Estratégias para o monitoramento do desempenho agronômico em vegetais a partir de imagens aéreas digitais

• Ano de defesa: 2022
• Autor(a) principal: Assis, Pablo Henrique de Souza
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Uberlândia; Brasil; Programa de Pós-graduação em Agricultura e Informações Geoespaciais
• Palavras-chave em Português: Lactuca sativa L; Solanum tuberosum L; Citrullus lanatus L; Fenotipagem por imagem; Índices de vegetação; Hortaliças; image phenotyping; vegetation indices; vegetables; CNPQ::OUTROS::ENGENHARIA CARTOGRAFICA; CNPQ::CIENCIAS AGRARIAS::AGRONOMIA; Agronomia; Hortaliças - Imagens de sensoriamento remoto; Alface - Imagens de sensoriamento remoto; Batata - Imagens de sensoriamento remoto; Melancia - Imagens de sensoriamento remoto; Agricultura - Experimentação
• Link de acesso: https://repositorio.ufu.br/handle/123456789/35093; http://doi.org/10.14393/ufu.di.2022.214

Agriculture is one of the great poles of influence in the world economy. Factors such as competitiveness, cost reduction, increased product quality, profitability and sustainability are the most targeted variables among producers and industries. Thus, several studies have brought more modern techniques that accelerate productivity and quality processes through large-scale phenotyping from digital aerial images. This way, remote sensing proves to be a very important tool for decision making. It has a series of digital processing that serve as a basis for several studies in agriculture. However, there are few studies that associate these aerial image data with field agronomic variables in vegetables. Thus, this study aimed to show the potential of vegetation indices from aerial images in monitoring the agronomic performance of three different crops: lettuce, potato and watermelon. Through basic statistical analysis, digital image processing and multivariate statistics, the vegetation indices NGRDI, NDVI, GLI, TGI and SAVI used in this study were effective in monitoring the agronomic performance of the crops studied. It was concluded that vegetation indices have the potential to correlate with several variables field responses and that it was possible to monitor the agronomic performance of lettuce, potato and watermelon in this study.