Variabilidade espacial dos atributos físicos do solo e dos componentes de produtividade do milho sob sistema de plantio direto

Abstract

Understanding the distribution and spatial variability of soil attributes allows landowners and farm managers to identify specific management zones with the help of isoline maps, which allows the optimization of the production process due to the efficient application of herbicides, pesticides and fertilizer at variable rates, yield increases and reduced environmental damage. The objective of this paper was to determine the spatial variation of soil physical attributes and corn yield components and to observe the correlation between soil physical attributes and corn yield. The study was conducted at the Santa Luzia Agricultural Farm, located in the municipality of São Raimundo das Mangabeiras, MA, in an experimental area of approximately 0.8 ha, managed for approximately 14 years under no-tillage system. For the evaluation of the physical parameters of the soil and yield of the maize crop a previously established 10 x 10 m sample mesh was used, in which the sample points corresponded to the crossing between the rows and columns of the mesh, totaling 100 sample points. For each sampling point the georeferencing, collection of undisturbed soil samples, soil resistance penetration and corn harvesting were performed. The data were submitted to classic statistical analysis and geostatistical analysis to obtain experimental semivariograms. The 10 x 10 m mesh was efficient to identify the spatial dependence of corn productivity variables and soil physical attributes. Most of the studied variables presented predominantly strong spatial dependence and were better adjusted to the Gaussian, exponential and spherical models. The maps from ordinary kriging were efficient in determining the spatial variability of soil physical attributes and corn yield and delimiting specific management zones that can assist in soil and crop management in order to improve crop yields maize, reducing costs for the producer and minimizing environmental impacts.