| Abstract: | Near-infrared reflectance spectroscopy (NIRS) has the potential to be a reliable method for accurately quantifying soil organic carbon (SOC). The objective of this study was to evaluate NIRS as a method for predicting SOC. Partial least squares (PLS) regression was used to predict SOC from soil reflectance values or the first derivative of the reflectance values. Two model validation techniques were evaluated: One was a full cross-validation and in the other 30 percent of the samples were removed from the calibration data set and then tested using the calibrated model. Significant relationships were observed for predicted SOC when compared to laboratory-measured SOC for all models evaluated, regardless of validation technique. The prediction models using the first derivative of the reflectance values outperformed prediction models using the reflectance values alone. In conclusion, NIRS can be used as a quick and accurate method for measuring SOC. |
