Eurasian Journal of Soil Science

Volume 12, Issue 3, Jun 2023, Pages 244-256
DOI: 10.18393/ejss.1275149
Stable URL: http://ejss.fess.org/10.18393/ejss.1275149
Copyright © 2023 The authors and Federation of Eurasian Soil Science Societies



Development of Hungarian spectral library: Prediction of soil properties and applications

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MohammedZein,M., Csorba,A., Rotich,B., Justin,P., Melenya,C., Andrei,Y., Micheli,E., 2023. Development of Hungarian spectral library: Prediction of soil properties and applications. Eurasian J Soil Sci 12(3):244-256. DOI : 10.18393/ejss.1275149
MohammedZein,M.,Csorba,A.Rotich,B.Justin,P.Melenya,C.Andrei,Y.,& Micheli,E. Development of Hungarian spectral library: Prediction of soil properties and applications Eurasian Journal of Soil Science, 12(3):244-256. DOI : 10.18393/ejss.1275149
MohammedZein,M.,Csorba,A.Rotich,B.Justin,P.Melenya,C.Andrei,Y., and ,Micheli,E."Development of Hungarian spectral library: Prediction of soil properties and applications" Eurasian Journal of Soil Science, 12.3 (2023):244-256. DOI : 10.18393/ejss.1275149
MohammedZein,M.,Csorba,A.Rotich,B.Justin,P.Melenya,C.Andrei,Y., and ,Micheli,E. "Development of Hungarian spectral library: Prediction of soil properties and applications" Eurasian Journal of Soil Science,12(Jun 2023):244-256 DOI : 10.18393/ejss.1275149
M,MohammedZein.A,Csorba.B,Rotich.P,Justin.C,Melenya.Y,Andrei.E,Micheli "Development of Hungarian spectral library: Prediction of soil properties and applications" Eurasian J. Soil Sci, vol.12, no.3, pp.244-256 (Jun 2023), DOI : 10.18393/ejss.1275149
MohammedZein,Mohammed Ahmed ;Csorba,Adam ;Rotich,Brian ;Justin,Phenson Nsima ;Melenya,Caleb ;Andrei,Yuri ;Micheli,Erika Development of Hungarian spectral library: Prediction of soil properties and applications. Eurasian Journal of Soil Science, (2023),12.3:244-256. DOI : 10.18393/ejss.1275149

How to cite

MohammedZein, M., Csorba, A., Rotich, B., Justin, P., Melenya, C., Andrei, Y., Micheli, E., 2023. Development of Hungarian spectral library: Prediction of soil properties and applications. Eurasian J. Soil Sci. 12(3): 244-256. DOI : 10.18393/ejss.1275149

Author information

Mohammed Ahmed MohammedZein , Institute of Environmental Sciences, Department of Soil Science, Hungarian University of Agriculture and Life Sciences, Hungary & Land and Water Research Center, Agricultural Research Corporation, Sudan
Adam Csorba , Institute of Environmental Sciences, Department of Soil Science, Hungarian University of Agriculture and Life Sciences, Hungary
Brian Rotich , Institute of Environmental Sciences, Department of Soil Science, Hungarian University of Agriculture and Life Sciences, Hungary
Phenson Nsima Justin , Institute of Environmental Sciences, Department of Soil Science, Hungarian University of Agriculture and Life Sciences, Hungary
Caleb Melenya , Institute of Environmental Sciences, Department of Soil Science, Hungarian University of Agriculture and Life Sciences, Hungary
Yuri Andrei , Institute of Environmental Sciences, Department of Soil Science, Hungarian University of Agriculture and Life Sciences, Hungary
Erika Micheli , Institute of Environmental Sciences, Department of Soil Science, Hungarian University of Agriculture and Life Sciences, Hungary

Publication information

Article first published online : 01 Apr 2023
Manuscript Accepted : 24 Mar 2023
Manuscript Received: 26 Jan 2023
DOI: 10.18393/ejss.1275149
Stable URL: http://ejss.fesss.org/10.18393/ejss.1275149

