Determination of total soil organic C and hot water-extractable C from VIS-NIR soil reflectance with partial least squares regression and spectral feature selection techniques

European Journal of Soil Science

Volumn 62, Issue 4, 2011, Pages 598-606

  Vohland, M ^a   Emmerling, C ^a  

^a UNIVERSITY OF TRIER   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY ASSESSMENT; CALIBRATION; DATA SET; DETECTION METHOD; NEAR INFRARED; ORGANIC CARBON; REFLECTANCE; REGRESSION ANALYSIS; SOIL CLASSIFICATION; SOIL ORGANIC MATTER; SPECTRAL ANALYSIS; VISIBLE SPECTRUM;

EID: 79960439123     PISSN: 13510754     EISSN: 13652389     Source Type: Journal    
DOI: 10.1111/j.1365-2389.2011.01369.x     Document Type: Article

References (30)

1. Araújo, M.C.U., Saldanha, T.C.B., Galvão, R.K.H., Yoneyama, T., Chame, H.C. & Visani, V. 2001. The successive projections algorithm for variable selection in spectroscopic multicomponent analysis. Chemometrics & Intelligent Laboratory Systems, 57, 65-73.
2. Baumgardner, M.F., Kristof, S.J., Johansen, C.J. & Zachary, A.L. 1970. Effect of organic matter on the multispectral properties of soils. Proceedings of Indian Academy of Science, 79, 413-422.
3. Ben-Dor, E. & Banin, A. 1995a. Near-infrared analysis as a rapid method to simultaneously evaluate several soil properties. Soil Science Society of America Journal, 59, 364-372.
4. Ben-Dor, E. & Banin, A. 1995b. Near infrared analysis (NIR) as a method to simultaneously evaluate spectral featureless constituents in soils. Soil Science, 159, 259-270.
5. Ben-Dor, E., Irons, J.A. & Epema, A. 1999. Soil spectroscopy. In: Manual of Remote Sensing (ed. A. Rencz), pp. 111-188. John Wiley & Sons, Inc., New York.
6. Ben-Dor, E., Taylor, R.G., Hill, J., Demattê, J.A.M., Whiting, M.L., Chabrillat, S. et al. 2008. Imaging spectrometry for soil applications. In: Advances in Agronomy, Volume 97 (ed. D.L. Sparks), pp. 321-392. Elsevier, Amsterdam.
7. Bowers, S.A. & Hanks, R.J. 1965. Reflection of radiant energy from soils. Soil Science, 100, 130-138.
8. Cécillon, L., Barthès, B.G., Gomez, C., Ertlen, D., Genot, V., Hedde, M., et al. 2009. Assessment and monitoring of soil quality using near-infrared reflectance spectroscopy (NIRS). European Journal of Soil Science, 60, 770-784.
9. Chodak, M., Khanna, P. & Beese, F. 2003. Hot water extractable C and N in relation to microbiological properties of soils under beech forests. Biology & Fertility of Soils, 39, 123-130.
10. Confalonieri, M., Fornasier, F., Ursino, A., Boccardi, F., Pintus, B. & Odoardi, M. 2001. The potential of near infrared reflectance spectroscopy as a tool for the chemical characterisation of agricultural soils. Journal of Near Infrared Spectroscopy, 9, 123-141.
11. Coûteaux, M.M., Berg, B. & Rovira, P. 2003. Near infrared reflectance spectroscopy for determination of organic matter fractions including microbial biomass in coniferous forest soils. Soil Biology & Biochemistry, 35, 1587-1600.
12. Dalal, R.C. & Henry, R.J. 1986. Simultaneous determination of moisture, organic carbon, and total nitrogen by near infrared reflectance spectrophotometry. Soil Science Society of America Journal, 50, 120-123.
13. Hartge, K.H. & Horn, R. 1989. Die physikalische Untersuchung von Böden. Enke, Stuttgart.
14. Henderson, T.L., Baumgardner, M.F., Franzmeier, D.P., Stott, D.E. & Coster, D.C. 1992. High dimensional reflectance analysis of soil organic matter. Soil Science Society of America Journal, 56, 865-872.
15. Landgraf, D., Böhm, C. & Makeschin, F. 2003. Dynamic of different C and N fractions in a cambisol under five year succession fallow in Saxony (Germany). Journal of Plant Nutrition & Soil Science, 166, 319-325.
16. Leardi, R. & González, A.L. 1998. Genetic algorithms applied to feature selection in PLS regression: how and when to use them. Chemometrics & Intelligent Laboratory Systems, 41, 195-207.
17. Malley, D.F., Martin, P.D. & Ben-Dor, E. 2004. Application in analysis of soils. In: Near-Infrared Spectroscopy in Agriculture, Agronomy, Volume 44 (eds C.A. Roberts, J. Workman Jr & B. Reeves III), pp. 729-783. American Society of Agronomy, Madison, WI.
18. McCarty, G.W., Reeves, J.B. III, Reeves, V.B., Follett, R.F. & Kimble, J.M. 2002. Mid-infrared and near-infrared diffuse reflectance spectroscopy for soil carbon measurement. Soil Science Society of America Journal, 66, 640-646.
19. Mouazen, A.M., Maleki, M.R., De Baerdemaeker, J. & Ramon, H. 2007. On-line measurement of some selected soil properties using a VIS-NIR sensor. Soil & Tillage Research, 93, 13-27.
20. Reeves, J.B. III 2009. Near- versus mid-infrared diffuse reflectance spectroscopy for soil analysis emphasizing carbon and laboratory versus on-site analysis: where are we and what needs to be done? Geoderma, 158, 3-14.
21. Rinnan, R. & Rinnan, A. 2007. Application of near infrared reflectance (NIR) and fluorescence spectroscopy to analysis of microbiological and chemical properties of arctic soil. Soil Biology & Biochemistry, 39, 1664-1673.
22. Rinnan, Å., Van den Berg, F. & Engelsen, S.B. 2009. Review of the most common pre-processing techniques for near-infrared spectra. Trends in Analytical Chemistry, 28, 1201-1222.
23. Schulz, E. & Körschens, M. 1998. Characterization of the decomposable part of soil organic matter (SOM) and transformation processes by hot water extraction. Eurasian Soil Science, 31, 809-813.
24. Vasques, G.M., Grunwald, S. & Sickman, J.O. 2008. Comparison of multivariate methods for inferential modeling of soil carbon using visible/near-infrared spectra. Geoderma, 146, 14-25.
25. Vasques, G.M., Grunwald, S. & Sickman, J.O. 2009. Modeling of soil carbon fractions using visible-near-infrared spectroscopy. Soil Science Society of America Journal, 73, 176-184.
26. Viscarra Rossel, R.A. & Lark, R.M. 2009. Improved analysis and modelling of soil diffuse reflectance spectra using wavelets. European Journal of Soil Science, 60, 453-464.
27. Viscarra Rossel, R.A., Walvoort, D.J.J., McBratney, A.B., Janik, L.J. & Skjemstad, J.O. 2006. Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties. Geoderma, 131, 59-75.
28. Wold, S., Sjöström, M. & Eriksson, L. 2001. PLS-regression: a basic tool of chemometrics. Chemometrics & Intelligent Laboratory Systems, 58, 109-130.
29. Ye, S., Wang, D. & Min, S. 2008. Successive projections algorithm combined with uninformative variable elimination for spectral variable selection. Chemometrics & Intelligent Laboratory Systems, 91, 194-199.
30. Yoshido, H., Leardi, R., Funatsu, K. & Varmuza, K. 2001. Feature selection by genetic algorithms for mass spectral classifiers. Analytica Chimica Acta, 446, 485-494.