Remaining phosphorus in soils developed from different parent materials in three topossequences, Pinheiral-RJ

• Autor(a) principal: Fontana, Ademir
• Data de Publicação: 2013
• Outros Autores: Pereira, Marcos Gervasio, Santos, Adailde Carmo dos, Bernini, Thiago Andrade, Anjos, Lúcia Helena Cunha dos, Fernández, Carlos Fernando Dorronsoro, Peinado, Francisco José Martins
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Semina. Ciências Agrárias (Online)
• Texto Completo: https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/11048
• topic: Phosphate adsorption; Surface and subsurface horizons; Soils attribute.; 5.01.01.03-0; Adsorção de fosfato; Horizontes superficiais e subsuperficiais; Atributos dos solos.; 5.01.01.03-0

This work aimed to evaluate the remaining phosphorus tenors and correlate with the chemical, physical and mineralogical attributes in soils horizons developed from different parent materials in three topossequences in the municipality of Pinheiral, RJ. Were described and collected samples of surface horizons (A) and subsurface (B+C) from 14 soils profiles under pasture in three toposequences (T1, T2 and T3), being T1 under basalt, T2 under muscovite-biotite-gneiss and T3 under gabbro. Chemical and physical routine analyses as well as Al and Fe by sulfuric acid attack and X-ray fluorescence, Fed (dithionite-citrate-bicarbonate) and Feo (ammonium oxalate), clay specific surface (SS), clay and oxide mineralogy and remaining phosphorus (Prem), were taken. Variations in the Prem tenors were observed, which related to the nature of parent material, landscape position and soils development degree, which can be analyzed by the chemical, physical and mineralogical variations. The Prem tenors followed the order T2 > T1 = T3 in A horizons and T1 > T3 and T2 ~ T1 e T3 in B+C horizons. Negative correlations between Prem tenors with Fe2O3 (X rays) > Fed > SS > Feo in the A horizon and with Fe2O3 (sulfuric acid) > Fe2O3 (X rays) > clay > Fed > Feo in the B+C horizons, were observed. The principal components and hierarchical clustering analysis contributed to the joint data evaluation, showing the related attributes and the similarity between soils.