Abstract

Soil physical attributes are affected by several events. The ability to identify the variation of those attributes can be used to decide the best crop management. Although it is known that smaller grids are more representative, predicting the least number of points while maintaining accuracy is a tool that might reflect a gain in yield and time. The aims of this study were to evaluate the spatial physical variability and to define the minimum sampling density in a tropical Typic Haplustults soil using a scaled semivariogram in a central pivot area with pinto bean (Phaseolus vulgaris L.) after the eighth bean harvest in Cristalina, Goias State. Soil samples were collected at a regular grid of 10-m intervals, totaling 180 points, and at depths of 0.00–0.10 m, 0.10–0.20 m, and 0.20–0.30 m to determine total sand content (TS), silt (SIL), clay (CL), water-dispersed clay (WDC), mean weight diameter of soil aggregates (MWD), soil penetration resistance (PR), soil macroporosity (Ma), soil microporosity (Mi), and soil bulk density (BD). The results demonstrated that management promoted superficial soil compaction with increasing BD and Mi and decreasing Ma and TP. The scaled semivariogram demonstrated similarity between attributes in the three studied soil layers, evidencing strong spatial dependency. The sample density showed a strong influence of WDC in the irrigated soil properties. Adoption of a scaled semivariogram is a strategy that can be used to determine a minimum number of points that represents the spatial variability of soil physical attributes and to assist the best management in irrigated soils.

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