Seleção simultânea para produtividade, precocidade e alto teor de proteína em soja

• Ano de defesa: 2021
• Autor(a) principal: Pessoni, Laurenia Oliveira
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Lavras; Programa de Pós-Graduação em Genética e Melhoramento de Plantas; UFLA; brasil; Departamento de Biologia
• Palavras-chave em Português: Soja - Melhoramento genético; Seleção de genótipos; Soja - Produtividade; Soja - Qualidade; Soybean - Genetic improvement; Genotype selection; Soybean - Productivity; Soybean - Quality; Melhoramento Vegetal
• Link de acesso: http://repositorio.ufla.br/jspui/handle/1/48197

The high yields of soybean cultivars are attributed to crop management and genetic improvementof the crop. In the latter case, several traits are considered in order to select genotypes and recommend cultivars. Some have been widely studied by researchers and soybean breeders, such as precocity and grain yield. The study of the association between traits allows a better understanding of the relationships between them, expanding the possibilities of success with the selection. Therefore, in order to meet the current demand of the market, farmers and industry for genotypes that show yield, precocity and grain quality, the objective was to select early, high yielding soybean progenies with high protein content in the grains. The experiments were carried out in the municipalities of Lavras and Ijaci, State of Minas Gerais, in the crop season 2018/19 and 2019/20. Segregating progenies obtained from F2 populations were used. The F2:3 and F2:4 progenies were evaluated in an incomplete block design (DBI) in 13x13 single lattice and 9x10 triple rectangular lattice, respectively. In F2:3 the plots consisted of 1 line of 2.0 meters spaced 0.6m apart and in F2:4 two lines of 3.0 meters spaced 0.6m apart. Both sowings were carried out manually at the end of October. The traits evaluated were: absolute maturation, grain yield and grain protein content. Percent protein content analysis were performed using the Near Infrared Spectroscopy technique with readings in triplicate. Data were analyzed using the R software, using mixed model approach. The results obtained allow us to infer that there is genetic variability among the progenies for absolute maturation and yield, and that the association between the evaluated traits was of low magnitude. It is possible to obtain early and high yielding genotypes.