458 resultados para variabilidade de atributos físicos do solo


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Pós-graduação em Agronomia (Irrigação e Drenagem) - FCA

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pós-graduação em Agronomia - FEIS

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Os solos são classificados por seus horizontes e atributos diagnósticos para que possam ser agrupados por semelhanças e fornecer informações relativas a sua utilização. Conhecer a variabilidade espacial dos atributos diagnósticos utilizados na classificação do solo é importante na definição do manejo do solo. O objetivo desse trabalho foi verificar a dependência espacial dos atributos diagnósticos na classificação de solos (índice de avermelhamento, gradiente textural e V%) e identificar os limites entre classes de solos. O índice de avermelhamento, gradiente textural e V% do solo foram determinados nos horizontes A e B de uma grade amostral de 65 pontos coletados no Horto da cidade de Mogi-Guaçu, SP. A análise da variabilidade espacial dos atributos estudados foi realizada por meio da geoestatística, considerando a dependência espacial no intervalo de amostragem. Todos os atributos do Horto de Mogi-Guaçu apresentaram dependência espacial e foram interpolados pela krigagem ordinária para obtenção dos mapas temáticos. Com base nos mapas de índice de avermelhamento, gradiente textural e V% foi possível gerar o mapa de classes de solos. Na área de estudo houve maior ocorrência de solos Vermelho Amarelo sem migração de argila do horizonte A para o B e Distrófico.

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The sugarcane crop plays an important role on Brazilian economy,, especially in the aspect related to alternative energy sources. Yield of ratoon cane (2nd cycle) was evaluated in relation to resistance to penetration, gravimetric moisture and organic matter in a Typic Tropustalf, in the municipality of Suzanápolis (SP), 20º28'10'' S and 50º49'20'' W, in the Brazilian cerrado, in 2009. The main purpose was to select, among the attributes surveyed, the one with the highest linear and spatial correlations that explains the variability of sugar cane yield. A geostatistical grid was installed in order to collect data from the soil as well from the plant, with 120 sampling points in an area of 14.53 ha. Organic matter correlated linearly and negatively with penetration resistance, indicating that the soil management practices that aim its increase in the soil profile can improve soil physical conditions, and consequently, the development and yield of sugarcane. Both gravimetric moisture (UG) and content of soil organic matter (OM) correlated directly, linearly (UG2 and MO1) and spatially (UG1 and MO1) with sugarcane yield, proving to be the best attributes, among the evaluated ones, to estimate and increase the sugarcane yield.

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Research has investigated the best nitrogen rate for maize under the most diverse types of soil management. The aim of this study was to evaluate the influence of cover crops, soil management and topdressed N rates on the dry matter production, nutritional status, plant lodging, plant height and first-ear insertion of maize. Field experiments were carried out in Selvíria, Mato Grosso do Sul State, Brazil, in the growing seasons of 2009/2010 and 2010/2011, on a clayey Rhodic Haplustox (20º 20' S and 51º 24' W, at 340 m asl). Thirty-six treatments were established with four replications, in a randomized blocks design, to test combinations of cover crops (millet, Crotalaria juncea and millet + Crotalaria juncea), soil management (tillage with chisel plow + lightweight disking, heavy disking + lightweight disking, and no-tillage system) and N rates (0, 60, 90 e 120 kg ha-1 - urea as source). The maize hybrid DKB 350 YG® was used and topdressing N applied at stage V5 (fifth expanded leaf). Previously grown sunn hemp and millet + sunn hemp resulted in a higher shoot dry matter, P leaf content and total N, P and K uptake. In the no-tillage system, the initial and final population and shoot dry were highest, and first-ear insertion and plant height lower. The application of 120 kg ha-1 topdressed N increased the P leaf content, N and P in the entire plant, shoot dry matter, total N, P and K uptake, plant height, and the first-ear insertion of maize.

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Phosphorus is one of the limiting nutrients for sugarcane development in Brazilian soils. The spatial variability of this nutrient is great, defined by the properties that control its adsorption and desorption reactions. Spatial estimates to characterize this variability are based on geostatistical interpolation. However, inherent uncertainties in the procedure of these estimates are related to the variability structure of the property under study and the sample configuration of the area. Thus, the assessment of the uncertainty of estimates associated with the spatial distribution of available P (Plabile) is decisive to optimize the use of phosphate fertilizers. The purpose of this study was to evaluate the performance of sequential Gaussian simulation (sGs) and ordinary kriging (OK) in the modeling of uncertainty in available P estimates. A sampling grid with 626 points was established in a 200-ha experimental sugarcane field in Tabapuã, São Paulo State. The sGs algorithm generated 200 realizations. The sGs realizations reproduced the statistics and the distribution of the sample data. The G statistic (0.81) indicated good agreement between the values of simulated and observed fractions. The sGs realizations preserved the spatial variability of Plabile without the smoothing effect of the OK map. The accuracy in the reproduction of the variogram of the sample data obtained by the sGs realizations was on average 240 times higher than that obtained by OK. The uncertainty map, obtained by OK, showed less variation in the study area than that obtained by sGs. Thus, the evaluation of uncertainties by sGs was more informative and can be used to define and delimit specific management areas more precisely.