Tropical soil pH and sorption complex prediction via portable X-ray fluorescence spectrometry

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorTeixeira, Anita Fernanda dos Santos-
Autor(es): dc.creatorPelegrino, Marcelo Henrique Procópio-
Autor(es): dc.creatorFaria, Wilson Missina-
Autor(es): dc.creatorSilva, Sérgio Henrique Godinho-
Autor(es): dc.creatorGonçalves, Mariana Gabriela Marcolino-
Autor(es): dc.creatorAcerbi Júnior, Fausto Weimar-
Autor(es): dc.creatorGomide, Lucas Rezende-
Autor(es): dc.creatorPádua Júnior, Alceu Linares-
Autor(es): dc.creatorSouza, Igor Alexandre de-
Autor(es): dc.creatorChakraborty, Somsubhra-
Autor(es): dc.creatorWeindorf, David C.-
Autor(es): dc.creatorGuilherme, Luiz Roberto Guimarães-
Autor(es): dc.creatorCuri, Nilton-
Data de aceite: dc.date.accessioned2026-02-09T12:36:34Z-
Data de disponibilização: dc.date.available2026-02-09T12:36:34Z-
Data de envio: dc.date.issued2020-08-26-
Data de envio: dc.date.issued2020-08-26-
Data de envio: dc.date.issued2020-03-
Fonte completa do material: dc.identifierhttps://repositorio.ufla.br/handle/1/42651-
Fonte completa do material: dc.identifierhttps://doi.org/10.1016/j.geoderma.2019.114132-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1164726-
Descrição: dc.descriptionPortable X-ray fluorescence (pXRF) spectrometry delivers results rapidly, at low-cost, and without generating chemical residues. This study aimed to predict soil pH, sum of bases (SB), base saturation percentage (BSP), cation exchange capacity (CEC), and Al saturation (Alsat) of 2017 contrasting Brazilian soil samples through the association of pXRF and three different algorithms [Cubist, Random forest (RF), and stepwise multiple linear regression (SMLR)]. Soil samples were collected from the surface (SURF) and subsurface (SUB) horizons in seven Brazilian states. The prediction models were generated for the SURF and SUB horizons separately and combined (SURF + SUB dataset). Overall, the best predictions were achieved via Cubist followed by RF. For the pH predictions, the model combining SURF and SUB horizons data presented better results. Satisfactory results were achieved for the predictions of SB (validation R2 = 0.86), BSP (validation R2 = 0.81) and Alsat (R2 = 0.76). Moreover, promising results were obtained for predicting pH (R2 = 0.63). Notably, CaO appeared as the most influential variable for soil property prediction models. Overall, pXRF showed great potential for predicting soil fertility properties for diversified tropical soils with low cost, rapidity, and without chemical waste generation.-
Idioma: dc.languageen-
Publicador: dc.publisherElsevier-
Direitos: dc.rightsrestrictAccess-
???dc.source???: dc.sourceGeoderma-
Palavras-chave: dc.subjectPortable X-ray fluorescence-
Palavras-chave: dc.subjectBase saturation-
Palavras-chave: dc.subjectCation exchange capacity-
Palavras-chave: dc.subjectRandom forest-
Palavras-chave: dc.subjectCubist-
Palavras-chave: dc.subjectSoil fertility-
Palavras-chave: dc.subjectEspectrômetros de fluorescência de raios X-
Palavras-chave: dc.subjectSaturação de base-
Palavras-chave: dc.subjectCapacidade de troca de cátions-
Palavras-chave: dc.subjectFloresta aleatória-
Palavras-chave: dc.subjectFertilidade do solo-
Título: dc.titleTropical soil pH and sorption complex prediction via portable X-ray fluorescence spectrometry-
Tipo de arquivo: dc.typeArtigo-
Aparece nas coleções:Repositório Institucional da Universidade Federal de Lavras (RIUFLA)

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