Abstract

The study of the soil characterization and the relation of its attributes allows a systematic proposal of the local particularities, leading to adequate practices for maintenance and/or preservation of its productive capacity. In this sense, the aim of this study was to evaluate the influence of structural attributes in association with physical and chemical soil classes, using the multivariate statistical techniques to differentiate environments. The research was carried out in the Moacir Lucena Project, located in the municipality of Apodi, RN, Brazil. Three representative environments were chosen as follows: Profile 1 (P1)-Red-yellow Latosol-Area in recovery (1AR), P2-Haplic Cambisol-Lake Area, (2AL) and P3-Eutrophic Yellow Latosol-Cashew Tree Area (3AC). The soil samples were collected in the horizons of the studied areas. Ten (10) samples were collected per horizons in volumetric rings and in soil blocks (aggregate analysis), which resulted in triplicates in the laboratory. Structural, physical and chemical attributes were evaluated. The data were analyzed using multivariate statistical techniques, with correlation matrix, clustering analysis and factorial analysis performed by the extraction of the factors into principal components. The use of clustering analysis allowed the formation of four groups for soil classes and attributes; the inorganic fractions were determinant for environmental differentiation, where the sand was discriminant for the Red-yellow Latosol and the Eutrophic Yellow Latosol, and the clay and silt for the Haplic Cambisol. Higher similarity was observed in the transition horizons of the Latosols Class. The physical and structural attributes were determinant in the dissimilarity for the Haplic Cambisol, reflecting in physical restrictions to the plant growth. The factor analysis revealed that the variables particle density (Dp), Ca²⁺, Mg²⁺, sum of bases (SB) and cation exchange capacity (CEC) for factor 1, followed by pH, P, K⁺, total Sand, Clay and soil density (Ds) for factor 2 are important soil attributes to distinguish the studied environments.

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