Modelos multivariados na caracterização e seleção de genótipos superiores de aveia preta (Avena strigosa S.)

• Ano de defesa: 2022
• Autor(a) principal: Klein, Luís Antônio
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• dARK ID: ark:/26339/001300000p5pg
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Agronomia; UFSM; Programa de Pós-Graduação em Agronomia - Agricultura e Ambiente; UFSM Frederico Westphalen
• Palavras-chave em Português: Parâmetros genéticos; Seleção simultânea; Adaptabilidade; Estabilidade; Genetic parameters; Simultaneous selection; Adaptability; Stability; CNPQ::CIENCIAS AGRARIAS::AGRONOMIA
• Link de acesso: http://repositorio.ufsm.br/handle/1/24330

Black oat (Avena strigosa S.) is one of the most cultivated winter cereals in Rio Grande do Sul due to its rapid growth, rusticity, high forage yield and easy seeding. Despite the extensive cultivated areas, few breeding programs have developed new cultivars of black oat. In this sense, the objective of this work was to select and characterize possible genotypes with potential for the development of new cultivars of black oat, with characteristics such as low size, early cycle and high productivity of dry mass and seeds, using multivariate models, in addition to testing the adaptability and stability of these genotypes. The experiment was conducted in the experimental area of the Laboratory for Genetic Improvement and Plant Production, at the Federal University of Santa Maria, campus of Frederico Westphalen/RS, in the years 2018, 2019, 2020 and 2021, in addition to the experimental area of the Improvement Laboratory Genetic from Universidade Tecnológica Federal do Paraná, in Pato Branco/PR, in 2020. The experiment was carried out in a randomized block design, with three replications. Some black oat genotypes from the university's genetic improvement program were evaluated, with the addition of control cultivars, namely IAPAR 61, IPR Cabocla, UPFA 21 - Moreninha, FPS Agro Esteio and BRS 139. The characteristics evaluated were: a) days from emergence to flowering ( DEF, days); b) plant height (APL, cm); c) number of tillers per plant (NAP, n°); d) panicle mass (MDP, g); e) panicle grain mass (MGP, g); f) plant mass (MPL, g); g) total green mass (MVT, kg ha-1); h) total dry mass (MST, kg ha-1); i) seed yield (PDS, kg ha-1). From the information obtained, the genotypes were submitted to analyzes to determine the components of variance and genetic parameters, prediction of genetic values, analysis of genetic divergence, simultaneous selection using the MGIDI index and analysis of adaptability and stability using the GGE model. The lines UFSMFW 2-07, UFSMFW 2-05 and UFSMFW 2-01 showed desirable predicted genetic values for the development of early black oat cultivars with high dry mass and seed productivity. The MGIDI selected the genotypes UFSMFW 2-01 and UFSMFW 2-04 as those that are closer to the ideotype when conducted in Frederico Westphalen/RS. When conducted in Pato Branco/PR, the MGIDI selected the genotypes UFSMFW 2-07 and UFSMFW 2-04. MGIDI was efficient in selecting the best black oat genotypes, showing desirable selection gains for most traits. The genotypes UFSMFW 2-01 and UFSMFW 2-07 present as strengths the characteristics related to dry mass productivity and, therefore, have potential in the cultivation for soil cover. The GGE analysis showed the UFSMFW 2-07 genotype as the most productive, but due to instability it can be considered as adapted to the specific environment. The years 2018, 2020 and 2021 showed a certain similarity in the productive averages, being considered representative environments by the GGE Biplot, while 2019 was a favorable year for high productivity and proved to be a discriminating environment.