Szczegóły publikacji
Opis bibliograficzny
Estimation of total nitrogen and organic carbon contents in mine soils with NIR reflectance spectroscopy and various chemometric methods / Anna PUDEŁKO, Marcin CHODAK // Geoderma ; ISSN 0016-7061. — 2020 — vol. 368 art. no. 114306, s. 1–7. — Bibliogr. s. 7, Abstr. — Publikacja dostępna online od: 2020-03-09
Autorzy (2)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 128456 |
|---|---|
| Data dodania do BaDAP | 2020-05-06 |
| DOI | 10.1016/j.geoderma.2020.114306 |
| Rok publikacji | 2020 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Czasopismo/seria | Geoderma |
Abstract
Rapid analytical methods are needed to measure organic carbon (OC) and total nitrogen (N-t) contents in reclaimed mine soils. Near infrared spectroscopy (NIRS) with appropriate chemometric techniques could be used for OC and N-t monitoring in the mine soils. The aim of this study was to compare efficiency of NIR-based models developed using various chemometric approaches to predict OC and N-t contents in afforested mine soils. The studied approaches were: partial least square regression (PLSR), principal component regression (PCR) and artificial neural networks based on the entire spectral data (ANN), the principal components (PCA-ANN) and the latent variables (PLS-ANN) calculated from the spectral data. The samples (n = 90) of uppermost mine soil horizons (0-20 cm) were taken from the reclaimed dump of Belchatow lignite mine (Poland) and measured for the OC content by dry combustion and for the N-t content by Kjehldahl method. The samples were air-dried, finely ground and their NIR spectra (1000 nm-2500 nm) were recorded. The models were developed using 60 samples while the remaining 30 samples were used for independent validation. All the tested chemometric approaches (except the ANN model for OC) yielded excellent models useful for quantitative estimations. The PLSR models were promising at the calibration stage (values of ratio of inter-quartile distance to standard error of prediction (RPIQ(c)) were 7.00 and 4.22 for N-t and OC, respectively) however in the validation they performed less successfully (RPIQ(v) = 3.08 for N-t and RPIQ(v) = 2.75). The accuracy of ANN models based on the entire spectra was similar to PLSR or PCR models. However, the ANN based on reduced spectral data (PCA-ANN and PLS-ANN) performed distinctly better. The most accurate predictive models for the OC and N-t contents were obtained using PCA-ANN approach (RPIQ(v) = 3.64 and 2.90, for N-t and OC, respectively). The results indicate that NIRS coupled with ANN based on the reduced spectral data can be successfully applied to measure the OC and N-t contents in mine soils.
