As one of the most important components of soil nutrient, it is necessary to obtain the soil total nitrogen（STN）content in precision agriculture. It is a feasible method to predict soil total nitrogen content based on NIRS. However, the effect of soil moisture content (SMC) on the prediction of STN is very serious. In the present research, the effect of SMC was discussed from qualitative analysis and quantitative analysis by the Fourier spectrum analyzer MATRIX_I. Firstly, sixty soil samples with different STN and SMC were scanned by the MATRIX_I. It was found that the reflectance of soil samples in near infrared region decreased with the increase in SMC. Subsequently, Moisture absorbance index (MAI) was proposed by the diffuse of absorbance at the wavelengths of 1 450 and 1 940 nm to classify soil properties and then correction factor was present. Finally, the STN forecasting model with BP NN method was established by the revised absorbance data at the six wavelengths of 940, 1 050, 1 100, 1 200, 1 300 and 1 550 nm. The model was evaluated by correlation coefficient of RC, correlation coefficient of RV, root mean square error of calibration (RMSEC), root mean square error of validation (RMSEP) and residual prediction deviation (RPD). Compared with the model obtained from original spectral data, both the accuracy and the stability were improved. The new model was with RC of 0.86, RV of 0.81, RMSEC of 0.06, RMSEP of 0.05, and RPD of 2.75. With the first derivative of the revised absorbance, the RPD became 2.90. The experiments indicated that the method could eliminate the effect of SMC on the prediction of STN efficiently.