Abstract
The aim of this paper was to quantify and evaluate the spatial distribution of soil chemical properties in different grid sampling sizes using descriptive statistics and geostatistics. The study was carried out in Bom Sucesso City, Paraná State, Brazil. Using GPS, a 50 x 50 m grid sampling size was set, comprising four samples per hectare. In each grid point positioned on the field, soil samples at a depth of 00 to 0.20m were extracted, resulting in 203 sampling points in a 51.15 ha area. Calcium, magnesium and potassium quantity were determined. Grid sampling size, with lower number of samples per area, were established from the first grid, removing randomly, soil samples, resulting in: 70.8 x 70.8 m (2 samples/ha), 100 x 100 m (1 sample/ha), 141 4 x 141.4 m (1 sample/2 ha), 173.3 x 173.3 m (1 sample/3 ha) and 200 x 200 m (1 sample/4 ha) grid sampling sizes. Each soil chemical properties in each grid sampling size were subjected to descriptive statistical and geostatistical analysis. An experimental semivariogram was developed to understand the spatial dependence structure. The attributes calcium, magnesium and potassium showed spatial correlation in almost all grids sampling, except for the 200 m grid sampling for calcium and magnesium. Key words: Spatial distribution of attributes, spatial dependence, descriptive statistics, geostatistics.
Highlights
IntroductionFurther studies regarding the spatial variability of physical, chemical and biological soil attributes are necessary since the management of agricultural practices depends on this variability, with direct impact on agricultural yield and on the environment
In each grid point positioned on the field, soil samples at a depth of 00 to 0.20m were extracted, resulting in 203 sampling points in a 51.15 ha area
The attributes calcium, magnesium and potassium showed spatial correlation in almost all grids sampling, except for the 200 m grid sampling for calcium and magnesium
Summary
Further studies regarding the spatial variability of physical, chemical and biological soil attributes are necessary since the management of agricultural practices depends on this variability, with direct impact on agricultural yield and on the environment. It seems to be the most elaborate way to understand the production of variables related to the soil-plant system. Knowledge of these variations is essential to the survey and classification of areas with productive potential, assessment of their fertility, development of appropriate systems of sampling, experimental design and definitions of appropriate management practices and recovery of agricultural areas. The number of samples required to represent the variability of the field has been a subject of discussion since at least, 1920 (Linsley and Bauer, 1929)
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