Application of FT-NIR spectroscopy and NIR hyperspectral imaging to predict nitrogen and organic carbon contents in mine soils

The aim of this study was to compare the performance of FT-NIR spectroscopy and near-infrared hyper-spectral imaging (NIR-HSI) in predicting the C-org and N-t contents in mine soils. The mine soil samples were measured for the C-org and N-t contents and their NIR spectra were recorded (1000-2500 nm). Predictive models were developed using 126 samples with partial least square regression (PLSR) or artificial neural networks (ANN) and validated with 58 independent samples. The NIR-HSI based models had distinctly higher accuracy of C-org content prediction than those based on FT-NIR data in both PLSR and ANN methods, as indicated by lower of standard errors of prediction. The prediction accuracy for the N-t content was similar for the two spectral methods and both chemometric approaches tested. The study showed that despite lower spectral resolution the NIR-HSI spectra retained all the information needed for accurate prediction of C-org and N-t contents. (C) 2020 Elsevier Ltd. All rights reserved.