Sampling density to detect spatial dependence of potassium, calcium and magnesium in sandy soils

Abstract

The sampling grid density for georeferenced soil collection must be large enough to allow the identification of the spatial dependence of attributes with representative accuracy of the cultivated area, but not large enough to make fertility mapping unfeasible. The objective of this study was to define, from the evaluation of geostatistical parameters obtained from a super dense soil sampling, an efficient grid for detecting the spatial dependence of potassium (K+), calcium (Ca2+), and magnesium (Mg2+) in a sandy soil. The experiment was conducted in a 3.2 hectare annatto crop (Bixa orellana L.), in 2017. The geostatistical grid consisted of 31 points per hectare, totaling 101 georeferenced points in an 18x18 m spacing. Soil was sampled at the depths of 0-0.20 m and 0.20-0.40 m. A strong spatial dependence was found for all soil attributes in both depths, while the semivariograms fitted to the spherical model with good coefficients of determination (R²) indicating a spatial correlation between the attributes. The range of spatial dependence was close to 100 m for all attributes in both layers. In sandy soils, an efficient sampling grid to detect the spatial dependence of K+, Ca2+ and Mg2+ must consider a semivariogram range of approximately 100 meters.