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Geostatistical and multivariate techniques have been widely used to identify and characterize the soil spatial variability, as well as to detect possible relationships between soil properties and management. Besides that, these techniques provide information regarding the spatial and temporal structural changes of soils to support better decision-making processes and management practices. Although the Zona da Mata region is a reference for sugarcane production in the northeast of Brazil, only a few studies have been carried out to clarify the effects of different management on soil physical attributes by using geostatistical and multivariate techniques. Thus, the objectives of this study were: (I) to characterize the spatial distribution of soils physical attributes under rainfed and irrigated sugarcane cultivations; (II) to identify the minimum sampling for the determination of soil physical attributes; (III) to detect the effects of the different management on soil physical attributes based on the principal component analysis (PCA). The study was carried out in the agricultural area of the Carpina Sugarcane Experimental Station of the Federal Rural University of Pernambuco, 7º51’13”S, 35º14’10”W, characterized by a Typic Hapludult with sandy clay loam soil texture. The investigated plot, cultivated with sugarcane, included a rainfed and an irrigated treatment in which a sprinkler system was installed according to a 12x12m grid. The interval between consecutive watering was fixed in two days, whereas irrigation depth was calculated to replace crop evapotranspiration (ETc) and accounting for the effective precipitation of the period. Daily ETc was estimated based on crop coefficient and reference evapotranspiration (ETo) indirectly obtained through a class A evaporation pan. In both treatments, the soil spatial variability was determined according to a 56x32m grid, on 32 soil samples collected in the 0.0-0.1m soil layer, spaced 7x8m, and georeferenced with a global position system. The soil was physically characterized according to the following attributes: bulk density (BD), soil penetration resistance (SPR), macroporosity (Macro), mesoporosity (Meso), microporosity (Micro), total porosity (TP), saturated hydraulic conductivity (Ksat), gravimetric soil water content (SWCg), geometric mean diameter (GMD) and mean weight diameter (MWD). The results of the descriptive statistics showed that among the studied attributes, Ksat, SPR, and Macro presented higher CV values, equal to 63 and 69%, 35 and 40%, and 32 and 44%, under rainfed and irrigated conditions, respectively. The minimum sampling, adequate to characterize the different soil attributes, resulted in general smaller in the rainfed area, characterized by higher homogeneity. Thus, the GMD, SWCg (both with 2 points ha-1), and SPR (with 6 points ha-1) were identified as the soil physical attributes requiring the lowest sample density; on the other hand, MWD and Ksat, with 14 and 15 points ha-1, respectively, required the highest number of samples. Pearson’s correlation analysis evidenced that soil BD was the most influential physical attribute in the studied areas, with a significant and inverse effect in most of the investigated attributes. The geostatistical approach associated with the multivariate PCA provided to understand the relationships between the spatial distribution patterns associated with irrigated and rainfed management and soil physical properties.

Soil management, although intended to create favorable structural conditions for crop growth and development, without prior assessment of potential and limitations, has been one of the reasons for the degradation of natural resources. The effects on soil degradation and respective structural quality are generally evaluated by some physical soil attributes such as bulk density (BD), total porosity (TP) and soil penetration resistance (PR). The PR is recognized as a physical parameter that supports the identification of areas with different stages of compaction and thus can be used to define appropriate management for soil remediation. Besides, this parameter depends on intrinsic soil factors (texture, structure, and mineralogy) and soil water content (SWC). Therefore, PR increases with BD and decreases with SWC (gravimetric or volumetric). Thus, it is possible to establish the critical limit of PR (PRCL) associated with the value of SWC that limits the growth of plant roots. PRCL varies according to soil type and plant species, but 2.0 MPa is the value scientifically accepted as the critical value to limit the root growth. Thus, the paper aimed to evaluate the spatial and temporal variability of PR in a field cultivated with sugarcane, under the conventional tillage system. The research was carried out in the Carpina Sugarcane Experimental Station, Pernambuco, Brazil. A grid of 70 x 70 m was delineated at intervals of 10 m and in each point soil samples were collected in the layers 0 - 0.30 m and 0.30 - 0.60 m depth. Three samplings were done to determine gravimetric soil water content; the first after six months of subsoiling (Time 6) before harrowing and planting, the second after 12 months of subsoiling (Time 12, six months after harrowing and planting) and the last after 18 months of subsoiling, before harvesting (Time 18). In each sampling time, in situ PR tests were carried out with the Solo Track equipment (Falker® - Model PLG 5300) and the simultaneous values of gravimetric soil water content were determined and associated with the PR data. The results showed that soil water content had a weak degree of spatial dependence, indicating the need to increase the number of samples. On the other hand, the PR values showed that the subsoiling did not promote a positive effect on the soil physical quality, with values above the PRCL for root development in Time 6 (2.42 MPa), even if after one year the sugarcane root system acted positively, by reducing PR in Time 18 (1.04 MPa) below the critical value.

Spatial mapping of soil chemical attributes is essential for sampling efficiency and agricultural planning management, ensuring a regional development and sustainability of the unique characteristics of archaeological black earths (ABEs). Thus, this study was developed aiming at assessing the spatial variability and sampling density of chemical attributes in soils of ABEs under pasture in southern Amazonas, Brazil. A sampling grid of 56 × 80 m with regular spacings of 8 m was installed in the experimental area and samples were taken from the crossing points at depths of 0.0–0.05, 0.05–0.10, and 0.10–0.20 m, totaling 264 georeferenced points. The chemical attributes pH in water, organic carbon, Ca, Mg, K, P, Al, and potential acidity were determined in these samples, while CEC, SB, V, t, T, and m were calculated. The attributes present a spatial dependence varying from strong to moderate, being Al3+ the only chemical attribute that does not present a spatial dependence structure in the assessed depths. Scaled semivariograms satisfactorily reproduce the spatial behavior of attributes in the same pattern of individual semivariograms, allowing their use to estimate the variability of soil attributes. Sampling density is higher at a depth of 0.0–0.05 m, requiring 2 and 1 point ha−1 at depths of 0.05–0.10 and 0.10–0.20 m, respectively, to represent the spatial pattern of chemical attributes.