Corn stover, the aboveground non-grain fractions of corn plant, is an important feedstock for biobased industries. Determination of lignin and ash contents of corn stover is important for improving the conversion processes. The current wet chemistry methods for biomass characterization are time, resource and labor-intensive. The main objective of this study was to evaluate near infrared (NIR) spectroscopy method for rapid determination of lignin and ash contents of corn stover. 160 corn stover samples were air-dried, milled, and sifted through screen with mesh widths of 1 mm. The ground samples were scanned with NIR spectrometer. Acid-soluble lignin, acid-insoluble lignin and ash contents of same samples were measured through the well-established wet chemistry method. Multivariate analysis was used for correlating NIR spectral data with wet chemistry measurements. The developed NIR models predicted acid-soluble lignin, acid-insoluble lignin and ash contents of corn stover with coefficients of determination (R2) of 0.87, 0.64 and 0.89, respectively. The accuracy of models was comparable to that of previously established models on predicting lignin and ash contents of similar crops. The prediction performances of the models could be further improved by increasing the number of samples from different years and different regions for NIR model development and calibration. It was concluded that lignin and ash contents of corn stover can be rapidly characterized using NIR technique. Development of NIR technique in biobased industries can provide significant savings in time, labor and cost, compared to traditional wet chemistry method.