Atributos do solo e componentes produtivos da soja: Uma abordagem linear, multivariada e geoestatística

• Ano de defesa: 2015
• Autor(a) principal: Lovera, Lenon Henrique [UNESP]
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual Paulista (Unesp)
• Palavras-chave em Português: Agricultura de precisão; Solos - Manejo; Produtividade agrícola; Precision farming
• Link de acesso: http://hdl.handle.net/11449/131899; http://www.athena.biblioteca.unesp.br/exlibris/bd/cathedra/29-10-2015/000853458.pdf

The study of soil properties and plant using geostatistics, and the subsequent generation of kriging maps result in the rational use of fertilizers and thus to reduce costs for producers. In the agricultural year 2013/2014, in Selvíria (MS) aimed to evaluate the spatial dependency and multivariate analysis of physical, chemical attributes, foliar nutrient content and macrofauna of Oxisol in two depths, with yield components and grain yield grown in no-till system. A sampling grid was installed to collect soil data, plant and macrofauna, with 100 sampling points distributed random, in an area of 7980 m 2 . The greatest variability of the attributes analyzed by the coefficient of variation occurred at a depth of 0.00 to 0.10 m above the ground. Some of the attributes studied presented spatial dependence, it is possible to map the area under study. The values of geostatistical ranges recommended for the surveyed attributes should be between 9,9 and 91,8 m. Spatially speaking, the productivity of the soybeans could be estimated by means of co-kriging with the value DS2, DMG, DMP soil and foliar phosphorus. So, low and high values of these attributes indicate sites with higher or lower yields of grain and soybeans. Multivariate analysis has allowed only a few attributes to stand out as main components, being considered the most important for soil management in this area