Single-trait bayesian analysis of some growth traits in japanese quail

Karaman, Emre; Fırat, Mehmet Ziya; Narinç, Doğan

doi:10.1590/1516-635x160251-56

Cited by 5 publications

(5 citation statements)

References 30 publications

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“…The same group of researchers estimated in another study a heritability value of 0.36 for BW at 35 days in Japanese quail (Narinc et al, 2014). Karaman et al (2014) reported a lesser heritability estimate for BW at 42 days of age (0.48) than what was found in the present study for BW at 35 days of age. These values were lesser when compared with those estimated by RRM in the present study and greater than the estimated by the multi-trait model.…”

Section: Heritabilitysupporting

confidence: 47%

“…In this scenario, the genetic material of less productive potential becomes a problem when selection is focused on productive traits. Thus, when selection of economicinterest traits is based on a directed breeding program, changes on growth caused by the selection itself are more accurate and precise (Khaldari et al, 2010;Karaman et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

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Genetic evaluation and selection response for growth in meat-type quail through random regression models using B-spline functions and Legendre polynomials

Mota

Martins²,

Littiere

et al. 2018

Animal

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The objective was to estimate (co)variance functions using random regression models (RRM) with Legendre polynomials, B-spline function and multi-trait models aimed at evaluating genetic parameters of growth traits in meat-type quail. A database containing the complete pedigree information of 7000 meat-type quail was utilized. The models included the fixed effects of contemporary group and generation. Direct additive genetic and permanent environmental effects, considered as random, were modeled using B-spline functions considering quadratic and cubic polynomials for each individual segment, and Legendre polynomials for age. Residual variances were grouped in four age classes. Direct additive genetic and permanent environmental effects were modeled using 2 to 4 segments and were modeled by Legendre polynomial with orders of fit ranging from 2 to 4. The model with quadratic B-spline adjustment, using four segments for direct additive genetic and permanent environmental effects, was the most appropriate and parsimonious to describe the covariance structure of the data. The RRM using Legendre polynomials presented an underestimation of the residual variance. Lesser heritability estimates were observed for multi-trait models in comparison with RRM for the evaluated ages. In general, the genetic correlations between measures of BW from hatching to 35 days of age decreased as the range between the evaluated ages increased. Genetic trend for BW was positive and significant along the selection generations. The genetic response to selection for BW in the evaluated ages presented greater values for RRM compared with multi-trait models. In summary, RRM using B-spline functions with four residual variance classes and segments were the best fit for genetic evaluation of growth traits in meat-type quail. In conclusion, RRM should be considered in genetic evaluation of breeding programs.

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Section: Heritabilitysupporting

confidence: 47%

Section: Introductionmentioning

confidence: 99%

Genetic evaluation and selection response for growth in meat-type quail through random regression models using B-spline functions and Legendre polynomials

Mota

Martins²,

Littiere

et al. 2018

Animal

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“…However, the frequentist technique is limited to obtaining point estimates of variance (Xie & Singh, 2013), while Bayesian has a distribution for all parameters (a posteriori distribution). One of the most frequently used frequentist methods is based on ANOVA, but it can present a negative estimate of the components of variance (Karaman, Firat, & Narinc, 2014), which is not of interest to the breeder and does not occur in Bayesian inference.…”

Section: Discussionmentioning

confidence: 99%

Study of repeatability and phenotypical stabilization in kale using frequentist, Bayesian and bootstrap resampling approaches

et al. 2019

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The aim of this study was to obtain information for the genetic improvement of kale through repeatability and phenotypic stabilization studies and to compare methodologies that represent the reliability of the estimated parameters. Thirty-three half-sib progenies were evaluated in a randomized block design with three replicates and six plants per plot. Eight harvests were evaluated in terms of the yield of fresh leaves, number of shoots, number of leaves and average mass of leaves. Then, a phenotypic repeatability and stabilization study was performed, estimating the genetic parameters σ2a, σ²g, σ²e, and the coefficient of environmental variation and repeatability using the frequentist and Bayesian methodologies. To evaluate the reliability of these estimates, intervals were obtained using the frequentist, Bayesian and bootstrap methods. It was verified that the reliable selection of progenies of half-sib of kale can be achieved in four harvests that were realized between 95 and 170 days after planting. It was observed that the frequentist and Bayesian methodologies are better suited to obtain reliable estimates of the genetic parameters evaluated, as the last one provided smaller amplitudes for the obtained intervals. The bootstrap methodologies are not recommended for phenotypic repeatability and stabilization studies in kale.

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“…The problem with ANOVA is that it requires balance data for it to work and most often it can give negative estimates of variance Keywords: Autocorrelations, egg production, genetic correlations, heritability, strain crosses. components (Karaman et al, 2014). Because data that are generated in animal breeding experiments are often unbalanced and come from different type of relationship, maximum likelihood (ML) and restricted maximum likelihood (REML) are often used to estimate variance components.…”

Section: Introductionmentioning

confidence: 99%

Genetic parameters for egg production traits in crosses between local and exotic chickens estimated by Bayesian inference

Udeh

Omeje

2021

NJAP

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Estimates of genetic parameters for economic traits are important to enable the breeder estimate the breeding value of individuals available for selection. Thus, this study was carried out to estimate genetic parameters namely heritability and genetic correlations among egg production traits in two strain crosses using bivariate animal model in Bayesian (MCMC) method. The egg production data were obtained from four generations which comprised the base population of two commercial egg strains and the local chicken, the inbred population derived from the base population, the F1 crossbred population obtained from the crossing of the local and exotic inbred chickens and the backcross population obtained from the backcrossing of the crossbred to their parents. A total number of 1,138 daughters of 62 sires and 620 dams were used for the study. The autocorrelations among samples in the MCMC chain were less than 0.1 for all lag values indicating that all samples of the posterior distribution were independent. The estimated heritability for age at first egg, body weight at first egg, hen day egg number, weight of first egg, egg weight at thirty week and egg weight at forty week were 0.62, 0.48, 0.47, 0.53, 0.54 and 0.56 for strain 1 crosses and 0.43, 0.48, 0.49, 0.52, 0.52 and 0.53 for strain 2 crosses. The corresponding highest posterior density interval ranged from 0.22 to 0.91 for strain 1 crosses and 0.07 to 0.83 for strain 2 crosses. The genetic correlations among egg production traits ranged from 0.06 to 1.97 in strain 1 and 0.06 to 2.59 in strain 2 crosses. The estimates were within the range reported in literature for egg production traits in chicken and imply that appreciable amount of additive genes exist in the strain crosses which could be used for the selection of superior birds. The magnitude of genetic correlations implies that selection of one trait could lead to correlated response to the other traits.

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Single-trait bayesian analysis of some growth traits in japanese quail

Cited by 5 publications

References 30 publications

Genetic evaluation and selection response for growth in meat-type quail through random regression models using B-spline functions and Legendre polynomials

Genetic evaluation and selection response for growth in meat-type quail through random regression models using B-spline functions and Legendre polynomials

Study of repeatability and phenotypical stabilization in kale using frequentist, Bayesian and bootstrap resampling approaches

Genetic parameters for egg production traits in crosses between local and exotic chickens estimated by Bayesian inference

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