Abstract

Updating soil information systems (SIS) requires advanced technologies to support the time and cost-effective and environment-friendly soil data. The use of mid- infrared (MIR) Spectroscopy as alternative to wet chemistry has been tested. The MIR spectral library is a useful technique for predicting soil attributes with high accuracy, efficiency, and low cost. The Hungarian MIR spectral library contained data on 2200 soil samples from 10 counties representing the first Soil Information and Mentoring System (SIMS) survey. Archived soil samples were prepared and scanned based on Diffuse Reflectance Infrared spectroscopy (DRIFT) technique and spectra data were saved in the fourier transform infrared (FTIR) spectrometer OPUS software. Preprocessed filtering methods, outlier detection methods and calibration sample selection methods were applied for spectral library. MIR calibration models were built for soil attributes using Partial Least Square Regression (PLSR) method. Coefficient determination (R2), The Root Mean Squared Error (RMSE) and Ratio of Performance to Deviation (RPD) were used to assess the goodness of calibration and validation models. MIR spectral library had the ability to significantly estimate soil properties such as SOC, CaCO3, sand, clay and silt through various scale models (national, county and soil type). The findings showed that our spectral library soil estimations are precise enough to provide information on national, county and soil type levels enabling a wide range of soil applications that demand huge amounts of data such as soil survey, precision agriculture and digital soil mapping.

Keywords

Fourier-transform infrared spectroscopy, mid-infrared spectroscopy, partial least square regression, soil information system.

Corresponding author

References

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Abstract

Updating soil information systems (SIS) requires advanced technologies to support the time and cost-effective and environment-friendly soil data. The use of mid- infrared (MIR) Spectroscopy as alternative to wet chemistry has been tested. The MIR spectral library is a useful technique for predicting soil attributes with high accuracy, efficiency, and low cost. The Hungarian MIR spectral library contained data on 2200 soil samples from 10 counties representing the first Soil Information and Mentoring System (SIMS) survey. Archived soil samples were prepared and scanned based on Diffuse Reflectance Infrared spectroscopy (DRIFT) technique and spectra data were saved in the fourier transform infrared (FTIR) spectrometer OPUS software. Preprocessed filtering methods, outlier detection methods and calibration sample selection methods were applied for spectral library. MIR calibration models were built for soil attributes using Partial Least Square Regression (PLSR) method. Coefficient determination (R2), The Root Mean Squared Error (RMSE) and Ratio of Performance to Deviation (RPD) were used to assess the goodness of calibration and validation models. MIR spectral library had the ability to significantly estimate soil properties such as SOC, CaCO3, sand, clay and silt through various scale models (national, county and soil type). The findings showed that our spectral library soil estimations are precise enough to provide information on national, county and soil type levels enabling a wide range of soil applications that demand huge amounts of data such as soil survey, precision agriculture and digital soil mapping.

Keywords: Fourier-transform infrared spectroscopy, mid-infrared spectroscopy, partial least square regression, soil information system.

References

Baumann, P., Helfenstein, A., Gubler, A., Keller, A., Meuli, R.G., Wächter, D., Lee, J., Viscarra Rossel, R., Six, J., 2021. Developing the Swiss mid-infrared soil spectral library for local estimation and monitoring. Soil 7(2): 525–546.

Bullock, P., Montanarella, L., 1987. Soil information : Uses and needs in Europe. European Soil Bureau Research Report No.9, pp. 397–417.

Burns, D.A., Ciurczak, E.W., 2007. Handbook of Near-Infrared Analysis. CRC Press, Boca Raton, 814p.

D’Acqui, L.P., Pucci, A., Janik, L.J., 2010. Soil properties prediction of western Mediterranean islands with similar climatic environments by means of mid-infrared diffuse reflectance spectroscopy. European Journal of Soil Science 61(6): 865–876.

