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

• Ano de defesa: 2014
• Autor(a) principal: Macedo, Vinícius Ribamar Alencar
• 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
• Palavras-chave em Português: krigagem; Qualidade física do solo; Semivariograma; Zonas de manejo; Produtividade do milho; Cultivo do milho; kriging; Soil physical quality; Semivariogram; Management zones; Corn productivity; Corn cultivation; Ciência do Solo
• Link de acesso: http://repositorio.uema.br/handle/123456789/183

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