Comportamento do NDVI da cultura da soja e sua relação com as variáveis agronômicas

• Ano de defesa: 2010
• Autor(a) principal: Groff, Edson Cristiano
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual de Maringá; Brasil; Programa de Pós-Graduação em Agronomia; UEM; Maringá, PR; Departamento de Agronomia
• Palavras-chave em Português: Soja (Glycine max (L.) Merrill); Produtividade de grãos; Cultivo; Agricultura de precisão; Sensoriamento remoto; Variáveis agronômicas; Amostragem; Densidade de plantas; Índice de vegetação; Produtividade; Brasil.; Sampling; Plant density; Vegetation index; Productivity; Brazil.; Ciências Agrárias; Agronomia
• Link de acesso: http://repositorio.uem.br:8080/jspui/handle/1/1199

The soybean (Glycine max L. Merrill) is distinguished by the great economic importance and growth in recent years. With the increasing use of precision agriculture (PA) it is crucial to understand the variability of the agronomic traits. Using ground sensors it's possible to establish relationships between spectral responses and growth parameters of the culture. This is possible through the reading of vegetation indexes, such as The Normalized Difference Vegetation Index (NDVI). This study was conducted from October 2008 to April 2009, in Ponta Grossa - PR, with the aim of evaluating the spectral response of soybean by means of NDVI and its correlation with agronomic variables such as height of plants, plant density, and dry weight yield, grain yield and leaves nutrient content. Six NDVI readings were performed using a spectroradiometer. Regression analysis were performed in order to determine which agronomic variables established some relationship degree with the NDVI. The NDVI behavior was characteristic for the canopy of plants. For EF V9, the variables grain and dry weight yield had r2 of 0.59 and 0.28, respectively. For the variable leaf copper, the NDVI was able to see the variation between the EF and R3, where it obtained r2 of 0.60. The NDVI levels and some agronomic variables separation in classes (low, medium and high), allowed the understanding of their spatial distribution and establish sampling and/or management areas.