Portable XRF and Vis-NIR spectrometry for predicting chemical properties of forest soils in the Amazon: Insights into sensor data dimensionality reduction

Portable XRF and Vis-NIR spectrometry for predicting chemical properties of forest soils in the Amazon: Insights into sensor data dimensionality reduction

Proximal sensor data integrated with machine learning algorithms have been successful in assessing soil chemical parameters. The accuracy of these sensors for assessing soil parameters in tropical forest soils is still limited. This research employed portable X-ray fluorescence spectrometry (pXRF) a...

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Bibliographic Details
Main Authors: Quésia Sá Pavão, Paula Godinho Ribeiro, Gutierre Pereira Maciel, Sérgio Henrique Godinho Silva, Suzana Romeiro Araújo, Antonio Rodrigues Fernandes, José Alexandre Melo Demattê, Pedro Walfir Martins e Souza Filho, Silvio Junio Ramos
Format: Article
Language:English
Published: Elsevier 2025-12-01
Series:Soil Advances
Subjects:
Machine learning
Proximal sensors
Random forest
Online Access:http://www.sciencedirect.com/science/article/pii/S2950289625000314
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http://www.sciencedirect.com/science/article/pii/S2950289625000314

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