Data fusion modelling of visible-near-infrared and mid-infrared spectra Ghent University
Spectroscopy has emerged as a solution to estimate key soil attributes in precision agriculture (PA) during recent decades. Chemometrics and machine-learning methods are used in order to extract useful information out of the spectra. In this paper, the performance of visible-near-infrared (Vis-NIR) and mid-infrared (MIR) spectrophotometers for the prediction of pH, organic carbon (OC), phosphorous (P), potassium (K), magnesium (Mg), calcium ...