Sensing soil organic matter is crucial for precision farming and environment friendly agriculture. Near infra-red(NIR) was utilized to measure the soil organic matter. Multivariate calibration methods, including stepwise multiple linear regression(MLR), principal components recession(PCR) and partial least squares regression(PLS), were applied to soil spectral reflectance data to predict the organic matter content. The effect of soil particle size and water content was studied. The range of soil organic matter contents was from 0.5 to 11%. Near infrared (NIR) region from 700 to 2,500nm was applied. For uniform soil particle size, result had good correlation (R$^$2/ = 0.984, standard error of prediction= 0.596). The effect of soil particle size could be eliminated with 1st order derivative of the NIR signal. However. moist soil had a little lower correlation. R$^$2/ was 0.95 and standard error of prediction was 0.94% using the PLS method. The results showed the possibility of soil organic matter measurement using NIR reflectance on the field.