Variabilidade espacial dos atributos físicos do solo e componentes de produtividade do milho em um latossolo amarelo distrocões

Detalhes bibliográficos
Ano de defesa: 2014
Autor(a) principal: Macedo, Vinícius Ribamar Alencar
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: UEMA
Brasil
Campus São Luis Centro de Ciências Agrárias – CCA
Centro de Ciências Agrárias
PROGRAMA DE PÓS-GRADUAÇÃO EM AGROECOLOGIA
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://repositorio.uema.br/handle/123456789/183
Resumo: Precision agriculture is based on the idea that the variability of key factors responsible for crop productivity can be identified, quantified and spatially delimited. Therefore, this work aimed to evaluate and map the variation spatial analysis of soil physical attributes and corn productivity components and examine difference between the spatial variation of these attributes and corn yield. For this they were 417 sample points were delimited in a uniform grid of 5 x 7 m. At each sampling point undisturbed samples were collected in volumetric rings, to determine the physical attributes and with the digital penetrometer to determine resistance to penetration, in corn crop productivity components were evaluated. Ordinary kriging was used to interpolate values, in order to define the spatial pattern of scientific research using semivariograms, which allowed the creation of isoline maps. The variables studies studied spatial dependence, fitting the exponential model for most of the variables. The experimental note proved to be adequate for assessing dependence space of research. Corn productivity was correlated with resistance to penetration into the layer of 11 to 20 cm, maximum pressure, total porosity and fine sand content, which highlighted the influence of these attributes on corn productivity, therefore the attributes selected can be used as physical indicators in mapping zones of specific management for corn cultivation