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Land Use and Its Impact on Phosphorus Adsorption Capacity in a Tropical Dryland Agricultural Frontier: Insights and Predictive Modeling

dc.contributor.authorde Souza, José Wilker G.
dc.contributor.authorda Luz, João H. S.
dc.contributor.authorSilva, Dayane M. R.
dc.contributor.authorSilva, Ricardo B.
dc.contributor.authorPaulino, Sivaldo S.
dc.contributor.authorda S. Marques, Isabelly C. [UNESP]
dc.contributor.authorde O. Galdino, Wesley
dc.contributor.authorde Sousa, Jadielson I.
dc.contributor.authorDo N. S. Barbosa, Luana
dc.contributor.authorMelo, Alan F.
dc.contributor.authorde Souza, Weslly G.
dc.contributor.authorda S. Lira, Viviane
dc.contributor.authordos Santos, Valdevan R.
dc.contributor.institutionFederal University of Alagoas
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.date.accessioned2025-04-29T20:08:24Z
dc.date.issued2025-01-01
dc.description.abstractLand use significantly impacts the physical-chemical properties of soil, particularly in tropical regions where the maximum phosphorus adsorption capacity (MPAC) plays a crucial role in agricultural sustainability. This study evaluates the influence of land uses (cropland, grassland, and forest) on MPAC in dryland soils of Sergipe, Alagoas, and Bahia (SEALBA) agricultural frontier in Northeast Brazil. Soil samples from nine sites were analyzed for their physical-chemical characteristics (potential of hydrogen (pH), available phosphorus (P), remaining P, soil organic matter (SOM), calcium and magnesium content, exchangeable aluminum, potential acidity and texture) in the 0–20 cm soil depth. MPAC was determined using two isotherm models, and three predictive models were applied. The results revealed that cropland soils exhibit the highest MPAC, contrary to expectations of lower values due to legacy P from P inputs. However, MPAC varied slightly across sites, indicating specific dependencies on soil physical-chemical properties and suggesting that land use may have a more significant influence over the long term. Random forest and decision tree models identified SOM and available P as the most significant predictors of MPAC, yet with these routine soil fertility indicators alone, the maximum explanatory power (R2) was 75% with a precision (RMSE) of 77 mg kg−1 using the random forest model. Consequently, the conversion of forest to cropland can increase MPAC, and predicting MPAC can be a valuable tool for guiding land use and assisting in the formulation of more sustainable agricultural and environmental policies, particularly in dryland agricultural frontiers.en
dc.description.affiliationDepartment of Agricultural Sciences Federal University of Alagoas, Alagoas
dc.description.affiliationDepartment of Soil Science “Luiz de Queiroz” College of Agriculture University of Sao Paulo
dc.description.affiliationDepartment of Plant Production College of Agricultural Sciences Paulista State University (UNESP), SP
dc.description.affiliationUnespDepartment of Plant Production College of Agricultural Sciences Paulista State University (UNESP), SP
dc.identifierhttp://dx.doi.org/10.1080/00103624.2025.2452995
dc.identifier.citationCommunications in Soil Science and Plant Analysis.
dc.identifier.doi10.1080/00103624.2025.2452995
dc.identifier.issn1532-2416
dc.identifier.issn0010-3624
dc.identifier.scopus2-s2.0-85214920796
dc.identifier.urihttps://hdl.handle.net/11449/307095
dc.language.isoeng
dc.relation.ispartofCommunications in Soil Science and Plant Analysis
dc.sourceScopus
dc.subjectAdsorption isotherm
dc.subjectphosphate sorption
dc.subjectrandom forest
dc.subjectSEALBA
dc.titleLand Use and Its Impact on Phosphorus Adsorption Capacity in a Tropical Dryland Agricultural Frontier: Insights and Predictive Modelingen
dc.typeArtigopt
dspace.entity.typePublication

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