Journal of Food, Agriculture and Environment




Geostatistical models in a study on the spatio-temporal dependence of agricultural data


Author(s):

Bruna Gabriela Wendpap 1, Miguel Angel Uribe-Opazo 2*, Jerry Adriani Johann 3, Márcio Antônio Vilas Boas 4, Eduardo Godoy De Souza 5

Recieved Date: 2015-06-08, Accepted Date: 2015-09-28

Abstract:

Knowing the spatial dependence of a given attribute and studying the behavior of such dependence in time, allow for its mapping and monitoring. This will lead to good local management practices of farms, with the intent to achieve greater profitability, as well as reduced environmental liability usually caused by poor awareness on the actual physicochemical requirements of a particular soil. The present work aimed to model, in different ways, the structure of spatial dependence of observations in time and its influence on the generation of thematic maps. The “experimental area” data were gathered from an experiment employed at the Research Center Eloy Gomes from the Cooperativa Central Agropecuária de Desenvolvimento Tecnológico e Econômico Ltda (COODETEC), in the city of Cascavel - PR. The area was 1.33 ha, divided into a regular grid of 256 plots of 7.20 m x 7.20 m, summing up a total of 128 plots with local chemical management and 128 plots with no local chemical management. For five years, maps of soil potassium in the experimental area were compared through individual geostatistical models; scaling semivariance model and linear models with multiple independent replications. The accuracy rates indicated similarity between the thematic maps generated by the various methods proposed. A model of spatial estimation of soybean yield was also generated, considering multiple independent replications, depending on covariates.

Keywords:

Scaled semivariogram, thematic maps, spatial linear model


Journal: Journal of Food, Agriculture and Environment
Year: 2015
Volume: 13
Issue: 3&4
Category: Agriculture
Pages: 21-28


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