Local influence for spatial analysis of soil physical properties and soybean yield using student's t-distribution

The modeling and estimation of the parameters that define the spatial dependence structure of a regionalized variable by geostatistical methods are fundamental, since these parameters, underlying the kriging of unsampled points, allow the construction of thematic maps. One or more atypical observations in the sample data can affect the estimation of these parameters. Thus, the assessment of the combined influence of these observations by the analysis of Local Influence is essential. The purpose of this paper was to propose local influence analysis methods for the regionalized variable, given that it has n-variate Student's t-distribution, and compare it with the analysis of local influence when the same regionalized variable has n-variate normal distribution. These local influence analysis methods were applied to soil physical properties and soybean yield data of an experiment carried out in a 56.68 ha commercial field in western Paraná, Brazil. Results showed that influential values are efficiently determined with n-variate Student's t-distribution.

Soil water retention and s index after crop rotation and chiseling

Soil compaction can be minimized either mechanically or biologically, using plant species with vigorous root systems. An experiment was carried out with soybean (Glycine max) in rotation with triticale (X Triticosecale) and sunflower (Helianthus annuus) in fall-winter associated with pearl millet (Pennisetum glaucum), grain sorghum (Sorghum bicolor) or sunn hemp (Crotalaria juncea) in spring. Crop rotation under no-till was compared with mechanical chiseling. The experiment was carried out in Botucatu, São Paulo State, Brazil. Soil quality was estimated using the S index and soil water retention curves (in the layers of 0-0.05, 0.075-0.125, 0.15-0.20, 0.275-0.325, and 0.475-0.525 m deep). Crop rotation and chiseling improved soil quality, increasing the S index to over 0.035 to a depth of 20 cm in the soil profile. The improved soil quality, as shown by the S index, makes the use of mechanical chiseling unnecessary, since after 3 years the soil physical quality under no-tilled crop rotation and chiseling was similar.

Distribution and vertical stratification of carbon and nitrogen in soil under different managements in the pampean region of Argentina

One of the expected benefits of no-tillage systems is a higher rate of soil C sequestration. However, higher C retention in soil is not always apparent when no-tillage is applied, due e.g., to substantial differences in soil type and initial C content. The main purpose of this study was to evaluate the potential of no-tillage management to increase the stock of total organic C in soils of the Pampas region in Argentina. Forty crop fields under no-tillage and conventional tillage systems and seven undisturbed soils were sampled. Total organic C, total N, their fractions and stratification ratios and the C storage capacity of the soils under different managements were assessed in samples to a depth of 30 cm, in three layers (0-5, 5-15 and 15-30 cm). The differences between the C pools of the undisturbed and cultivated soils were significant (p < 0.05) and most pronounced in the top (0-5 cm) soil layer, with more active C near the soil surface (undisturbed > no-tillage > conventional tillage). Based on the stratification ratio of the labile C pool (0-5/5-15 cm), the untilled were separated from conventionally tilled areas. Much of the variation in potentially mineralizable C was explained by this active C fraction (R² = 0.61) and by total organic C (R² = 0.67). No-till soils did not accumulate more organic C than conventionally tilled soils in the 0-30 cm layer, but there was substantial stratification of total and active C pools at no till sites. If the C stratification ratio is really an indicator of soil quality, then the C storage potential of no-tillage would be greater than in conventional tillage, at least in the surface layers. Particulate organic C and potentially mineralizable C may be useful to evaluate variations in topsoil organic matter.