888 resultados para Malha distendida


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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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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.

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Uma das necessidades da agricultura de precisão é avaliar a qualidade dos mapas dos atributos dos solos. Neste sentido, o presente trabalho objetivou avaliar o desempenho dos métodos geoestatísticos: krigagem ordinária e simulação sequencial gaussiana na predição espacial do diâmetro médio do cristal da goethita com 121 pontos amostrados em uma malha de 1 ha com espaçamentos regulares de 10 em 10 m. Após a análise textural e da concentração dos óxidos de ferro, calcularam-se os valores do diâmetro médio do cristal da goethita os quais foram analisados pela estatística descritiva e geoestatística; em seguida, foram utilizadas a krigagem ordinária e a simulação sequencial gaussiana. Com os resultados avaliou-se qual foi o método mais fiel para reproduzir as estatísticas, a função de densidade de probabilidade acumulada condicional e a estatística epsilon εy da amostra. As estimativas E-Type foram semelhantes à krigagem ordinária devido à minimização da variância. No entanto, a krigagem deixa de apresentar, em locais específicos, o grau de cristalinidade da goethita enquanto o mapa E-Type indicou que a simulação sequencial gaussiana deve ser utilizada ao invés de mapas de krigagem. Os mapas E-type devem ser preferíveis por apresentar melhor desempenho na modelagem.

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The use of geostatistical techniques allows detection of the existence of dependence and the spatial distribution of soil properties, thus constituting an important tool in the analysis and detailed description of the behavior of soil physical properties. The aim of the present study was to use geostatistics in assessment of physical properties in a Latossolo (Oxisol) dystrophic under native forest and pasture in the Amazon region of Manicore. Grids with of 70 x 70 m were established in native forest and pasture, and points were marked in these grids spaced at every 10 m, for a total of 64 points. These points were then georeferenced and in each one, soil samples (128) were collected at the depths of 0.00-0.20 and 0.40-0.60 m for a survey of their physical properties. These grids are parallel at a distance of 100 m from one another. The following determinations were made: texture, bulk density and particle density, macroporosity, microporosity, total porosity and aggregate stability in water. After tabulating the data, descriptive statistical analysis and geostatistical analysis were performed. The pasture had a slight variation in its physical properties in relation to native forest, with a high coefficient of variation and weak spatial dependence. The scaled semivariograms were able to satisfactorily reproduce the spatial behavior of the properties in the same pattern as the individual semivariograms, and the use of the parameter range of the semivariogram was efficient for determining the optimal sampling density for the environments under study. The geostatistical results indicate that the removal of native forest for establishing pasture altered the natural variability of the physical properties.

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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.

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Pós-graduação em Engenharia Elétrica - FEIS

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Pós-graduação em Engenharia Elétrica - FEIS

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Pós-graduação em Engenharia Mecânica - FEG

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Pós-graduação em Engenharia Elétrica - FEIS

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Pós-graduação em Engenharia Elétrica - FEIS

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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The State of Mato Grosso do Sul is in full growth of this sector, thus the concern about harvesting systems are being studied, and these systems may influence the weed community interference of weeds in the cane sugar. The integrated management tool attached to geostatistics is to avoid productivity losses due to weed interference. The objective of this work was to study the spatial variability of the seed bank of weeds depending on the system for collecting cane sugar (raw and burning). The experiment was conducted in the area of commercial cultivation of the plant ETH Bioenergy S/A Eldorado Unity. Soil samples were taken with auger layer from 0.00 to 0.40 m depth in both cropping systems. The experimental plot was composed by a mesh consisting of 50 points georeferenced with irregular distances. Soil samples were taken to the greenhouse for germination. The number of weed species was analyzed using descriptive statistics and geostatistical techniques. The seeds of B. pilosa, dicots, bitter grass, nutsedge, dayflower monocots and spatial dependence of the seed bank in the collection system with burning of cane sugar. For the system of harvest only the raw sedge species present spatial dependence of distribution in the seed bank. In the harvest green cane enable the mapping of these species through the kriging maps produced, spot applications of herbicides in integrated management of Cyperus rotundus.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Pós-graduação em Matematica Aplicada e Computacional - FCT