Table 5 Estimates of variance components and genetic parameters for birth weight (the best model is shown in bold).

From: Improvement in genetic evaluation of quantitative traits in sheep by enriching genetic model with dominance effects

Model

\(\:{\sigma\:}_{a}^{2}\)

\(\:{\sigma\:}_{d}^{2}\)

\(\:{\sigma\:}_{c}^{2}\)

\(\:{\sigma\:}_{m}^{2}\)

\(\:{\sigma\:}_{a.m}\)

\(\:{\sigma\:}_{e}^{2}\)

\(\:{\sigma\:}_{p}^{2}\)

\(\:{h}_{a}^{2}\)

\(\:{h}_{d}^{2}\)

\(\:{h}_{c}^{2}\)

\(\:{h}_{m}^{2}\)

e2

ra, m

AIC

1

0.196

    

0.348

0.544

0.36 ± 0.03

   

0.64 ± 0.03

 

1068.69

2

0.194

0.191

   

0.162

0.548

0.35 ± 0.03

0.35 ± 0.06

  

0.30 ± 0.07

 

1054.69

3

0.052

 

0.112

  

0.347

0.511

0.10 ± 0.02

   

0.68 ± 0.02

 

911.59

4

0.050

0.147

0.111

  

0.205

0.514

0.10 ± 0.03

0.29 ± 0.06

  

0.39 ± 0.06

 

901.60

5

0.023

  

0.155

 

0.368

0.547

0.04 ± 0.01

 

0.22 ± 0.02

0.28 ± 0.02

0.67 ± 0.02

 

914.01

6

0.022

0.159

 

0.153

 

0.214

0.550

0.04 ± 0.01

0.29 ± 0.06

0.22 ± 0.02

0.28 ± 0.02

0.39 ± 0.06

 

902.16

7

0.021

  

0.138

0.035

0.370

0.549

0.04 ± 0.01

  

0.25 ± 0.02

0.67 ± 0.02

0.35 ± 0.19

913.63

8

0.020

0.160

 

0.136

0.019

0.215

0.551

0.04 ± 0.02

0.29 ± 0.06

 

0.24 ± 0.02

0.39 ± 0.05

0.37 ± 0.19

901.70

9

0.027

 

0.068

0.061

 

0.359

0.517

0.05 ± 0.02

 

0.13 ± 0.02

0.11 ± 0.02

0.69 ± 0.02

 

894.67

10

0.026

0.151

0.066

0.062

 

0.213

0.520

0.05 ± 0.01

0.30 ± 0.06

0.13 ± 0.02

0.12 ± 0.02

0.41 ± 0.06

 

883.96

11

0.024

 

0.067

0.048

0.017

0.361

0.519

0.05 ± 0.01

 

0.13 ± 0.02

0.09 ± 0.02

0.70 ± 0.01

0.49 ± 0.22

893.42

12

0.023

0.152

0.065

0.049

0.017

0.214

0.514

0.05 ± 0.01

0.29 ± 0.06

0.13 ± 0.02

0.09 ± 0.02

0.41 ± 0.03

0.50 ± 0.22

882.64

  1. \(\:{\sigma\:}_{a}^{2}\)= additive genetic variance;\(\:\:{\sigma\:}_{d}^{2}\)= dominance genetic variance;\(\:\:{\sigma\:}_{c}^{2}\)= maternal permanent environmental variance;\(\:\:{\sigma\:}_{m}^{2}\)= maternal genetic variance; \(\:{\sigma\:}_{a.m}\)= direct-maternal additive genetic covariance; \(\:{\sigma\:}_{e}^{2}\)= residual variance; \(\:{\sigma\:}_{p}^{2}\)= phenotypic variance;\(\:\:{h}_{a}^{2}\)= additive heritability; \(\:{h}_{d}^{2}\)= dominance heritability; \(\:\:{h}_{c}^{2}\)= maternal permanent environmental effect, \(\:{h}_{m}^{2}\)= maternal heritability; e2: ratio of residual variance to phenotypic variance; ra, m= direct-maternal additive genetic correlation; AIC= Akaike’s information criterion.