- Citado por Google
- Similares en SciELO
- Similares en Google
Revista Brasileira de Ciência do Solo
versión impresa ISSN 0100-0683
ZANAO JUNIOR, Luiz Antônio; LANA, Regina Maria Quintão; GUIMARAES, Ednaldo Carvalho y PEREIRA, Josefa Monteiro de Araújo. Spatial variability of macronutrient contents in untilled oxisols. Rev. Bras. Ciênc. Solo [online]. 2010, vol.34, n.2, pp.389-400. ISSN 0100-0683. http://dx.doi.org/10.1590/S0100-06832010000200012.
The effectiveness of soil sampling plans may be increased if the spatial variability of soil properties is known and taken into consideration; the factors that determine it should therefore be studied. The objective of this paper was to evaluate the spatial variability of the contents P, K, Ca, Mg, and S in two Oxisols, one very clayey and the other with medium texture, managed in a similar system for eight years, in no-tillage. Soil samples were collected at regular distances of 50 m, totaling 121 points in two layers (0-10 and 10-20 cm). The data were analyzed with descriptive statistics and geostatistics, based on the adjustment of semivariograms. It was found that spatial dependence varies with the nutrient, soil texture and sampling depth. Thus, the spatial variability of the medium texture Oxisol for nutrient levels was generally greater than of the very clayey Oxisol. The spatial variability for nutrient levels was highest in both Oxisols in the 0-10 cm layer. The analysis of spatial dependence showed that the spatial correlation in both soils and both layers was moderate for most nutrients studied. Exponential and spherical semivariogram models were adjusted, the first in greater quantity. Highest amounts of all nutrients were detected in the top 10 cm of soil. The range of spatial dependence in the medium texture Oxisol was lower (9-29 m) than in the very clayey Oxisol (31-399 m). If adopted in a geostatistical sampling scheme, the number of samples to be collected will be lower in the very clayey soil, due to the wider range of all variables.
Palabras clave : geostatistics; soil fertility; semivariogram; sampling.