Distribution and spatial autocorrelation of physical-water attributes of an Oxisol

Job  Teixeira de Oliveira; Rubens Alves de Oliveira; Gloria  Milena Rojas Plazas; Sinomar Moreira Andrade; Fernando  França da Cunha

doi:10.18011/bioeng.2023.v17.1109

Autores

Job Teixeira de Oliveira Professor UFMS, Department Agronomy, Universidade Federal de Mato Grosso do Sul (UFMS), CPCS, Chapadão do Sul-MS, Brazil. https://orcid.org/0000-0001-9046-0382
Rubens Alves de Oliveira Professor UFV, Departament Agricultural Engineering UFV, Universidade Federal de Viçosa (UFV), Viçosa-MG, Brazil. https://orcid.org/0000-0003-2557-592X
Gloria Milena Rojas Plazas Professor UFV, Departament Agricultural Engineering UFV, Universidade Federal de Viçosa (UFV), Viçosa-MG, Brazil. https://orcid.org/0000-0001-7260-6712
Sinomar Moreira Andrade Pos graduate UFV, Departament Agricultural Engineering UFV, Universidade Federal de Viçosa (UFV), Viçosa-MG, Brazil. https://orcid.org/0000-0001-6099-632X
Fernando França da Cunha Ms, Department Agronomy, Universidade Federal de Mato Grosso do Sul (UFMS), CPCS, Chapadão do Sul-MS, Brazil. https://orcid.org/0000-0002-1671-1021

DOI:

https://doi.org/10.18011/bioeng.2023.v17.1109

Palavras-chave:

Geostatistics, Moran bivariate, Precision agriculture

Resumo

Spatial autocorrelation, which in this work was calculated using Moran's bivariate analysis, can be defined as the coincidence of similar values in nearby locations, or the absence of randomness of a variable due to its spatial distribution. Therefore, the objective of this study is to analyze the distribution and spatial autocorrelation of physical attributes of an Oxisol. The experiment was carried out in the irrigation and drainage area of the Universidade Federal de Viçosa, in Viçosa, Minas Gerais, Brazil. The soil in which the experimental meshes were installed was classified as a sandy clayey Oxisol. The attributes were determined: soil moisture on a dry basis, % (DB), soil moisture on a wet basis, % (WB), volumetric soil moisture, % (VS), particle density, g cm-1 (PD), sampled at different depths and within a grid of 90 georeferenced points. For spatial autocorrelation, the global Moran and local Moran indexes (LISA) were used as statistical tools. Bivariate analysis revealed that soil volumetric moisture is closely related to wet and dry basis moisture. It was also found that the surface particle density is related to the deeper layers of the soil, thus reinforcing that the solid fraction of a soil sample, without considering porosity, tends to remain constant. This happens because the predominant mineral constituents in soils are quartz, feldspars, and colloidal aluminum silicates, whose particle densities are around 2.65 g cm^-3.

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