Abstract: Quick, non-destructive and accurate monitoring and diagnosis of plant nitrogen accumulation (PNA) is important for site-specific N management in winter oilseed rape production. To develop a method for determining PNA of winter oilseed rape (Brassica napus L.) with the hyperspectral techniques, field experiments were carried out for two growing seasons (2013-2014 and 2014-2015) at Meichuan town (30°06′47′′ N, 115°35′35′′ E), Hubei province, China. Rapeseed cultivar of Huayouza No. 9 (with low glucosinolate and erucic acid concentrations) was chosen as the test cultivar. Five N (as urea) fertilization rates were applied in the 2013-2014 growing season, i.e., 0 (N0), 90 (N90), 180 (N180), 270 (N270) and 360 kg/hm2 (N360). Additionally, for further examining the effects of N status on crop growth and spectral reflectance characteristics, three additional N rates, 45 (N45), 135 (N135) and 225 kg/hm2 (N225) were applied in the 2014-2015 growing season. Canopy hyperspectral reflectance and PNA under different N application rates at seedling, budding and flowering stage during the two growing seasons were measured separately using a Field Spec Pro spectrometer (Analytical Spectral Devices Inc. (ASD), Boulder, CO, USA) and chemical assays in the laboratory. Using linear and nonlinear regression methods, the estimate model for PNA of winter oilseed rape was built on the basis of the experiment data in 2013-2014 acted as training data set, and its precision had been evaluated and tested based on the experiment data in 2014-2015 acted as testing data set. The coefficient of determination (R2), relative root mean square error (RRMSE) and mean relative error (MRE) were used to evaluate the fitness between observed and predicted PNA values. The following sensitivity analysis method, Noise Equivalent (NE) model was calculated to assess the sensitivity of the optimal spectral parameters for detecting changes in PNA across different growth stages. The results indicated that PNA in winter oilseed rape increased with N fertilization rates, and changes in canopy hyperspectral reflectance under varied N rates were all highly significant and consistent in patterns across different growth stages and years. Compared with single reflectance measures, the simple reflectance ratio was more satisfied with its sound correlations with the PNA. PNA were highly and linearly correlated with spectral reflectance ratio of 1 259 nm and 492 nm (R1259/R492) with the highest R2 values (0.850). Upon the analysis the linear and nonlinear (logarithm, parabola, power and exponential) regression models for PNA estimation, and the selected optimal spectral parameters, e.g., ratio vegetation index-5 (RVI-5), normalized difference spectral index (NDSI), red-edge position with linear interpolation method (REIP), triangle vegetation index (TVI), first derivative of the reflectance spectra at the given wavelength at 742 nm (FD742) and the sum of first derivative with the red-edge region (SDR) had a good correlation with PNA (averaged R2 and standard error (SE) was 0.69 and 42.70, respectively), and the best spectral parameter was FD742 (R2 =0.79, SE=35.66). Based on the results of precision analysis, the model in which the optimum reflectance ratios (R1259/R492) and first derivative of the reflectance spectra at the given wavelength at 742 nm (FD742) as variables would be perfect of estimating PNA of winter oilseed rape using hyperspectral techniques. The two spectral parameters had the relative lower Noise Equivalent (NE) values and would be not affected by growing stages. The model estimation accuracy was high, the R2 values were 0.98 and 0.98, respectively, the RRMSE values were 0.73 and 0.72, and the MRE values were 14.42 % and 10.31 %, respectively. The overall results indicate that the PNA of winter oilseed rape could be reliably estimated with the canopy hyperspectral methods established in this study.