| The objective of this research was to investigate the effects of a long-term experiment on soil spectral properties and to develop prediction models of these properties (soil organic carbon (SOC), N, pH, Hh, P2O5, K2O, Ca, Mg, K, and Na content) from texturally homogeneous samples (loamy sand). To this aim, chemometric techniques, such as partial least square (PLS) regression and support vector machine (SVM) classification, were used. Our results show that visible and near infrared spectroscopy (VIS-NIRS) is suitable for the prediction of properties of texturally homogeneous samples. The effects of fertilizer applications were sufficient to modify the soil chemical composition to a range suitable for using VIS-NIRS for calibration and modeling purposes.... |
