Abstract: Photosynthesis of ear-leaf directly affects yield of maize in the late period, it is of great significance for evaluating photosynthesis quickly and accurately by analyzing the relationship between hyperspectral remote sensing data and photosynthetic related parameters. In this research, four different N levels (N0: 0 kg/hm², N1: 170 kg/hm², N2: 340 kg/hm², N3: 500 kg/hm²) were used to analyze the change trends of photosynthetic parameters, chlorophyll fluorescence parameters, photosynthetic pigments and spectral reflectance of maize ear-leaf, and to discuss the relationship between photosynthetic fluorescence parameters and reflectance data. The results showed that Pn, Tr, Fv/Fm, ΦPSⅡ, P, Chl, Cars, Chl/Cars increased with increasing N level, and there were significant differences compared with N0 treatment (P<0.05), while Gs and NPQ had no difference among all treatments (P>0.05). With a rise of N treatment rate, spectral reflectance decreased in visible wavelength with increasing N level, opposite trends were found in near-infrared region. In addition, the red edge position moved to red wavelength with increasing N level. According to the correlation analysis of hyperspectral reflectance, first derivative spectrum, vegetation index and Photosynthetic Fluorescence Parameters, the optimal-hyperspectral variable of Pn, Tr, Fv/Fm, ΦPSII, P, NPQ, Chl, Cars and Chl/Cars was Dλ₆₉₉, Dλ₇₀₁, Dλ₇₀₃, Dλ₇₀₂, Dλ₇₀₁, R₇₆₄, Dλ₆₉₉, Dλ₆₉₉ and Dλ₇₀₀, respectively. And the corresponding correlation coefficient was 0.81, -0.73, -0.54, -0.58, -0.61, -0.49, -0.996, -0.997 and -0.877 (P<0.01). The optimal hyperspectral variable for Gs was Dλ₅₇₅ (P<0.05). Therefore, it was possible to assessing photosynthetic fluorescence parameters using hyperspectral remote sensing data, and it would be of great significance for analyzing yield of maize in the late period of the growing cycle.