Partial least squares regression(PLSR) was employed to build predicting model of the content of soil carbon with on-the-go near-infrared reflectance spectroscopy(NIRS) measurements.The model based on band ratio or normalized difference of NIRS data can improve the prediction precision than the model with the original NIRS data.The reasons might be that the process of band arithmetic combination could reduce the risk of overfitting and it made the model include more useful components and information.The results showed that predicted models of soil carbon based on field NIRS measurements could be created by PLSR and the predicted accuracy might be improved by processing of NIRS with ratio or normalized difference. Therefore, it is feasible to estimate soil carbon in field by on-the-go NIRS measurements.