NEAR INFRARED ANALYSIS (NIRA) AS A METHOD TO SIMULTANEOUSLY EVALUATE SPECTRAL FEATURELESS CONSTITUENTS IN SOILS

Abstract

High resolution diffuse reflectance spectra (3113 spectral points) in the near infrared region (NIR) were recorded for 91 soil samples from Israel. Ten soil constituents (total iron [Fe2O3], aluminum [Al2O2], potassium [K2O], and phosphorous [P2O2], loss on ignition residual [LOI], free iron oxides [Fed], aggregate size (1.5–2mm) fraction [F1], average aggregate size (mm) [AVGR], and sodium adsorption percentages [CNaP]) were measured by routine methods employed in soil laboratories. An empirical model to predict each property from its reflectance spectrum in the near infrared spectral region was developed by adapting the near infrared analysis (NIRA) technique. Several data manipulations were used in order to obtain optimum performance. The optimum performance of several soil constituents was found to be at 3113 spectral points (Al2O3, Fed, and K2O) and 310 spectral points (Fe2O3), whereas for others (SiO2, AVGR, and F1) even 25 spectral points provided sufficient performance. Strong support for the capability of NIRA was obtained by a careful examination of the possible correlation between spectrally active soil properties (clay content [CLAY], specific surface area [SSA], hygroscopic moisture [HIGF] and calcite [CaCO3]), which were studied elsewhere, and the featureless constituents studied here. A slight bias was found for the prediction of Al2O3 and Fed, and a greater bias was found for K2O, suggesting that further study regarding the prediction of these constituents is needed. It was concluded that NIRA is a very promising vehicle for rapid and nonrestrictive analysis of soil materials.