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Genetic parameters and selection strategies in maize population UFVM100(HS)C2
Letícia Prada de Miranda
Universidade Federal de Viçosa
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Create a topicThe recurrent selection is a successfully breeding scheme used by maize breeders for increasing favorable alleles of quantitative traits at broad-based populations targeting the development of new varieties or even breeding populations. Our two objectives were to: i) estimate genetic parameters in the maize population UFVM100(HS)C2, and ii) predict the genetic gains by recombining the selected progenies. For this, 200 S1 progenies of population UFVM100(HS)C2 were evaluated across two locals, at Horta Nova and Coimbra (MG), during 2020/2021 season. In both locals, the trial was laid out in an alpha-lattice incomplete design with two replications. Each plot was a single 5 m row, with rows spaced 0.80 m apart. We evaluated five traits: days to pollen (DTP) and to silking (DTS), plant height (PH, cm), ear height (EH, cm), and grain yield (GY, kg ha-1). A mixed model approach was used to estimate variance components, and genetic gains of the 20 progenies for recombining was predicted based on GY per se and multiple traits using a selection index values across two locals. Our results showed that there was large phenotypic variation for all traits at each location and across locations. Variance components due to progenies were highly significant (P<0.01) based on the likelihood ratio test for all traits at each local and across locals. Variance components due to progenies x locals were significant for almost all traits, except for DTP. The estimates of broad-sense heritability were high and ranged from 0.63 (GY) to 0.78 (DTP). The selection based on GY per se increased GY by 23.41%, and also PH and EH by 4.65% and 6.55%, respectively, with no change for flowering time. In contrast, the selection based on index values that included GY and DTS reduced days to flowering (around 3%) and increased GY by almost 20%, with no changes in plant height. We concluded that there is genetic variability in the maize population UFVM100(HS)C2 and that the selection based on index values is the best breeding strategy to improve UFVM100(HS)C2 for increased yield and reduce cycle.
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