scholarly journals Estimation of Genetic Parameters for Calving Ease by Heifers and Cows Using Multi-trait Threshold Animal Models with Bayesian Approach

2002 ◽  
Vol 15 (8) ◽  
pp. 1085-1090
Author(s):  
D. H. Lee
Keyword(s):  
Animal Models ◽  
Bayesian Approach ◽  
Genetic Parameters ◽  
Calving Ease ◽  
Estimation Of Genetic Parameters

scholarly journals Estimation of genetic parameters and trends for energy-corrected 305-d milk yield in Iranian Holsteins

2012 ◽  
Vol 55 (5) ◽  
pp. 420-426
Author(s):  
N. G. Hossein-Zadeh
Keyword(s):  
Animal Models ◽  
Milk Yield ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Physiological Mechanism ◽  
Animal Breeding ◽  
Dairy Herds ◽  
Breeding Values ◽  
Estimation Of Genetic Parameters ◽  
Genetic Trends

Abstract. Calving records from the Animal Breeding Centre of Iran collected from January 1995 to December 2007 and comprising 217973 calving events of Holsteins from 704 dairy herds were analysed using univariate and bivariate linear animal models to estimate heritabilities and genetic correlations for energy-corrected 305-d milk yield (ECM) in the first three lactations of Holstein cows. Genetic trends were obtained by regressing yearly mean estimates of breeding values on calving year. Average ECM increased from parity 1 through parity 3. Estimates of heritabilities were from 0.14 to 0.21 for ECM and decreased over the parities. The greatest genetic correlations were between ECM2 and ECM3 (0.96), and the greatest phenotypic correlations were between ECM1 and ECM2 (0.57) and ECM2 and ECM3 (0.57). The high and positive genetic correlations between ECM traits at different lactations are evidence for common genetic and physiological mechanism controlling these traits. There were positive and increasing phenotypic and genetic trends for ECM over the years (P<0.001). Higher heritability of the ECM in the first parity along with the high genetic correlations between first-lactation ECM with these traits in other lactations shows that higher potential exists for selecting animals for ECM based on their first parity records.

Estimation of genetic parameters for lambing ease, birthweight and gestation length in Australian sheep

2016 ◽  
Vol 56 (5) ◽  
pp. 934 ◽  
Author(s):  
L. Li ◽  
D. J. Brown
Keyword(s):  
Animal Models ◽  
Environmental Effects ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Gestation Length ◽  
Phenotypic Variance ◽  
Full Dataset ◽  
Australian Sheep ◽  
Using Data ◽  
Estimation Of Genetic Parameters

This study presents estimates of genetic parameters for lambing ease (LE), birthweight (BW) and gestation length (GL) in Australian terminal sire sheep breeds using data from the Sheep Genetics LAMBPLAN database. LE was scored on lambs on a 1–5 scale, with 1 being no assistance and 5 being other such as special veterinary assistance. The full dataset consisted of 43 448 records on LE and its two subsets (the single and twin subsets) based on the birth type of the litter were analysed. Four models with different combinations of random effects consisting of direct genetic, maternal genetic and maternal permanent environmental effects were compared. All traits were analysed using linear animal models and linear sire models with LE further analysed by threshold sire models for all datasets to evaluate the influence of datasets and models on the estimation of genetic parameters. The results showed that multiple-born lambs had shorter GL, less BW and less lambing difficulty than single-born lambs. Lambing difficulty decreased with the increase of dam age from 1.5 to 4.5 years, and then increased afterwards. Genetic parameters using linear animal models were similar to those using linear sire models for all traits. Phenotypic variance and direct heritability were higher for single-born lambs compared with twin-born lambs. No significant maternal permanent environmental effect was detected for LE. Based on results using linear animal models with the full dataset, the direct heritabilities were 0.06 ± 0.01, 0.15 ± 0.01 and 0.52 ± 0.02, the maternal heritabilities were 0.03 ± 0.01, 0.15 ± 0.01 and 0.13 ± 0.02 for LE, BW and GL, respectively. The proportions of maternal permanent environmental effects to the total variances were 0.13 ± 0.01 for BW. Low to moderate direct genetic correlations of 0.31 ± 0.09 (LE and BW), 0.24 ± 0.11 (LE and GL) and 0.08 ± 0.08 (BW and GL) were estimated using tri-variate analysis from the full dataset, indicating the trend that lambs with greater BW and longer GL would result in more lambing difficulty.

scholarly journals Determination of the best model for estimation of genetic parameters on the Fars native chicken traits using Bayesian and REML methods

Genetika ◽  
2018 ◽  
Vol 50 (2) ◽  
pp. 431-447
Author(s):  
Ali Mohammadi ◽  
Yousef Naderi ◽  
Reza Nabavi ◽  
Fatemeh Jafari
Keyword(s):  
Body Weight ◽  
Bayesian Approach ◽  
Bayesian Method ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Correlation Coefficients ◽  
Native Chicken ◽  
Egg Number ◽  
Estimation Of Genetic Parameters

This study was conducted to determine the best model for genetic parameter estimation on the Fars native chicken traits using Bayesian and REML Methods. Studied traits were body weight at first day (BW1), body weight at eighth weeks (BW8), body weight at 12th weeks (BW12), age at sexual maturity (ASM), egg number production (EGP) and mean egg weight during 28th ,30th and 32nd week ages (EGW) involving three generations 17, 18 and 19 during the years 2010 to 2012. Genetic parameters were estimated with REML method using WOMBAT software and with Bayesian approach using MTGSAM software. Based on AIC and DIC criteria, the most appropriate model was determined. Estimations of direct additive heritabilities for BW1, BW8, BW12, ASM, EGP and EGW by the best models using REML method were 0.31, 0.32, 0.29, 0.45, 0.24 and 0.22 and by Bayesian method were 0.36, 0.33, 0.30, 0.48, 0.26 and 0.25, respectively. The genetic correlation coefficients ranged from -0.709 between EGP and ASM to 0.844 between BW8 and BW12 (by Bayesian method) and ranged from -0.724 between ASM and EGP to 0.894 between BW12 and BW8 (by REML method). Generally, based on the employed criteria, the 1st and 2nd models can be suggested for analysis of body weight traits (BW1, BW8 and BW12), whereas for other traits (ASM, EGP and EGW), 1st, 5th, 4th and 6th models seems to be suitable for estimation of genetic parameters of the Fars Native fowls traits using Bayesian and REML Methods. The Bayesian approach recommended for estimation of genetic parameters on the Fars native chicken traits because this method used the prior distribution in the calculation process.

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