Análise multivariada para definição de zonas de manejo na cultura da soja

• Ano de defesa: 2018
• Autor(a) principal: Diel, Felipe Augusto
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Mato Grosso; Brasil; Instituto de Ciências Agrárias e Ambientais (ICAA) – Sinop; UFMT CUS - Sinop; Programa de Pós-Graduação em Agronomia
• Palavras-chave em Português: Agricultura de precisão; Análise de agrupamento; Análise de componentes principais; Glycine max; Variabilidade espacial; CNPQ::CIENCIAS AGRARIAS::AGRONOMIA; Cluster analysis; Precision agriculture; Component analysis; Spatial variability
• Link de acesso: http://ri.ufmt.br/handle/1/2764

Soybean is the major agricultural crop in Brazilian economy. Its increasing demand encourages the use of technologies that optimize agricultural production. Precision agriculture is an important tool to the improvement of the inputs uses, identification of restricting production situations and reduction of environmental impact, however, it is often misused. The objective of this work was to know and map the behavior of soybeans crop in soils with high variability of attributes, by the application of improved precision agriculture techniques: multivariate data analysis techniques associated with geostatistics to management zones definition. The experiment was installed in Sinop-MT, year 2016, from the settlement of a rectangular mesh of 19 hectares, with 100 randomized sample units, which were determined the soil physical and chemical attributes and grain yield. During the cycle, it was monitored in 3 equivalent sections of the mesh, each representing a range of granulometric level, the contents of water in the soil and the oxygen concentration. By the cluster analysis was possible to distinguish groups from the chemical and physical attributes of the soil. The classic geostatistical analysis, and associated to multivariate data analysis, enabled the mapping of the spatial variability of variables linked to yield. The results indicated that there was a limitation to the grain yield by the nutrients phosphorus and potassium, in chemical attributes, and acroporosity of 0-20cm in physical. It was verified that did not occurred water restriction to the soybean crop in order to limit the grain yield. It was also found that the multivariate data analysis associated with geostatistics is an important tool of precision agriculture, proper to management zones definition.