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Genetic parameters and selection gain in tropical wheat populations via Bayesian inference
by
Barros, Willian Silva
, Azevedo, Camila Ferreira
, Borem, Aluízio
, Mezzmo, Henrique Caletti
, Casagrande, Cleiton Renato
, Nardino, Maicon
in
AGRONOMY
/ Algorithms
/ Bayesian analysis
/ Credibility
/ Crop yield
/ Cultivars
/ Design of experiments
/ early selection,TriticumaestivumL
/ Estimates
/ Genetic improvement
/ Heritability
/ information criterion
/ Parameters
/ Plant breeding
/ Population genetics
/ Populations
/ Probability distribution
/ Seeds
/ Software
/ Statistical inference
/ Wheat
/ wheat breeding
2023
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Genetic parameters and selection gain in tropical wheat populations via Bayesian inference
by
Barros, Willian Silva
, Azevedo, Camila Ferreira
, Borem, Aluízio
, Mezzmo, Henrique Caletti
, Casagrande, Cleiton Renato
, Nardino, Maicon
in
AGRONOMY
/ Algorithms
/ Bayesian analysis
/ Credibility
/ Crop yield
/ Cultivars
/ Design of experiments
/ early selection,TriticumaestivumL
/ Estimates
/ Genetic improvement
/ Heritability
/ information criterion
/ Parameters
/ Plant breeding
/ Population genetics
/ Populations
/ Probability distribution
/ Seeds
/ Software
/ Statistical inference
/ Wheat
/ wheat breeding
2023
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Do you wish to request the book?
Genetic parameters and selection gain in tropical wheat populations via Bayesian inference
by
Barros, Willian Silva
, Azevedo, Camila Ferreira
, Borem, Aluízio
, Mezzmo, Henrique Caletti
, Casagrande, Cleiton Renato
, Nardino, Maicon
in
AGRONOMY
/ Algorithms
/ Bayesian analysis
/ Credibility
/ Crop yield
/ Cultivars
/ Design of experiments
/ early selection,TriticumaestivumL
/ Estimates
/ Genetic improvement
/ Heritability
/ information criterion
/ Parameters
/ Plant breeding
/ Population genetics
/ Populations
/ Probability distribution
/ Seeds
/ Software
/ Statistical inference
/ Wheat
/ wheat breeding
2023
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Genetic parameters and selection gain in tropical wheat populations via Bayesian inference
Journal Article
Genetic parameters and selection gain in tropical wheat populations via Bayesian inference
2023
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Overview
The development process of a new wheat cultivar requires time between obtaining the base population and selecting the most promising line. Estimating genetic parameters more accurately in early generations with a view to anticipating selection means important advances for wheat breeding programs. Thus, the present study estimated the genetic parameters of F2 populations of tropical wheat and the genetic gain from selection via the Bayesian approach. To this end, the authors assessed the grain yield per plot of 34 F2 populations of tropical wheat. The Bayesian approach provided an adequate fit to the model, estimating genetic parameters within the parametric space. Heritability (h2) was 0.51. Among those selected, 11 F2 populations performed better than the control cultivars, with genetic gain of 7.80%. The following populations were the most promising: TbioSossego/CD 1303, CD 1303/TbioPonteiro, BRS 254/CD 1303, Tbio Duque/Tbio Aton, and Tbio Aton/CD 1303. Bayesian inference can be used to significantly improve tropical wheat breeding programs. RESUMO: O processo de desenvolvimento de uma nova cultivar de trigo requer tempo entre a obtenção da população base e a seleção da linhagem mais promissora. Estimar parâmetros genéticos com mais precisão nas primeiras gerações com vistas a antecipar a seleção significa avanços importantes para os programas de melhoramento de trigo. Assim, o presente estudo estima os parâmetros genéticos de populações F2 de trigo tropical e o ganho genético da seleção via abordagem Bayesiana. Para tanto, os autores avaliaram a produtividade de grãos por parcela de 34 populações F2 de trigo tropical. A abordagem Bayesiana proporcionou um ajuste adequado ao modelo, estimando parâmetros genéticos dentro do espaço paramétrico. A herdabilidade (h2) foi de 0,51. Dentre as selecionadas, 11 populações F2 obtiveram desempenho superior às cultivares controle, com ganho genético de seleção de 7,80%. As seguintes populações foram as mais promissoras: Tbio Sossego/CD 1303, CD 1303/Tbio Ponteiro, BRS 254/CD 1303, Tbio Duque/Tbio Aton e Tbio Aton/CD 1303. A inferência Bayesiana pode ser usada para melhorar significativamente programas de melhoramento de trigo tropical.
Publisher
Universidade Federal de Santa Maria Centro de Ciencias Rurais,Universidade Federal de Santa Maria
Subject
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