Fusion of Vis-NIR and XRF spectra for estimation of key soil attributes

•Fusion of Vis-NIR and XRF spectra in soil analysis is examined.•Spectra of 253 soil samples of 9 fields were used to evaluate the proposed methods.•Concatenation of Vis-NIR and XRF spectra may improve the soil prediction performance.•CNN with PCs of Vis-NIR and XRF spectra as input improves predict...

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Veröffentlicht in:	Geoderma Jg. 385; S. 114851
Hauptverfasser:	Javadi, S. Hamed, Munnaf, Muhammad Abdul, Mouazen, Abdul M.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.03.2021
Schlagworte:	calcium Chemometrics Convolutional neural network (CNN) Local weighted regression (LWR) magnesium neural networks organic carbon phosphorus precision agriculture Precision agriculture (PA) prediction principal component analysis sodium Soil analysis soil fertility soil properties Spectra fusion (SF) spectrometers Visible-near-infrared (Vis-NIR) X-ray fluorescence (XRF) Spectra fusion (SF) Visible-near-infrared (Vis-NIR) Soil analysis X-ray fluorescence (XRF) Precision agriculture (PA) Convolutional neural network (CNN) Chemometrics Local weighted regression (LWR)
ISSN:	0016-7061, 1872-6259
Online-Zugang:	Volltext
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