The application of near infrared (NIR) spectroscopy for the quantitative assessment of soil organic matter fraction in forests
Zastosowanie spektroskopii w bliskiej podczerwieni (NIR) do ilościowej oceny materii organicznej w glebach leśnych
Sylwan 166 (10):635-646, 2022
Available online: 2023-03-03
Open Access (CC-BY)
forest soils • near infrared spectroscopy • soil analysis • soil fraction • soil organic matter

In this study we investigated if near infrared (NIR) spectroscopy can be effectively used to predict content of various fraction (LF – light fraction and MAF – mineral associated fractions) of soil organic matter, also in the context of their spatial distribution. Additionally, we used NIR spectroscopy to evaluate basic properties of forest soils. We analyzed 256 soil samples from the topsoil of plots in central Poland. Using laboratory techniques, we divided the soil samples into two soil carbon fractions: the light fraction (LF) and mineral−associated fraction (MAF). A calibration model was developed using the spectra from 171 soil samples and their corresponding measured values. The regression model was validated using 85 independent soil samples. Using this model, we estimated the following forest soil properties: carbon concentration in light fraction (CLF), carbon concentration in mineral−associated fraction (CMAF), ratio of the CLF to the total carbon content of the soil sample (CLF/C), ratio of the CMAF to the total carbon content of the soil sample (CMAF/C), the total concentration of carbon (Ct) and nitrogen (Nt), C:N ratio (CN), pH, the concentration of exchangeable base cations (BC) and cation exchange capacity (CEC). The best calibration results were obtained for CLF, CLF/C and CMAF/C. The largest adjusted coefficients of determination for validation were obtained for Nt, CN, BC and CEC. Model developed forthe CLF was characterized by inaccurate value prediction. The paper shows also the relationship between the optimum number of soil sample spectra and the absolute and relative measurement error. Comparison of the measured and predicted values show that NIR spectroscopy has potential for determining soil parameters. The statistical assessment and spatial distribution analysis of the modelled CMAF demonstrated relatively good agreement with measured values. However, the model’s assessment of the CLF was less accurate. We conclude that NIR spectroscopy is most applicable for use in soil science to determine the parameters: Ct, Nt, C/N, pH, CEC, CMAF and CMAF/C.

Atkins, P.W., 2001. Chemia fizyczna. Warszawa: Wydawnictwo Naukowe PWN, 936 pp.
Ben-Dor, E., Banin, A., 1995. Near-infrared analysis as a rapid method to simultaneously evaluate several soil properties. Soil Science Society of America Journal, 59 (2): 364-372. DOI:
Buurman, P., van Lagen, B., Velthorst, E.J., 1996. Manual for Soil and Water Analysis. Leiden: Backhuys Publishers, 316 pp.
Chodak, M., Niklińska, M., Beese, F., 2007. Near-infrared spectroscopy for analysis of chemical and microbiological properties of forest soil organic horizons in a heavy-metal-polluted area. Biology and Fertility of Soils, 44 (1): 171-180. DOI:
Christensen, B.T., 2001. Physical fractionation of soil and structural and functional complexity in organic matter turnover. European Journal of Soil Science, 52 (3): 345-353. DOI:
Conyers, M.K., Davey, B.G., 1990. The variability of pH in acid soils of the southern highlands of New South Wales. Soil Science, 150 (4): 695-704.
Cozzolino, D., Morón, A., 2006. Potential of near-infrared reflectance spectroscopy and chemometrics to predict soil organic carbon fractions. Soil and Tillage Research, 85 (1-2): 78-85. DOI:
FAO, 2014. World reference base for soil resources. Rome: World Soil Resources Report 106.
Gil, W., 1995. Przestrzenne mikrozróżnicowanie gleby leśnej – jego charakter i związki z drzewostanem. [Spatial microdifferentiation of forest soil – its character and links with tree stand (in Polish)]. Sylwan, 139 (4): 33-39.
Islam, K., Singh, B., McBratney, A., 2003. Simultaneous estimation of several soil properties by ultra-violet, visible, and near-infrared reflectance spectroscopy. Australian Journal of Soil Research, 41 (6): 1101-1114. DOI:
Kania, M., Gruba, P., 2016. Estimation of selected properties of forest soils using near-infrared spectroscopy (NIR). Soil Science Annual, 67 (1): 32-36. DOI:
Kania, M., Gruba, P., Wiecheć, M., 2017. Zastosowanie techniki bliskiej podczerwieni do obliczania Siedliskowego Indeksu Glebowego. Sylwan, 161 (11): 935-939. DOI:
Krajewski, R., 1955. Szczegółowa mapa geologiczna Polski w skali 1:50 000. Warszawa: Wydawnictwo Geologiczne.
Krysicki, W., Bartos, J., Dyczka, W., Królikowska, K., Wasilewski, M., 1995. Rachunek prawdopodobieństwa i statystyka matematyczna w zadaniach. Część II. Statystyka matematyczna. Warszawa: Wydawnictwo Naukowe PWN, 331 pp.
Loveland, P., Webb, J., 2003. Is there a critical level of organic matter in the agricultural soils of temperate regions: A review. Soil and Tillage Research, 70 (1): 1-18. DOI:
Ludwig, B., Khanna, P.K., Bauhus, J., Hopmans, P., 2002. Near infrared spectroscopy of forest soils to determine chemical and biological properties related to soil sustainability. Forest Ecology and Management, 171 (1-2): 121-132. DOI:
Ng, W., Husnain, Anggria, L., Siregar, A.F., Hartatik, W., Sulaeman, Y., Jones, E., Minasny, B., 2020. Developing a soil spectral library using a low-cost NIR spectrometer for precision fertilization in Indonesia. Geoderma Regional, 22: e00319. DOI:
Pietrzykowski, M., Chodak, M., 2014. Near infrared spectroscopy – A tool for chemical properties and organic matter assessment of afforested mine soils. Ecological Engineering, 62: 115-122. DOI:
Seema, Ghosh, A.K., Das, B.S., Reddy, N., 2020. Application of VIS-NIR spectroscopy for estimation of soil organic carbon using different spectral preprocessing techniques and multivariate methods in the middle Indo-Gangetic plains of India. Geoderma Regional, 23: e00349. DOI:
Sohi, S.P., Mahieu, N., Arah, J.R.M., Powlson, D.S., Madari, B., Gaunt, J.L., 2001. A procedure for isolating soil organic matter fractions suitable for modeling. Soil Science Society of America Journal, 65 (4): 1121-1128. DOI:
Stenberg, B., Viscarra Rossel, R.A., Mouazen, A.M., Wetterlind, J., 2010. Visible and near infrared spectroscopy in soil science. Advances in Agronomy, 107 (C): 163-215. DOI:
Viscarra Rossel, R.A., McGlynn, R.N., McBratney, A.B., 2006. Determining the composition of mineral-organic mixes using UV-vis-NIR diffuse reflectance spectroscopy. Geoderma, 137 (1-2): 70-82. DOI: