InfluÃncia local para modelos geoestatÃsticos utilizando a produtividade da soja e atributos quÃmicos do solo / Local influence on geostatistical models using soy productivity and chemical soil

AUTOR(ES)
FONTE

IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia

DATA DE PUBLICAÇÃO

16/02/2012

RESUMO

Soy is one of the main crops in Brazil and in the region of Cascavel / PR, where agricultural production is large, although some factors that affect productivity, monitoring and process management have been diagnosed by geostatistical models for analysis of agricultural data. Studies on the spatial variability of soil attributes associated with soybean yield, provide recommendations for doses o with varied rates, according to the maps created by spatial models. The diagnostic study on influential points is a recommended procedure for studies on spatial variability. Detecting the influential points through local influence allows measuring the changes that these points have influence on and the construction of the thematic map. This paper aims to present studies on local influence in linear spatial models considering as dependent variable soybean yield and as covariates Carbon (C), Calcium (Ca), Potassium (K), Magnesium (Mg), Manganese (Mn) and Phosphorus (P). The study on local influence is held in the response variable and the covariates using additive disturbances. The techniques of local influence diagnostics, according to the final results, were efficient in identifying outliers considered influential variables for the individual linear spatial model

ASSUNTO(S)

mÃxima verossimilhanÃa dependÃncia espacial maximum likelihood spatial dependence precision agriculture engenharia agricola agricultura de precisÃo

ACESSO AO ARTIGO

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