Please use this identifier to cite or link to this item:
http://repositorio.ufla.br/jspui/handle/1/33240
Title: | Genetic progress in popcorn recurrent selection by a multivariate mixed-model approach |
Other Titles: | Progresso genético na seleção recorrente em milho pipoca via abordagem de modelos mistos multivariado |
Keywords: | Plant breeding Grain yield Popping expansion Melhoramento de plantas Rendimento de grão Capacidade de expansão |
Issue Date: | Apr-2018 |
Publisher: | Editora UFLA |
Citation: | EMATNÉ, H. J. et al. Genetic progress in popcorn recurrent selection by a multivariate mixed-model approach. Ciência e Agrotecnologia, Lavras, v. 42, n. 2, p. 159-167, Mar./Apr. 2018. DOI: 10.1590/1413-70542018422016817. |
Abstract: | Recurrent selection is a viable alternative for popcorn breeding. However, frequent verification of progress attained is required. The aim of this study was to estimate the genetic progress attained for popping expansion (PE) and grain yield (GY) after four cycles of recurrent selection and to compare this progress with the expected progress estimated at the end of each cycle while considering the genetic relationships between the progenies via univariate and multivariate mixed-model approaches. To estimate the genetic parameters and gains from indirect selection, cycles 1, 2, 3, and 4 of a UFLA population were used. To estimate the genetic gains achieved, the following cycles were used: UFLA (original) and cycles 0, 1, 2, 3, and 4, evaluated in three environments. The multivariate approach provided more accurate estimates than did the univariate approach. There was genetic gain for PE in the recurrent selection program. In contrast, gain was not observed for GY using the different estimation strategies. |
URI: | http://repositorio.ufla.br/jspui/handle/1/33240 |
Appears in Collections: | DBI - Artigos publicados em periódicos |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
ARTIGO_Genetic progress in popcorn recurrent selection by a multivariate mixed-model approach.pdf | 531,39 kB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License