97 resultados para Spatial Empirical bayes Smoothing


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This study aimed to establish relationships between maize yield and rainfall on different temporal and spatial scales, in order to provide a basis for crop monitoring and modelling. A 16-year series of maize yield and daily rainfall from 11 municipalities and micro-regions of Rio Grande do Sul State was used. Correlation and regression analyses were used to determine associations between crop yield and rainfall for the entire crop cycle, from tasseling to 30 days after, and from 5 days before tasseling to 40 days after. Close relationships between maize yield and rainfall were found, particularly during the reproductive period (45-day period comprising the flowering and grain filling). Relationships were closer on a regional scale than at smaller scales. Implications of the crop-rainfall relationships for crop modelling are discussed.

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The objective of this work was to assess the spatial and temporal variability of sugarcane yield efficiency and yield gap in the state of São Paulo, Brazil, throughout 16 growing seasons, considering climate and soil as main effects, and socioeconomic factors as complementary. An empirical model was used to assess potential and attainable yields, using climate data series from 37 weather stations. Soil effects were analyzed using the concept of production environments associated with a soil aptitude map for sugarcane. Crop yield efficiency increased from 0.42 to 0.58 in the analyzed period (1990/1991 to 2005/2006 crop seasons), and yield gap consequently decreased from 58 to 42%. Climatic factors explained 43% of the variability of sugarcane yield efficiency, in the following order of importance: solar radiation, water deficit, maximum air temperature, precipitation, and minimum air temperature. Soil explained 15% of the variability, considering the average of all seasons. There was a change in the correlation pattern of climate and soil with yield efficiency after the 2001/2002 season, probably due to the crop expansion to the west of the state during the subsequent period. Socioeconomic, biotic and crop management factors together explain 42% of sugarcane yield efficiency in the state of São Paulo.

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The objective of this work was to evaluate sampling density on the prediction accuracy of soil orders, with high spatial resolution, in a viticultural zone of Serra Gaúcha, Southern Brazil. A digital elevation model (DEM), a cartographic base, a conventional soil map, and the Idrisi software were used. Seven predictor variables were calculated and read along with soil classes in randomly distributed points, with sampling densities of 0.5, 1, 1.5, 2, and 4 points per hectare. Data were used to train a decision tree (Gini) and three artificial neural networks: adaptive resonance theory, fuzzy ARTMap; self‑organizing map, SOM; and multi‑layer perceptron, MLP. Estimated maps were compared with the conventional soil map to calculate omission and commission errors, overall accuracy, and quantity and allocation disagreement. The decision tree was less sensitive to sampling density and had the highest accuracy and consistence. The SOM was the less sensitive and most consistent network. The MLP had a critical minimum and showed high inconsistency, whereas fuzzy ARTMap was more sensitive and less accurate. Results indicate that sampling densities used in conventional soil surveys can serve as a reference to predict soil orders in Serra Gaúcha.

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The objective of this work was to evaluate the spatial distribution of thrips in different crops, and the correlation between meterological parameters and the flight movements of this pest, using immunomarking. The experiment was conducted in cultivated areas, with tomato (Solanum lycopersicum), potato (Solanum tuberosum), and onion (Allium cepa); and non-cultivated areas, with weedy plants. The areas with tomato (100 days), potato (20 days), and weeds were sprayed with casein, albumin, and soy milk, respectively, to mark adult thrips; however, the areas with onion (50 days) and tomato (10 days) were not sprayed. Thrips were captured with georeferenced blue sticky traps, transferred into tubes, and identified by treatment area with the Elisa test. The dependence between the samples and the capture distance was determined using geostatistics. Meteorlogical parameters were correlated with thrips density in each area. The three protein types used for immunomarking were detected in different proportions in the thrips. There was a correlation between casein-marked thrips and wind speed. The thrips flew a maximum distance of 3.5 km and dispersed from the older (tomato) to the younger crops (potato). The immunomarking method is efficient to mark large quantities of thrips.

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In this work is presented and tested (for 106 adducts, mainly of the zinc group halides) two empirical equations supported in TG data to estimate the value of the metal-ligand bond dissociation enthalpy for adducts: <D> (M-O) = t i / g if t i < 420 K and <D> (M-O) = (t i / g ) - 7,75 . 10-2 . t i if t i > 420 K. In this empirical equations, t i is the thermodynamic temperature of the beginning of the thermal decomposition of the adduct, as determined by thermogravimetry, andg is a constant factor that is function of the metal halide considered and of the number of ligands, but is not dependant of the ligand itself. To half of the tested adducts the difference between experimental and calculated values was less than 5%. To about 80% of the tested adducts, the difference between the experimental (calorimetric) and the calculated (using the proposed equations) values are less than 15%.

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The atomic shell structure can be observed by inspecting the experimental periodic properties of the Periodic Table. The (quantum) shell structure emerges from these properties and in this way quantum mechanics can be explicitly shown considering the (semi-)quantitative periodic properties. These periodic properties can be obtained with a simple effective Bohr model. An effective Bohr model with an effective quantum defect (u) was considered as a probe in order to show the quantum structure embedded in the Periodic Table. u(Z) shows a quasi-smoothed dependence of Z, i.e., u(Z) ≈ Z2/5 - 1.

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The spatial dynamics of Citrus Variegated Chlorosis (CVC) was studied in a five-year old commercial orchard of 'Valencia' sweet orange (Citrus sp.) trees, located in the northern region of the state of São Paulo, Brazil. One thousand trees were assessed in 25 rows of 40 trees, planted at 8 x 5 m spacing. Disease incidence data were taken beginning in March 1994 and ending in January 1996, at intervals of four to five months. Disease aggregation was observed through the dispersion index analysis (Ib), which was calculated by dividing the area into quadrants. CVC spatial dynamics was examined using semivariogram analysis, which revealed that the disease was aggregated in the field forming foci of 10 to 14 m. For each well-fitted model, a kriging map was created to better visualize the distribution of the disease. The spherical model was the best fit for the data in this study. Kriging maps also revealed that the incidence of CVC increased in periods during which the trees underwent vegetative growth, coinciding with greater expected occurrence of insect vectors of the bacterium in the field.