313 resultados para geostatistical


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O experimento foi realizado na área experimental do Departamento de Engenharia Rural da Faculdade de Ciências Agronômicas – Unesp/Botucatu, Estado de São Paulo, em duas estufas dispostas em diferentes orientações geográficas, Leste/Oeste e Norte/Sul. A alface (Lactuva sativa L.) cv. Elisa foi cultivada em ambas estufas, sendo semeada em 05/05/99, transplantada em 29/05/99 e colhida em 31/06/99. Utilizou-se tensiômetros para monitorar o potencial de água no solo para realizar o manejo do sistema de irrigação por gotejamento. Microevaporímetros eqüidistantes de 3 m e colocados em 3 alturas, 0.50, 1.00 e 1.50 m, termohigrógrafos e tanques Classe “A” foram instalados nas duas estufas. Através de análise geoestatística, não se observou dependência espacial nem variabilidade espacial da evaporação nas duas estufas. Entretanto, a altura dos evaporímetros apresentou diferenças significativas: a evaporação à altura de 1.50 foi menor que nas outras duas.As médias de temperatura, umidade relativa e déficit de pressão de vapor do arnão diferiram estatisticamente entre as estufas e o ambiente externo. Os valores médios de evaporação de água no tanque Classe A instalado fora das estufas diferiram estatisticamente quando comparados com os instalados no interior das estufas, porém, entre as orientações não se constatou diferença significativa. Pôde-se verificar que não houve diferença significativa das características agronômicas da alface em ambas orientações estudadas. No entanto, houve diferença significativa para essas características entre os canteiros no interior das mesmas, havendo variância espacial para os dados de matéria fresca apenas na estufa N/S.

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In Brazil, common bean is in one of the most representative economic crops, not only because of its growing area but also because of the economic value of its production. In the crop year 2006/07, in Selvíria (MS), we analyzed the common bean yield as a function of some physical attributes of a Typic Acrustox in minimum tillage and center pivot irrigation system. The aim of this work was to evaluate among the soil physical attributes, under minimum tillage, those that better explain the variability of bean yield using the Pearson and spatial correlations,. A geostatistical grid was installed to collect data from soil and plants, with 117 sampling points in an area of 2025 m² and homogeneous slope of 0.055 m m-1. The results showed a low yield of bean, which occurred probably due to a lower density of plants that the system provided. Thus, for the minimum tillage system, the bean yield could be explained as a function of total porosity and bulk density.

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

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The socioeconomic importance of sugar cane in Brazil is unquestionable because it is the raw material for the production of ethanol and sugar. The accurate spatial intervention in the management of the crop, resulting zones of soil management, increases productivity as well as its agricultural yields. The spatial and Person's correlations between sugarcane attributes and physico-chemical attributes of a Typic Tropustalf were studied in the growing season of 2009, in Suzanápolis, State of São Paulo, Brazil (20°28'10'' S lat.; 50°49'20'' W long.), in order to obtain the one that best correlates with agricultural productivity. Thus, the geostatistical grid with 120 sampling points was installed to soil and data collection in a plot of 14.6 ha with second crop sugarcane. Due to their substantial and excellent linear and spatial correlations with the productivity of the sugarcane, the population of plants and the organic matter content of the soil, by evidencing substantial correlations, linear and spatial, with the productivity of sugarcane, were indicators of management zones strongly attached to such productivity.

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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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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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In agriculture, the search for higher crop yields based on sustainable soil management has led to a gradual pursuit of knowledge of the variables related to production systems. The identification of the causes of variability of these properties has become a part of strategic planning in the sugar and ethanol industry. This study investigated the spatial variability of iron oxides in the clay fraction and its relationship to soil physical and chemical properties in different sugarcane cultivation systems in the region of Ribeirão Preto, São Paulo State. Two 1-ha plots were outlined in areas with mechanical and manual harvesting systems. Soil samples were taken at 126 points from the 0.00-0.25 m layer in both areas. The mineralogical and chemical data were subjected to geostatistical analyses, to determine the spatial dependence, semivariograms and kriging maps of the properties. To analyze the correlation between the parameters cross-semivariograms were constructed. The spatial variability of chemical properties was greater in areas with mechanical harvesting than burnt harvesting (manual harvesting), whereas the range of the mineralogical properties was largest in the area of green-harvested sugarcane. The properties organic matter, mean crystal diameter goethite had a negatively spatial correlation, while clay was positive correlated with P sorption in the two sugarcane harvest systems.

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Pós-graduação em Biometria - IBB

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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)).

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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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The objective of this study was to analyze different intensities of soil sampling for accuracy in geostatistical analysis and interpolation maps for precision agriculture in the sugarcane area. Soil samples were collected at two regular grids at a depth of 0.00 to 0.20m for granulometric analysis (area 1) and soil fertility (area 2). We compared soil sampling intensities: 208, 105, 58 and 24 points in Area 1 and 206, 102 and 53 points in Area 2. The data were submitted to descriptive analysis and geostatistics. The variograms constructed with 105 points didn't differ from variograms with 208 points, which doesn't occur for 58 and 24 points. The increase of sampling interval and reducing the number of points promote greater error in kriging. Samples with more than 100 points per area did not result in significant improvements in the error of kriging, or differed in the amount of fertilizer applied to the field.

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