Abstract: Effectively monitoring crop nitrogen nutritional level and soil nitrogen supply capability can provide an important basis for the rational application of nitrogen during fertilization. In this study, the method of vegetation index and partial least square regression (PLSR) were used to compare and analyze the relationship between the hyperspectral reflectance of wheat canopy and the concentration of nitrogen in leaf and soil based on data from three growing regions across two growing seasons. The correlation between canopy spectral reflectance and leaf nitrogen content was significantly negative in the visible bands. Moreover, a significantly positive correlation existed in near-infrared bands, while the correlation of canopy spectral reflectance and soil nitrogen content showed the right opposite results. The determination coefficients from the regression model of leaf nitrogen content based on spectral parameters of ND705 and GNDVI were 0.827 and 0.826. According to the parameter ND705 and GNDVI, the determination coefficient obtained by the regression model was 0.646. Compared with the vegetation index, the prediction accuracy of PLSR models for wheat leaf and soil nitrogen content on the spectral reflectance among 350-2500 nm was enhanced with the determination coefficients as 0.842 and 0.654. These results could provide certain theoretical basis and technical support for further study on diagnosing nitrogen nutrition of wheat and soil, and monitoring rational nitrogen fertilization.