Seleção de genitores e híbridos de Panicum maximum pela abordagem de modelos mistos

Detalhes bibliográficos
Ano de defesa: 2016
Autor(a) principal: Ematne, Hugo Junqueira
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
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
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: http://repositorio.ufla.br/jspui/handle/1/11696
Resumo: In the present work aimed to: i) to estimate breeding values of sexual progenitors of P. maximum based on their assessment in clonal test and by means of progeny test, addressing models with and without parent information. ii) to evaluate and select sexual hybrid of P. maximum considering and not the modeling of the progenitors assessment information in a clonal test and to obtain estimates of genetic gains with selection as the main character target for improvement. For this work, it was used 20 sexual progenitors of P. maximum, and these plants selected by the breeding program of Embrapa Beef Cattle. These plants were used in a polycross field to obtain progenies of half-sibs (PHS) of each plant. Twenty sexual progenitors in a clonal test in complete block design with two repetitions and PHS in complete block design with six repetitions, using as control Mombaça and Tanzânia cultivars in both experiments were assessed. It was evaluated agronomic characteristics under four cuts and nutritional value in two cuts. The statistics-genetic analyzes were performed by the approach of mixed models under different models. In both experiments the selective accuracies indicated good experimental reliability. In the article "i" model contemplating the parent information on ploidy of the species (tetraploid) provided the best estimates regarding to genetic parameters and estimates gains with selection of the 10 best progenitors. However, the three approaches used, have a high coincidence rate in the selection of the best progenitors. In the article "ii" the segregating population (PHS) showed genetic variability to be exploited, and the selection of the 30 best hybrids provided high genetic gains for agronomic characteristics.