Selection indices for agronomic traits in segregating populations of soybean

• Autor(a) principal: Bizari, Eduardo Henrique [UNESP]
• Data de Publicação: 2017
• Outros Autores: Val, Bruno Henrique Pedroso [UNESP], Pereira, Elise de Matos [UNESP], Mauro, Antonio Orlando Di [UNESP], Unêda-Trevisoli, Sandra Helena [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.5935/1806-6690.20170012; http://hdl.handle.net/11449/174091
• topic: Genetic improvement; Glycine max; Selection criteria

In genetic improvement of the soybean crop, the selection process is complex and greatly influenced by the environment. One of the alternatives for facilitating this process is the use of selection indices, making it possible to select desirable genotypes for the early generations of breeding programs. The aim of this study was to compare different selection indices in segregating populations of soybean, indicating methods which are superior in various situations, and proposing economic weightings in order to obtain higher gains. Direct and indirect selection criteria were used, together with the classic Smith-Hazel index, an index based on the sum ranks of Mulamba and Mock, a Williams base index, an index based on the desired gains of Pesek and Baker, and a genotype-ideotype distance index. The genetic material consisted of seven F5 generation soybean populations, giving a total of 386 progeny, conducted in a Federer augmented-block design, with the following characteristics being evaluated: Number of days to maturity, plant height at maturity, insertion height of the first pod, lodging, agronomic value, number of pods per plant, oil content and grain yield. According to the results, the classic index and base index showed the smallest variations in gains in the different situations and economic weightings under study. The index based on the sum of ranks using agronomic value and grain productivity as the main characteristics with an economic weighting of one, gave the most favourable gains under the conditions of this study.