Demattê, J.A.M., Dotto, A.C., Bedin, L.G., Sayão, V.M., Souza, A.B., 2019. Soil analytical quality control by traditional and spectroscopy techniques: Constructing the future of a hybrid laboratory for low environmental impact. Geoderma 337: 111–121.

Demattê, J.A.M., Dotto, A.C., Paiva, A.F.S., Sato, M.V., Dalmolin, R.S.D., de Araújo, M.S.B., da Silva, E.B., Nanni, M.R., ten Caten, A., Noronha, N.C., Lacerda, M.P.C., de Araújo Filho, J.C., Rizzo, R., Bellinaso, H., Francelino, M.R., Schaefer, C.E.G.R., Vicente, L.E., dos Santos, U.J., de Sá Barretto Sampaio, E.V., Menezes, R.S.C., de Souza, J.J.L.L., Abrahão, W.A.P., Coelho, P.M., Grego, C.R., Lani, J.L., Fernandes, A.R., Gonçalves, D.A.M., Silva, S.H.G., de Menezes, M.D., Curi, N.C., Couto, E.G., dos Anjos, L.H.C., Ceddia, M.B., Pinheiro, E.F.M., Grunwald, S.G., Vasques, G.M., Júnior, J.M., da Silva, A.J., de Vasconcelos Barreto, M.J., Nóbrega, G.N., da Silva, M.Z., de Souza, S.F., Valladares, G.S., Viana, J.H.M., da Silva Terra, F., Horák-Terra, I., Fiorio, P.R., da Silva, R.C., Júnior, E.F.F., Lima, R.H.C., Alba, J.M.F., de Souza Junior, V.S., Brefin, M.L.M.S., Ruivo, M.L.P., Ferreira, T.O., Brait, M.A., Caetano, N.R., Bringhenti, I., Mendes, W.S., Safanelli, J.L., Guimarães, C.C.B., Poppiel, R.R., Souza, A.B., Quesada, C.A., do Couto, H.T.Z., 2019. The Brazilian Soil Spectral Library (BSSL): A general view, application and challenges. Geoderma 354: 113793.

Deng, F., Minasny, B., Knadel, M., McBratney, A., Heckrath, G., Greve, M.H., 2013. Using Vis-NIR spectroscopy for monitoring temporal changes in soil organic carbon. Soil Science 178(8): 389–399.

Dickens, A.A.. 2014. Standard operating procedures. Method for analysing samples for spectral characteristics in mid IR range using alpha. Code: METH07V02. World Agroforestry Centre, Nairobi, Kenya.

Grunwald, S., Thompson, J.A., Boettinger, J.L., 2011. Digital soil mapping and modeling at continental scales: Finding solutions for global issues. Soil Science Society of America Journal 75(4): 1201–1213.

Guerrero, C., Wetterlind, J., Stenberg, B., Mouazen, A.M., Gabarrón-Galeote, M.A., Ruiz-Sinoga, J.D., Zornoza, R., Viscarra Rossel, R.A., 2016. Do we really need large spectral libraries for local scale SOC assessment with NIR spectroscopy? Soil and Tillage Research 155: 501–509.

Janik, L.J., Merry, R.H., Forrester, S.T., Lanyon, D.M., Rawson, A., 2007. Rapid prediction of soil water retention using mid infrared spectroscopy. Soil Science Society of America Journal 71(2): 507–514.

Janik, L.J., Merry, R.H., Skjemstad, J.O., 1998. Can mid infrared diffuse reflectance analysis replace soil extractions? Australian Journal of Experimental Agriculture 38(7): 681–696.

Janik, L.J., Skjemstand, J.O., Raven, M.D., 1995. Characterization and analysis of soils using mid-infrared partial least squares. I. correlations with xrf-determined major element composition. Australian Journal of Soil Research 33(4): 621–636.

Johnson, J.M., Vandamme, E., Senthilkumar, K., Sila, A., Shepherd, K.D., Saito, K., 2019. Near-infrared, mid-infrared or combined diffuse reflectance spectroscopy for assessing soil fertility in rice fields in sub-Saharan Africa. Geoderma 354: 113840.

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