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Spatial patterns of magnetic susceptibility optimized by anisotropic correction in different Alisols in southern Amazonas, Brazil

Authors :
Laércio Santos Silva
Fernando Gomes de Souza
Alan Ferreira Leite de Lima
Thalita Silva Martins
Wildson Benedito Mendes Brito
José Maurício da Cunha
Milton César Costa Campos
Flávio Pereira de Oliveira
Ivanildo Amorim de Oliveira
Federal University of Amazonas (UFAM)
Universidade Federal da Paraíba (UFPB)
Federal University of Roraima (UFRR)
Universidade Estadual Paulista (UNESP)
Universidade Estadual de Maringá (UEM)
Source :
Scopus, Repositório Institucional da UNESP, Universidade Estadual Paulista (UNESP), instacron:UNESP
Publication Year :
2022

Abstract

Made available in DSpace on 2022-04-29T08:32:31Z (GMT). No. of bitstreams: 0 Previous issue date: 2022-04-01 Changes in primary cover for agricultural crops in Amazonas region influence the phenomenon of spatial variability in soil properties. This phenomenon is still studied assuming that the spatial data is isotropic, but does not consider the anisotropic pattern of soil properties. Thus, the aim of this work was to characterize, identify and correct isotropic patterns of magnetic susceptibility (MS) measurements using anisotropic models that actually represent the spatial aspects of the data. Three cultivation areas and one under native forest, classified as Haplic Alisol, were georeferenced and sampled by a mesh system covering 192 samples per area. Texture, X-ray diffraction and frequency-dependent (χfd) and mass-specific (χlf and χhf) magnetic susceptibility analyzes were performed. Then, classical and geostatistical analyzes were applied to the data, assuming isotropy and anisotropy. All χ frequencies were shown to be spatially dependent, satisfying the isotropy hypothesis. Thereby, the application of anisotropic analysis was able to confirm the presence of all types of anisotropy in Alisols. Anisotropic correction provided an improvement in models that fit the directional trends within the areas, and provided a reduction in the nugget effect and an increase in the correlation ranges. Thus, the generated kriging maps improved the patches of zonal trends of greater or lesser χ that stand out at the level of sub-regions. These zones should, therefore, be used as indicators of variability, paying special attention during their management, especially in research related to the delimitation of specific management zones. Amazon Environment and Soil Research Group (GPSAA) Federal University of Amazonas (UFAM), Amazonas Amazon Environment and Soil Research Group (GPSAA) Center of Agricultural Sciences Federal University of Paraíba (CCA/UFPB), Paraíba Department of Agronomy Federal University of Roraima (UFRR), Roraima Soil Characterization for Specific Management Research Group (CSME) Faculty of Agrarian and Veterinary Sciences Paulista State University (FCAV/UNESP), São Paulo Department of Soils and Rural Engineering Agricultural Sciences Center Federal University of Paraíba (DSER/CCA/UFPB), Paraíba Federal Institute of Rondônia (IFRO), Rondônia Soil Characterization for Specific Management Research Group (CSME) Faculty of Agrarian and Veterinary Sciences Paulista State University (FCAV/UNESP), São Paulo

Details

Language :
English
Database :
OpenAIRE
Journal :
Scopus, Repositório Institucional da UNESP, Universidade Estadual Paulista (UNESP), instacron:UNESP
Accession number :
edsair.doi.dedup.....c8b3d138ae27ece046274870d631e08f