Modelagem geoestatística por geoprocessamento em uma área da Baixada Santista

Pós-graduação em Geociências e Meio Ambiente - IGCE

Análises estatística multivariada e filogenética dos dipnoiformes brasileiros. Comparações bióticas com o Gondwana ocidental

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Caracterização de uma jazida visando a garantia da qualidade de matérias-primas para indústria cerâmica de revestimentos

Pós-graduação em Geologia Regional - IGCE

Distribuição espacial de Diaphorina citri Kuwayama (Hemiptera: Psyllidae) e sua relação com a expansão do greening em laranjeira Valência, utilizando geoestatística

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Suscetibilidade magnética e sua associação com atributos do solo e do relevo em uma topossequência de Latossolos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Distribuição espacial e raio de agregação de cancro cítrico definidos por geoestatística

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Indicadores de avaliação de programas de pós-graduação no Brasil: uma análise multivariada na área de Matemática

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Geoestatística na avaliação dos atributos físicos em latossolo sob floresta nativa e pastagem na Região de Manicoré, Amazonas

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.

Modelagem geoestatística das incertezas da distribuição espacial do fósforo disponível no solo, em área de cana-de-açúcar

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.

Caracterização de um latossolo em sistemas agroflorestais e mata com o uso de análise estatística multivariada

Pós-graduação em Agronomia (Ciência do Solo) - FCAV

Abordagem multivariada, perfil composicional e construção de curva de calibração para predição do teor de óleo em Jatropha curcas L

Pós-graduação em Agronomia (Genética e Melhoramento de Plantas) - FCAV

Abordagem genética e multivariada na performance agronômica de genótipos de soja oriundos de diferentes genealogias

Pós-graduação em Agronomia (Genética e Melhoramento de Plantas) - FCAV

Número de amostras na análise geoestatística e na krigagem de mapas de atributos do solo

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.

Gestão de estoque no setor de varejo calçadista: abordagem via análise multivariada e teoria do controle ótimo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Abordagem multivariada na análise de diversidade genética em cruzamentos para alto teor de óleo em soja

The soybean crop is considered a high expression around the world. In plant breeding programs, knowledge of genetic diversity is extremely important and in this context, are frequently used multivariate analyzes. Thus, the aim of the present study was to evaluate the genetic divergence between soybean crosses through multivariate techniques. In total, 16 crosses were evaluated, which were in the F2 generation of inbreeding. The evaluated characteristics were plant height at maturity, height of the first pod, number of branches per plant, number of pods per plant, number of nodes per plant, hundred seed weight, grain yield and oil content. For the analyzes was used Euclidean distance, methods of hierarchical clustering UPGMA and Ward and principal component analysis. Genetic distances estimated using Euclidean distance ranged from 1.24 to 8.13, with the smallest distance observed between crosses C1 and C4, and the greatest distance between the C2 crosses and C6. The methods UPGMA clustering and Ward met crossings in five different groups. The principal component analysis explained 86.2% of the variance contained in the original eight variables with three main components. The APM characters, NV, NR, NN, PG% and oil were the main contributors to genetic divergence among traits. Multivariate techniques were crucial to the analysis of genetic diversity, and the methods of Ward and UPGMA clustering and principal components have consistent results in this way, the simultaneous use of these tools in genetic analysis of crosses is indicated