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

The GEMAS Project Team

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Abstract

The 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", Ca (2.9), Mg (2.5), Al (2.3), Fe (2.2), Ga (2.2), Si (2.1), Na (2.0); " Indicator quality", V (1.9), Ni (1.9), Sc (1.9), K (1.8), Ti (1.8), Rb (1.8), Zn (1.7), Co (1.7), Zr (1.6), Cr (1.6), Sr (1.6), Y (1.6), Nb (1.6), Ba (1.5), Mn (1.5), As (1.5), Ce (1.5); " Poor quality", Cs (1.4), Th (1.4), P (1.4), Cu (1.4), Pb (1.3), La (1.2), Hf (1.1).Good agreement was observed between the RPD values obtained for the elements analysed in this study and those from the AR study. Despite the different elemental concentrations determined by the XRF method compared to the AR method, MIR spectroscopy was still capable of predicting elemental concentrations.

Original languageEnglish
Pages (from-to)135-143
Number of pages9
JournalApplied Geochemistry
Volume29
DOIs
Publication statusPublished - 1 Feb 2013

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chemical element
X-ray fluorescence
infrared spectroscopy
Chemical elements
Infrared spectroscopy
reflectance
grazing
Fluorescence
Soils
X rays
prediction
soil
calibration
Calibration
agricultural soil
Fourier transform
Fourier transform infrared spectroscopy
Sampling
Infrared radiation
sampling

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@article{73a848e81773472093902837b202f78b,
title = "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 = "The 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{"}, Ca (2.9), Mg (2.5), Al (2.3), Fe (2.2), Ga (2.2), Si (2.1), Na (2.0); {"} Indicator quality{"}, V (1.9), Ni (1.9), Sc (1.9), K (1.8), Ti (1.8), Rb (1.8), Zn (1.7), Co (1.7), Zr (1.6), Cr (1.6), Sr (1.6), Y (1.6), Nb (1.6), Ba (1.5), Mn (1.5), As (1.5), Ce (1.5); {"} Poor quality{"}, Cs (1.4), Th (1.4), P (1.4), Cu (1.4), Pb (1.3), La (1.2), Hf (1.1).Good agreement was observed between the RPD values obtained for the elements analysed in this study and those from the AR study. Despite the different elemental concentrations determined by the XRF method compared to the AR method, MIR spectroscopy was still capable of predicting elemental concentrations.",
keywords = "soil geochemistry, mid-infrared spectroscopy",
author = "{The GEMAS Project Team} and Soriano-Disla, {J. M.} and L. Janik and McLaughlin, {M. J.} and S. Forrester and J. Kirby and C. Reimann and S. Albanese and M. Andersson and A. Arnoldussen and R. Baritz and Batista, {M. J.} and A. Bel-Lan and M. Birke and D. Cicchella and A. Demetriades and E. Dinelli and {De Vivo}, B. and {De Vos}, W. and R. Dohrmann and M. Duris and A. Dusza-Dobek and Eggen, {O. A.} and M. Eklund and V. Ernstsen and P. Filzmoser and Finne, {T. E.} and D. Flight and M. Fuchs and U. Fugedi and A. Gilucis and M. Gosar and V. Gregorauskiene and A. Gulan and J. Halamid and E. Haslinger and P. Hayoz and G. Hobiger and R. Hoffmann and J. Hoogewerff and H. Hrvatovic and S. Husnjak and Johnson, {C. C.} and G. Jordan and J. Kivisilla and V. Klos and F. Krone and P. Kwecko and L. Kuti and A. Ladenberger and A. Lima and J. Locutura and P. Lucivjansky and D. Mackovych and Malyuk, {B. I.} and R. Maquil and Meuli, {R. G.} and N. Miosic and G. Mol and P. N{\'e}grel and P. O'Connor and K. Oorts and Ottesen, {R. T.} and A. Pasieczna and V. Petersell and S. Pfleiderer and M. Poňavicč and C. Prazeres and U. Rauch and I. Salpeteur and A. Schedl and A. Scheib and I. Schoeters and P. Sefcik and E. Sellersj{\"o} and F. Skopljak and I. Slaninka and A. Šorša and R. Srvkota and T. Stafilov and T. Tarvainen and V. Trendavilov and P. Valera and V. Verougstraete and D. Vidojevid and Zissimos, {A. M.} and Z. Zomeni",
year = "2013",
month = "2",
day = "1",
doi = "10.1016/j.apgeochem.2012.11.005",
language = "English",
volume = "29",
pages = "135--143",
journal = "Applied Geochemistry",
issn = "0883-2927",
publisher = "Elsevier Limited",

}

TY - JOUR

T1 - 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

AU - The GEMAS Project Team

AU - Soriano-Disla, J. M.

AU - Janik, L.

