Determination of organic carbon and nitrogen in particulate organic matter and particle size fractions of Brookston clay loam soil using infrared spectroscopy

European Journal of Soil Science (Impact Factor: 2.39). 04/2012; 63(2):177-188. DOI: 10.1111/j.1365-2389.2011.01421.x

ABSTRACT The objective of this study was to determine whether models developed from infrared spectroscopy could be used to estimate organic carbon (C) content, total nitrogen (N) content and the C:N ratio in the particulate organic matter (POM) and particle size fraction samples of Brookston clay loam. The POM model was developed with 165 samples, and the particle size fraction models were developed using 221 samples. Soil organic C and total N contents in the POM and particle size fractions (sand, 200053 mu m; silt, 532 mu m; clay, <2 mu m) were determined by using dry combustion techniques. The bulk soil samples were scanned from 4000 to 400 cm-1 for mid-infrared (MIR) spectra and from 8000 to 4000 cm-1 for near-infrared (NIR) spectra. Partial least squares regression (PLSR) analysis and the leave-one-out' cross-validation procedure were used for the model calibration and validation. Organic C and N content and C:N ratio in the POM were well predicted with both MIR- and NIR-PLSR models ( = 0.840.92; = 0.780.87). The predictions of organic C content in soil particle size fractions were also very good for the model calibration ( = 0.840.94 for MIR and = 0.860.92 for NIR) and model validation ( = 0.790.94 for MIR and = 0.840.91 for NIR). The prediction of MIR- and NIR-PLSR models for the N content and the C:N ratio in the sand and clay fractions was also satisfactory ( = 0.730.88; = 0.670.85). However, the predictions for the N content and C:N ratio in the silt fraction were poor ( = 0.230.55; = 0.200.40). The results indicate that both MIR and NIR methods can be used as alternative methods for estimating organic C and total N in the POM and particle size fractions of soil samples. However, the NIR model is better for estimating organic C and N in POM and sand fractions than the MIR model, whereas the MIR model is superior to the NIR model for estimating organic C in silt and clay fractions and N in clay fractions.

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