Abstract: To explore fast analysis method on nutrients of rice bran meal by near infrared spectroscopy,the near infrared spectra of 261 rice bran samples was collected. The spectra was performed with 20 different preprocessing methods,such as standard normal variate,detrend and multiplicative scatter correction. The near infared spectroscopy quantitative models of rice bran meal nutrients in 1000~1799 nm were respectively established by partial least square,principal component analysis combined with artificial neural network and partial least square combined with artificial neural network with the data measured by chemical method. The results showed that the models obtained by partial least square combined with artificial neural network were the best and its prediction accuracy was the highest. The correlation coefficients of the models were 0.9593,0.9168 and 0.9626 for moisture,ash content and crude protein,respectively.