Fenotipagem de alto desempenho para monitorar a taxa de crescimento e determinar o ponto de colheita em alface vermelha

Detalhes bibliográficos
Ano de defesa: 2022
Autor(a) principal: Espíndola, Gustavo Mendes
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
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
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: https://repositorio.ufu.br/handle/123456789/34721
http://doi.org/10.14393/ufu.di.2022.186
Resumo: Lettuce (Lactuca sativa L.) is a crop of great socioeconomic importance. It has a very short lifecycle; hence, following its growth is challenging. Brazil has several commercial plantations to supply large fast-food chains. These producers monitor the growth rate daily, in person, after transplantation. Owing to the fast growth of the plant and the large sizes of the plantations, the producers face significant food losses and waste. Therefore, the objective of this study was to monitor the growth and determine the harvest point of red lettuce based on different vegetation indices. Images obtained using an unmanned aerial vehicle were used to calculate the diameter of the plant, leaf area, and vegetation indices (BI, GLI, HUE, SCI, and SI). Agronomic parameters (plant diameter, stem diameter, green mass, number of leaves, and leaf temperature) were also measured in the field to validate the effectiveness of the different vegetation indices. Measurements were performed on 30 red lettuce genotypes. The means of the parameters were compared using the Scott-Knott test (p ≤ 0.05). The genetic dissimilarity was represented using a dendrogram obtained by the UPGMA hierarchical method. Pearson’s correlation was used to validate the consistency between the data obtained from images. The evaluated genotypes presented high genetic variability. The vegetation indices (BI, GLI, HUE, SCI, and SI) highly correlated with the plant diameter and leaf area obtained from the images. High-throughput phenotyping could be used to monitor the growth and determine the harvest point of different red lettuce genotypes, and is hence an excellent tool for producers.