Table 7 Estimates of variance components and genetic parameters for average daily gain (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

453.571

    

1871.31

3324.80

0.19 ± 0.03

   

0.81 ± 0.02

 

28034.95

2

450.776

405.77

   

1477.34

2333.23

0.19 ± 0.03

0.17 ± 0.07

  

0.63 ± 0.07

 

28033.12

3

171.902

 

277.506

  

1816.85

2366.26

0.08 ± 0.03

 

0.12 ± 0.01

 

0.80 ± 0.02

 

27996.11

4

168.513

460.623

279.947

  

1368.25

2277.34

0.07 ± 0.02

0.20 ± 0.07

0.12 ± 0.01

 

0.60 ± 0.07

 

27983.08

5

142.859

  

272.98

 

1902.07

2317.91

0.06 ± 0.02

  

0.12 ± 0.02

0.82 ± 0.02

 

28008.67

6

138.053

451.382

 

277.043

 

1462.83

2329.31

0.06 ± 0.02

0.19 ± 0.07

 

0.12 ± 0.02

0.63 ± 0.07

 

28006.10

7

139.954

  

261.990

12.421

1904.76

2318.13

0.06 ± 0.02

  

0.11 ± 0.02

0.82 ± 0.02

0.06 ± 0.21

28009.64

8

134.623

451.539

 

264.600

13.487

1456.39

2329.64

0.06 ± 0.02

0.19 ± 0.07

 

0.11 ± 0.02

0.62 ± 0.07

0.07 ± 0.23

28007.08

9

161.272

 

264.03

18.672

 

1822.19

2266.17

0.07 ± 0.02

 

0.12 ± 0.02

0.01 ± 0.02

0.80 ± 0.02

 

27986.73

10

157.192

461.381

266.395

18.890

 

1373.28

2277.39

0.07 ± 0.02

0.20 ± 0.07

0.12 ± 0.02

0.01 ± 0.02

0.61 ± 0.07

 

27983.85

11

156.485

 

262.610

14.804

7.352

1825.14

2266.40

0.07 ± 0.02

 

0.12 ± 0.01

0.01 ± 0.02

0.80 ± 0.02

0.15 ± 0.69

27987.71

12

150.757

462.83

264.429

13.515

10.135

1375.85

2277.52

0.07 ± 0.02

0.20 ± 0.07

0.12 ± 0.01

0.01 ± 0.02

0.60 ± 0.07

0.22 ± 0.77

27984.80

  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.