AU - McLaughlin, M. J.

AU - Forrester, S.

AU - Kirby, J.

AU - Reimann, C.

AU - Albanese, S.

AU - Andersson, M.

AU - Arnoldussen, A.

AU - Baritz, R.

AU - Batista, M. J.

AU - Bel-Lan, A.

AU - Birke, M.

AU - Cicchella, D.

AU - Demetriades, A.

AU - Dinelli, E.

AU - De Vivo, B.

AU - De Vos, W.

AU - Dohrmann, R.

AU - Duris, M.

AU - Dusza-Dobek, A.

AU - Eggen, O. A.

AU - Eklund, M.

AU - Ernstsen, V.

AU - Filzmoser, P.

AU - Finne, T. E.

AU - Flight, D.

AU - Fuchs, M.

AU - Fugedi, U.

AU - Gilucis, A.

AU - Gosar, M.

AU - Gregorauskiene, V.

AU - Gulan, A.

AU - Halamid, J.

AU - Haslinger, E.

AU - Hayoz, P.

AU - Hobiger, G.

AU - Hoffmann, R.

AU - Hoogewerff, J.

AU - Hrvatovic, H.

AU - Husnjak, S.

AU - Johnson, C. C.

AU - Jordan, G.

AU - Kivisilla, J.

AU - Klos, V.

AU - Krone, F.

AU - Kwecko, P.

AU - Kuti, L.

AU - Ladenberger, A.

AU - Lima, A.

AU - Locutura, J.

AU - Lucivjansky, P.

AU - Mackovych, D.

AU - Malyuk, B. I.

AU - Maquil, R.

AU - Meuli, R. G.

AU - Miosic, N.

AU - Mol, G.

AU - Négrel, P.

AU - O'Connor, P.

AU - Oorts, K.

AU - Ottesen, R. T.

AU - Pasieczna, A.

AU - Petersell, V.

AU - Pfleiderer, S.

AU - Poňavicč, M.

AU - Prazeres, C.

AU - Rauch, U.

AU - Salpeteur, I.

AU - Schedl, A.

AU - Scheib, A.

AU - Schoeters, I.

AU - Sefcik, P.

AU - Sellersjö, E.

AU - Skopljak, F.

AU - Slaninka, I.

AU - Šorša, A.

AU - Srvkota, R.

AU - Stafilov, T.

AU - Tarvainen, T.

AU - Trendavilov, V.

AU - Valera, P.

AU - Verougstraete, V.

AU - Vidojevid, D.

AU - Zissimos, A. M.

AU - Zomeni, Z.

PY - 2013/2/1

Y1 - 2013/2/1

N2 - The 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", Ca (2.9), Mg (2.5), Al (2.3), Fe (2.2), Ga (2.2), Si (2.1), Na (2.0); " Indicator quality", V (1.9), Ni (1.9), Sc (1.9), K (1.8), Ti (1.8), Rb (1.8), Zn (1.7), Co (1.7), Zr (1.6), Cr (1.6), Sr (1.6), Y (1.6), Nb (1.6), Ba (1.5), Mn (1.5), As (1.5), Ce (1.5); " Poor quality", Cs (1.4), Th (1.4), P (1.4), Cu (1.4), Pb (1.3), La (1.2), Hf (1.1).Good agreement was observed between the RPD values obtained for the elements analysed in this study and those from the AR study. Despite the different elemental concentrations determined by the XRF method compared to the AR method, MIR spectroscopy was still capable of predicting elemental concentrations.

AB - The 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", Ca (2.9), Mg (2.5), Al (2.3), Fe (2.2), Ga (2.2), Si (2.1), Na (2.0); " Indicator quality", V (1.9), Ni (1.9), Sc (1.9), K (1.8), Ti (1.8), Rb (1.8), Zn (1.7), Co (1.7), Zr (1.6), Cr (1.6), Sr (1.6), Y (1.6), Nb (1.6), Ba (1.5), Mn (1.5), As (1.5), Ce (1.5); " Poor quality", Cs (1.4), Th (1.4), P (1.4), Cu (1.4), Pb (1.3), La (1.2), Hf (1.1).Good agreement was observed between the RPD values obtained for the elements analysed in this study and those from the AR study. Despite the different elemental concentrations determined by the XRF method compared to the AR method, MIR spectroscopy was still capable of predicting elemental concentrations.

KW - soil geochemistry

KW - mid-infrared spectroscopy

UR - http://www.scopus.com/inward/record.url?scp=84873099399&partnerID=8YFLogxK

U2 - 10.1016/j.apgeochem.2012.11.005

DO - 10.1016/j.apgeochem.2012.11.005

M3 - Article

VL - 29

SP - 135

EP - 143

JO - Applied Geochemistry

JF - Applied Geochemistry

SN - 0883-2927

ER -