Uso do NDVI para prever qualidade de sementes de soja (Glycine max)

• Ano de defesa: 2019
• Autor(a) principal: Boelter, Jessica Hoch
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Agronomia; UFSM; Programa de Pós-Graduação em Agronomia; Centro de Ciências Rurais
• Palavras-chave em Português: Agricultura de precisão; Produção de sementes; Índice de vegetação; Precision agriculture; Management; Vegetation index; CNPQ::CIENCIAS AGRARIAS::AGRONOMIA
• Link de acesso: http://repositorio.ufsm.br/handle/1/20693

With the increase of soybean area and productivity in Rio Grande do Sul and the increasing use of geoprocessing tools in agriculture, the identification of seed quality through multispectral images becomes of great value for the production process. The objective of this work was to evaluate the correlation for the different vegetation levels determined by multispectral satellite images with soybean seed quality, determining management zones in the area, in order to improve the logistic efficiency of crop harvest. The experiment was conducted in the municipality of Vila Nova do Sul, Rio Grande do Sul, in the 2017/2018 and 2018/2019 crop years, with 10 m spatial resolution images processed giving rise to the vegetation index for study. Seed lots sampling was determined by management zones defined by the vegetation index, submitted to laboratory tests. The results were interpolated, generating management zones of different potentials in the field. The germination and vigor by first count parameters were positively related to the vegetation index evaluated in both harvests. The physical parameter humidity presented a positive relation of 43.62% and 47.08% of the area, in the first and second crop, respectively.