Application of FT-NIR spectroscopy and NIR hyperspectral imaging to predict nitrogen and organic carbon contents in mine soils. (November 2020) - Pudełko, Anna; Chodak, Marcin; Roemer, Jakub; Uhl, Tadeusz
Highlights: NIR-HSI models predicted more accurately Corg contents than FT-NIR models. Accuracy of predicting Nt content using NIR-HSI and FT-NIR data was similar. The ANN models had better accuracy than PLSR models. Abstract: The aim of this study was to compare the performance of FT-NIR spectroscopy and near-infrared hyperspectral imaging (NIR-HSI) in predicting the Corg and Nt contents in mine soils. The mine soil samples were measured for the Corg and Nt 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 Corg 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 Nt 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 Corg and Nt contents.