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Apple nitrogen status is a key indicator for evaluating quality of apple fruits. In order to estimate total nitrogen content of apple leaves (LNC), a way was proposed to monitor LNC which extracted spectral characteristics parameters from hyperspectral reflectance in the visible and near infrared regions. Hyperspectral monitoring of LNC was realized by using empirical regression analysis. Results showed that the correlation between spectral parameters and leaf nitrogen content was good in whole growth period, the best spectral parameters were Kge and S△ABC, respectively, the correlation coefficient was 0.85, the correlation between spectral parameters and leaf nitrogen content was bad, and a lot of spectral parameters were highly uncorrelated. Modeling results showed that the best model in the slope of the spectral characteristic curve was Kge of Fuji apple, the determination coefficient was 0.76, the root mean square error was 0.28, the relative error was zero, the best model in spectral characteristic curve area was S△ABC and S△BCD of gala apple, the determination coefficient was all 0.76, the root mean square error was all 0.30, the relative error was all 0.01%and zero;the best model in area ratio vegetation index was S△CDE /S△BCD and S△CDE /S△BCD of Fuji apple and S△DEF/S△ABC of Gala apple, the determination coefficient was 0.74, the root mean square error was all 0.35, the relative error was 0.01% and 0.02%, the best model in area normalized vegetation index was (S△CDE-S△BCD)/(S△CDE+S△BCD) in the whole growth period and (S△CDE-S△ABC/(S△CDE+S△ABC) of Gala apple, the determination coefficient was all 0.73, the root mean square error was 0.36 and 0.31, and the relative error was zero and -0.01%. The best verification results was area ratio vegetation index S△CDE/S△ABC, the determination coefficient, the root mean square error and the relative error was 0.47, 0.34 and -3.78% in the whole growth period, respectively. The determination coefficient, the root mean square error and the relative error was 0.37, 0.34, 3.00% and 0.40, 0.38, 3.70% in Fuji and Gala apple varieties, respectively. The other spectral characteristic parameters were significantly correlated with the LNC except spectral characteristic area variable S△EFG and normalized area vegetation index (S△CDE-S△FGH)/(S△CDE+S△FGH), in which spectral characteristic curve slope Kge and Kgprv, spectral characteristic area S△ABC and S△BCD, area ratio vegetation index S△CDE/S△ABC, S△CDE/S△BCD and S△DEF/S△ABC,normalized area vegetation index (S△CDE-S△ABC)/(S△CDE+S△ABC), (S△CDE-S△BCD)/(S△CDE+S△BCD) and (S△DEF-S△ABC)/(S△DEF+S△ABC) can describe preferably dynamic changes of LNC and these characteristic parameters were feasible for prediction of LNC of apples. By the precision evaluation of estimation models, the algorithm model constructed by S△CDE/S△ABC, S△CDE/S△FGH and (S△CDE-S△ABC)/(S△CDE+S△ABC) was proved to be the best model for estimation of LNC of apples. The results showed that the characteristics of the hyperspectral curve can provide a new reference for monitoring nitrogen nutrition.