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| Armindo,Robson A.; Coelho,Rubens D.; Teixeira,Marconi B.; Ribeiro Junior,Paulo J.. |
| This study aimed to evaluate the spatial variability of leaf content of macro and micronutrients. The citrus plants orchard with 5 years of age, planted at regular intervals of 8 x 7 m, was managed under drip irrigation. Leaf samples were collected from each plant to be analyzed in the laboratory. Data were analyzed using the software R, version 2.5.1 Copyright (C) 2007, along with geostatistics package GeoR. All contents of macro and micronutrients studied were adjusted to normal distribution and showed spatial dependence.The best-fit models, based on the likelihood, for the macro and micronutrients were the spherical and matern. It is suggest for the macronutrients nitrogen, phosphorus, potassium, calcium, magnesium and sulfur the minimum distances... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Citrus latifolia Tan.; Macronutrients; Micronutrients; Geostatistics. |
| Ano: 2012 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162012000300007 |
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| Guedes,Luciana P. C.; Ribeiro Junior,Paulo J.; Uribe-opazo,Miguel A.; Bastiani,Fernanda de. |
| ABSTRACT This study aimed to compare thematic maps of soybean yield for different sampling grids, using geostatistical methods (semivariance function and kriging). The analysis was performed with soybean yield data in t ha-1 in a commercial area with regular grids with distances between points of 25x25 m, 50x50 m, 75x75 m, 100x100 m, with 549, 188, 66 and 44 sampling points respectively; and data obtained by yield monitors. Optimized sampling schemes were also generated with the algorithm called Simulated Annealing, using maximization of the overall accuracy measure as a criterion for optimization. The results showed that sample size and sample density influenced the description of the spatial distribution of soybean yield. When the sample size was... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Accuracy indices; Optimization; Sampling grids; Spatial variability. |
| Ano: 2016 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162016000100114 |
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| Guedes,Luciana P. C.; Uribe-Opazo,Miguel A.; Ribeiro Junior,Paulo J.; Dalposso,Gustavo H.. |
| ABSTRACT Spatial variability depends on the sampling configuration and characteristics associated with the georeferenced phenomenon, such as geometric anisotropy. This study aimed to determine the influence of the sampling design on parameter estimation in an anisotropic geostatistical model and the spatial estimation of a georeferenced variable at unsampled locations. Datasets were simulated with geometric anisotropy, considering five values for the anisotropic ratio (1, 2, 3, 4, 5), and three sampling designs: lattice, random and lattice plus close pairs. The simulation results were used as a reference to select anisotropic models to describe the spatial dependence structure in chemical soil properties. For each dataset (with either simulated or chemical... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Bootstrap; Directional trend; Geostatistics; Spatial variability; Tests of isotropy. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000200260 |
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