Determinação de unidades de manejo a partir de mapas de produtividade normalizada e padronizada equivalente na cultura da soja.

• Autor(a) principal: Suszek, Grazieli
• Data de Publicação: 2007
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações do UNIOESTE
• Texto Completo: http://tede.unioeste.br:8080/tede/handle/tede/2635
• topic: soja; agricultura de precisão; geoestatística; soybean; precision agriculture; geostatistics; CNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA

Great transformations are being visualized in Brazilian agriculture. The precision agriculture is bringing new techniques, a degree of significantly bigger detailing of the agricultural methods and an increase of the efficiency on the basis of the site-specific management. In this context, it is important the establishment of methodologies of productivity information that can be used for determination of management zones. The objective of this work was to analyze two techniques for definition of management zones in a productive area using normalized and standardized yield maps presented in this work. It was used data soy yield, collected during the years of 1998 to 2002, in an area from the Cooperativa Central Agropecuária de Desenvolvimento Tecnológico e Econômico Ltda. (COODETEC), situated in Cascavel - PR, Brazil. The sampling area has 1.74 ha, with 128 plots with site-specific fertilization and 128 plots with conventional fertilization. The original data of each variable in study had been analyzed using geoestatistics techniques and the contour maps generated by means of kriging interpolation. The values of the contour maps of each variable and of each year had been normalized by the techniques of normalized yield and equivalent standardized yield, being later classified in management zones. It could be concluded that the two methods of management zones definition had revealed efficient, presenting similarities in the data disposal. Due to equivalent standardized yield uses standard score, it contemplates one better statistics justification, but it presents a bigger implementation difficulty.