103 resultados para SOIL SCIENCE
Resumo:
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Resumo:
Pós-graduação em Agronomia (Produção Vegetal) - FCAV
Resumo:
Pós-graduação em Agronomia (Ciência do Solo) - FCAV
Resumo:
Pós-graduação em Agronomia (Ciência do Solo) - FCAV
Resumo:
Pós-graduação em Agronomia (Ciência do Solo) - FCAV
Resumo:
Pós-graduação em Agronomia (Energia na Agricultura) - FCA
Resumo:
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Resumo:
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Resumo:
Pós-graduação em Agronomia (Horticultura) - FCA
Resumo:
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Resumo:
Pós-graduação em Agronomia (Irrigação e Drenagem) - FCA
Resumo:
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Resumo:
The sampling scheme is essential in the investigation of the spatial variability of soil properties in Soil Science studies. The high costs of sampling schemes optimized with additional sampling points for each physical and chemical soil property, prevent their use in precision agriculture. The purpose of this study was to obtain an optimal sampling scheme for physical and chemical property sets and investigate its effect on the quality of soil sampling. Soil was sampled on a 42-ha area, with 206 geo-referenced points arranged in a regular grid spaced 50 m from each other, in a depth range of 0.00-0.20 m. In order to obtain an optimal sampling scheme for every physical and chemical property, a sample grid, a medium-scale variogram and the extended Spatial Simulated Annealing (SSA) method were used to minimize kriging variance. The optimization procedure was validated by constructing maps of relative improvement comparing the sample configuration before and after the process. A greater concentration of recommended points in specific areas (NW-SE direction) was observed, which also reflects a greater estimate variance at these locations. The addition of optimal samples, for specific regions, increased the accuracy up to 2 % for chemical and 1 % for physical properties. The use of a sample grid and medium-scale variogram, as previous information for the conception of additional sampling schemes, was very promising to determine the locations of these additional points for all physical and chemical soil properties, enhancing the accuracy of kriging estimates of the physical-chemical properties.
Resumo:
In crop year 2006/07, in Selviria, MS, Brazil, were analyzed the productivity of beans because of the chemical attributes of an Acrustox cultivated under conditions of high technological level of management by no-tillage irrigated with pivot central. The objective was to select, among the attributes studied soil, the one with the best representation to explain the variability of agricultural productivity. Geostatistical grid was installed to collect data from soil and plant, with 117 sampling points in an area of 2,025 m(2) and homogeneous slope of 0.055 m m(-1). From the standpoint of linear and spatial bean yield was respectively explained in terms of P and soil pH. So much for the values of phosphorus (P) in the intermediate layer and subsurface between 24-26 mg dm(-3), as well as for Hydrogen (pH) in the surface layer between 5.0 to 5.4, resulted in sites with the most high yield (2,160-2,665 kg ha(-1)).
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)