Advisor(s)
Abstract(s)
Resumo
O objetivo do presente trabalho é estudar o
relacionamento entre os atributos do solo conteúdo de
fósforo, potencial hidrogeniônico e densidade do solo com a
produtividade da soja. As amostras foram coletadas em um
Latossolo Vermelho, em área localizada no município de
Braganey-PR, no Paraná, cultivada com soja (Glycine Max L).
Na área experimental foram demarcados 84 elementos
amostrais ao longo de uma transeção de 252 metros, com os
elementos espaçados metros entre si. Para a análise da
dependência espacial foram construídos autocorrelogramas,
identificando-se correlação entre as observações de
produtividade da soja, teor de fósforo, pH e densidade do solo.
Na análise da dependência espacial cruzada foram empregados
correlogramas cruzados, os quais mostraram dependência
espacial cruzada entre produtividade da soja e pH. Os modelos
estatísticos construídos para estimar a produtividade da soja
foram os modelos autoregressivos em Espaço de Estados e o
modelo de regressão linear simples. A análise realizada
mostrou que o modelo em Espaço de Estados foi mais
eficiente em comparação com o modelo de regressão linear
simples.
Abstract The objective of this study was to assess the relationship between soybean productivity and soil chemical properties. The experimental data were obtained at a Rhodic Acrudox soil, from Braganey County, State of Parana, in an area where soybean was grown. The data sets were sampled along 84 points on a 254 meters long spatial transect, 3 m spaced from each other. At each site, soybean crop samples were collected for yield quantification and soil samples were collected in the 0.10 - 0.20 m deep layer. At the experimental area, the samples were sampled along 84 points on a spatial transect, 3.0 meters spaced from each other. The State-Space approach was used to assess soybean yield estimate on position i, influenced by soybean yield, pH and phosphorus on position i-1. With the implementation of a space of states, only the variable pH showed significant correlation at 5% significance level, with the dependent variable, with the coefficient R2 equal to 0.852. This does possible to show the influence of independent variable pH on the response variable, which is the soybean yield. With the implementation of a space of states, only the variable pH showed significant correlation at 5% significance level, with the dependent variable, with the coefficient R2 equal to 0.852.
Abstract The objective of this study was to assess the relationship between soybean productivity and soil chemical properties. The experimental data were obtained at a Rhodic Acrudox soil, from Braganey County, State of Parana, in an area where soybean was grown. The data sets were sampled along 84 points on a 254 meters long spatial transect, 3 m spaced from each other. At each site, soybean crop samples were collected for yield quantification and soil samples were collected in the 0.10 - 0.20 m deep layer. At the experimental area, the samples were sampled along 84 points on a spatial transect, 3.0 meters spaced from each other. The State-Space approach was used to assess soybean yield estimate on position i, influenced by soybean yield, pH and phosphorus on position i-1. With the implementation of a space of states, only the variable pH showed significant correlation at 5% significance level, with the dependent variable, with the coefficient R2 equal to 0.852. This does possible to show the influence of independent variable pH on the response variable, which is the soybean yield. With the implementation of a space of states, only the variable pH showed significant correlation at 5% significance level, with the dependent variable, with the coefficient R2 equal to 0.852.
Description
Keywords
Autocorrelação Correlação cruzada Dependência espacial autocorrelation, cross correlation,
Citation
Oliveira, Márcio P.; Tavares, Maria H.; Timm, Luís & Niedzialkoski, Rosana (2013). Modelo em espaço de estados para o relacionamento entre atributos do solo e produtividade da soja. Millenium, n.º 44 (janeiro/junho). Pp. 41‐53.