Variabilidade espacial de atributos físicos do solo sob lavoura de café conilon

• Ano de defesa: 2015
• Autor(a) principal: Santos, Eduardo Oliveira de Jesus
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Espírito Santo; BR; Mestrado em Agricultura Tropical; UFES; Programa de Pós-Graduação em Agricultura Tropical
• Palavras-chave em Português: Management zones; Spatial correlation; Sample planning; Zonas de manejo; Correlação espacial; Planejamento amostral; Solos; Análise espacial (Estatística); Café - Cultivo; Geologia - Métodos estatísticos; Agronomia; 63
• Link de acesso: http://repositorio.ufes.br/handle/10/8265

Knowledge of the spatial variability of soil physical properties through the use of geostatistics can be a great tool to aid the management of coffee. The aim of this study was to determine the spatial variability of soil physical properties and their spatial correlation with productivity, and delimit agricultural management zones and propose a soil sampling methodology that best fit to the management system conditions. The experiment was conducted in a conilon coffee plantation, deployed in 2010, with the Bamburral genotype, in a double spacing 3.0 x 2.0 x 1.0 m (4,000 plants ha-1 ), located in São Mateus, state Espirito Santo, Brazil. It was installed an irregular sampling grid with dimensions of 107 x 95.7 m (10,240 m2 ). At each sampling point, soil samples were collected for physical analysis of the soil, where it was determined the soil bulk density (Ds), particle density (Dp), macroporosity (Macro) and soil microporosity (Micro), total porosity (VTP) and the size fractions of soil. The productivity was estimated through the in plant harvest for each sampling point, and its value multiplied by the population of plants per hectare. The data were submitted to descriptive statistical analysis, multivariate and geostatistical. Except for Dp, all physical soil attributes presented spatial dependence, with strong and moderate spatial dependency index. With the help of cluster analysis technique, it was delimited two management zones. The association between knowledge of the spatial variability with the definition of management zones can be used to improve application efficiency of agricultural inputs. There was a spatial correlation positive to Macro and VTP and negative for Ds, Micro and CAD with productivity conilon coffee. It was recommended, in similar conditions to the study area, collect 3 deformed samples of soil and 11 undisturbed soil samples to determine the average values of the soil physical properties.