Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/33958
Title: Estratégias de seleção no melhoramento genético da soja
Other Titles: Selection strategies in soybean breeding
Authors: Bruzi, Adriano Teodoro
Nogueira, Ana Paula Oliveira
Ferreira, Daniel Furtado
Keywords: Glycine max L. Merril
Modelos mistos
Mérito da população
Índice multigerações
Mixed models
Population effect
Multigeneration index
Issue Date: 29-Apr-2019
Publisher: Universidade Federal de Lavras
Citation: MARQUES, F. S. Estratégias de seleção no melhoramento genético da soja. 2019. 46 p. Dissertação (Mestrado em Agronomia/Fitotecnia)–Universidade Federal de Lavras, Lavras, 2019.
Abstract: Soybean progenies selection process is often conducted by evaluating the agronomic performance of progenies of several populations in different environments during two or more generations. Studies have sought to improve the selection methods in autogamous plants by the application of the mixed model approach, in which the use of BLUP associated with the merit of the population and data from multiple generations has made the selection process more efficient. Thus, the objective of this study was to compare soybean progeny selection strategies and to study the implications of different progeny selection strategies on the ranking of superior soybean genotypes. The F3:4 and F3:5 progenies from four distinct populations were evaluated for absolute maturity and grain yield. The F3:4 progenies were evaluated in Lavras and Itutinga, during the crop year of 2016/2017. Plots of a 1.5 m row with two replications were taken in a 12 x 12 simple lattice design (136 progenies + 8 controls). The F3:5 Progenies were evaluated in Lavras, Itutinga and Ijaci during the crop year of 2017/2018. Each plot consisted of one row of 3.0 m with three replications, in an 8 x 8 triple lattice design (56 progenies + 8 controls). The data were analyzed using mixed models approach through the following strategies: ignoring and considering the effect of populations in each generation, and considering the multigeneration index. The genetic and phenotypic parameters were estimated for each analysis. Genetic gains from selection, Spearman correlation and coincidence index were used to verify the efficiency of the models with and without the effect of the population and with the data of multiple generations. It was observed that there is alteration in the ranking and coincidence of the selected progenies in each generation by ignoring and considering the merit of the population. The multigeneration index is a promising strategy for selection of soybean progenies which associate early maturity and high grain yield.
URI: http://repositorio.ufla.br/jspui/handle/1/33958
Appears in Collections:Agronomia/Fitotecnia - Mestrado (Dissertações)

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