The use of diffuse reflectance mid-infrared spectroscopy for the prediction of the concentration of chemical elements estimated by X-ray fluorescence in agricultural and grazing European soils

Abstract

Editorial handling by R. Fuge a b s t r a c tThe aim of this study was to develop partial least-squares (PLS) regression models using diffuse reflectance Fourier transform mid-infrared (MIR) spectroscopy for the prediction of the concentration of elements in soil determined by X-ray fluorescence (XRF). A total of 4130 soils from the GEMAS European soil sampling program (geochemical mapping of agricultural soils and grazing land of Europe) were used for the development of models to predict concentrations of Al, As, Ba, Ca, Ce, Co, Cr, Cs, Cu, Fe, Ga, Hf, K, La, Mg, Mn, Na, Nb, Ni, P, Pb, Rb, Sc, Si, Sr, Th, Ti, V, Y, Zn and Zr in soil using MIR spectroscopy. The results were compared with those obtained where MIR models were developed with the same soils but using the concentration of elements extracted with aqua regia (AR).The PLS models were cross-validated against the experimental log-transformed XRF values of all the elements. The calibration models were derived from a set of 1000 randomly selected calibration samples. The rest of the samples (3130) were used as an independent validation set. According to the residual predictive deviation (RPD), predictions were classified as follows: ''Good quality

Synergistic Use of Vis‐NIR, MIR, and XRF Spectroscopy for the Determination of Soil Geochemistry

“…Similar to other soil spectral studies (Kemper and Sommer, 2002;Wu et al, 2007Wu et al, , 2005, prediction of some elements appeared to be possible through association with Al and Fe, and not with chemical parameters SOC and pH (Table 4). Many of the elements in the current study that were correlated (R > 0.70) with Al and to a lesser degree Fe, are reflective of relationships reported by Soriano-Disla et al (2013a, 2013b in European agricultural soils. The elements showing high inter-correlation are mostly minor elements; Ce, Ga, Ge, Sc, Th, Ti, V, and W (Table 4).…”

“…† introduced into the soil library. Overall, this model averaging approach resulted in a much greater success in soil geochemical characterization compared with other studies of soil geochemical characterization (Reeves and Smith, 2009;Soriano Disla et al, 2013a, 2013b using the traditional approach of selecting the best-performing model from a single spectral method.…”

Mid-Infrared and Total X-Ray Fluorescence Spectroscopy Complementarity for Assessment of Soil Properties

“…Soriano-Disla et al (2013) obtained good results for the prediction of total concentrations of Ca, Mg, Al, Fe, Ga, Si, and Na in soil as determined by X-ray fluorescence (XRF) in their development of PLSR models using DRIFT-MIR spectroscopy. The successful predictions of these elements are reported to have occurred because of major MIR-sensitive soil components such as clays, Al and Fe-oxides/oxyhydroxides and organic matter (Soriano-Disla et al, 2013). Soriano-Disla et al (2014) noted that the MIR spec- tral region does not have sufficient information to provide an accurate prediction of K in soils, especially for extractable K because the extractable fraction of K is influenced by factors that are not infrared active (e.g., the concentration of K + in soil solution).…”

NMR metabolomics for soil analysis provide complementary, orthogonal data to MIR and traditional soil chemistry approaches – a land use study

“…[9,10,[14][15][16] The analysis of MIR data for the soils in this work reflects this. PCA of the MIR data revealed that the spectra clustered according to location.…”