Geostatistics, kriging and multivariate physical attributes of an Oxisol under pasture
DOI:
https://doi.org/10.6008/CBPC2179-6858.2022.006.0001Keywords:
Geostatistics, Kriging, Soil management, Decision makingAbstract
Knowing the spatial distribution of soil and plant attributes is essential for the rational management of agricultural activities, and for this purpose indicators of soil physical quality can be used. The objective of this work was to identify the structure of spatial dependence of soil physical attributes and to correlate them through principal component analysis with pasture productivity. The experiment was conducted in the municipality of Corrente-PI. For the mapping of soil physical attributes and pasture productivity, 78 points were evaluated, referring to the crossing points of a sample mesh with regular intervals of 10 m. The hypothesis of data normality was tested in descriptive statistics using the Kolmogorov-Smirnov test and spatial dependence was analyzed using semivariogram adjustments. Soil physical quality indicator attributes such as: soil bulk density, total porosity, soil resistance to penetration, gravimetric moisture showed a strong degree of spatial dependence on degraded pasture area, suggesting that under the conditions studied, these variables are the main factors responsible for spatialization of pasture dry matter productivity that there was a moderate degree of spatial dependence. Soil physical attributes under degraded pasture showed spatial dependence structure in all layers studied. The Kriging Technique proved to be a viable alternative for data interpolation in unsampled locations in the study area.
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