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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Vydané v:	Geoderma Ročník 385; s. 114851
Hlavní autori:	Javadi, S. Hamed, Munnaf, Muhammad Abdul, Mouazen, Abdul M.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.03.2021
Predmet:	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
On-line prístup:	Získať plný text
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