed, and the quantitative relationships between LNA (gN·m-2) and RSI (i, j) were analyzed. It was found that several key spectral bands and spectral indices were suitable for estimating LNA in wheat, and the spectral parameter RSI (990, 720) was the most reliable indicator for LNA in wheat. The regression model based on the best RSI was formulated as y=5.095x-6.040, with R2 of 0.814. From testing of the derived equations with independent experiment data, the model on RSI (990, 720) had R2 of 0.847 and RRMSE of 24.7%. Thus, it is concluded that the present hyperspectral parameter of RSI (990, 720) and derived regression model can be reliably used for estimating LNA in winter wheat. These results provide the feasible key bands and technical basis for developing the portable instrument of monitoring wheat nitrogen status and for extracting useful spectral information from remote sensing images.