Characterization of Physical-Chemical and Structural Soil Attributes in the Semiarid Region of the Rio Grande do Norte State, Brazil

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.

Physical, chemical and structural attributes of soil in agroecosystems in the Brazilian Semiarid region

“…It is noteworthy that all studied soils had a pH close to neutral (6.0 to 7.3) and eutrophic characteristic (V ≥ 50%), including the Latossolo (Profiles 1 and 4), being a particularity of the region to find this class with high base saturation (LOPES et al, 2019;SILVA et al, 2018). This occurs due to the climate pattern of the semi-arid region, with low rainfall, which minimizes the leaching process of exchangeable bases, keeping fertile soils, in addition to the infl uence of the source material with basic or limestone rocks (SANTOS et al, 2018).…”

“…The highlighted variables (F1) demonstrate the interrelations between inorganic fractions, especially clay, with the chemical and structural attributes of the Note: SD -Soil density; PT -Total porosity; Macro -Macroporosity; Micro -Microporosity; FCfi eld capacity; PWP -Permanent withering point; AW -available water; GF -Degree of fl occulation; MPD -weighted average diameter; pH -hydrogen potential; EC -electrical conductivity; TOC -total organic carbon; P -Phosphorus; K + -Potassium; Na + -Sodium; Ca 2+ -Calcium; Mg 2+ -Magnesium; SB -Sum of bases; V -base saturation soil (LOPES et al, 2019). Since texture is an intrinsic property of soil, it is difficult to change and directly influences structure, fertility and water retention (KLEIN; KLEIN, 2015).…”

“…Soil is a fi nite natural resource, that is, it is not renewable over the human time scale (decades) and is subject to degradation by natural and anthropogenic factors (LAL, 2015). Thus, it is of fundamental importance to develop proper activity planning and maintenance of its productive capacity (LOPES et al, 2019).…”

“…Studies on the physical, chemical, and structural attributes of the soil and their interrelationship with agroecosystems are important, especially in family farming areas where these growers depend essentially on the soil resource. Thus, it is necessary to evaluate these attributes to characterize the environments regarding their potentialities and/or limitations, seeking subsidies to direct proper planning of agricultural activities and conservation of the soil productive capacity (LOPES et al, 2019;MARINHO et al, 2016).…”

“…In this context, multivariate statistical analysis emerges as an effi cient auxiliary tool, enabling the analysis of attributes and their relationships. It is a statistical model that allows, besides identifying the difference between the studied environments, to observe which attributes contribute most to the distinction between the studied agroecosystems (HAIR JR et al, 2009;LOPES et al, 2019).…”