Population parameters and selection of kale genotypes using Bayesian inference in a multi-trait linear model

Population parameters and selection of kale genotypes using Bayesian inference in a multi-trait linear model

Variance components must be obtained to estimate genetic parameters and predict breeding values. This information can be obtained through Bayesian inference. When multiple traits are evaluated, Bayesian inference can be used in multi-trait models. The objective of this study was to obtain estimates...

Full description

Saved in:
Bibliographic Details
Published in:Acta scientiarum. Agronomy Vol. 39; no. 1; pp. 25 - 31
Main Authors: Azevedo, Alcinei Mistico, Andrade júnior, Valter Carvalho de, Santos, Albertir Aparecido dos, Sousa Júnior, Aderbal Soares de, Oliveira, Altino Júnior Mendes, Ferreira, Marcos Aurélio Miranda
Format: Journal Article
Language:English
Published: Maringa Editora da Universidade Estadual de Maringá - EDUEM 01-01-2017
Eduem (Editora da Universidade Estadual de Maringá)
Subjects:
AGRONOMY
Bayesian analysis
Brassica oleracea L. var. acephala DC
correlations
crop breeding
Genetic engineering
genetic parameters
Genotype & phenotype
Kale
Selective breeding
statistical modeling
Brassica oleracea L. var. acephala DC
genetic parameters
correlações
statistical modeling
melhoramento genético
modelagem estatística
correlations
parâmetros genéticos
crop breeding
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Variance components must be obtained to estimate genetic parameters and predict breeding values. This information can be obtained through Bayesian inference. When multiple traits are evaluated, Bayesian inference can be used in multi-trait models. The objective of this study was to obtain estimates of genetic parameters, gains with selection, and genetic correlations among traits. Likewise, we aim to predict the genetic values and select the best kale genotypes using the Bayesian approach in a multi-trait linear model. The following traits were evaluated: stem diameter, plant height, number of shoots, number of marketable leaves and fresh weight of leaves using Bayesian inference in 22 kale genotypes. The experiment consisted of a randomized block design with three replications and four plants per plot. Genetic effects predominated over environmental effects. The highest correlation estimates were found between the fresh weight of leaves and stem diameter and between the plant height and number of marketable leaves. The following commercial cultivars and genotypes are recommended for cultivation and to integrate into breeding programs: UFLA 11, UFLA 5, UFLA 6, UFVJM 3 and UFVJM 19. The estimates of the gain with selection indicate the potential for improvement of the studied population.
ISSN:1679-9275
1807-8621
1807-8621
DOI:10.4025/actasciagron.v39i1.30856