1. EBVs and the
breeding herd –
What’s happening
out there?
Wayne Pitchford
Kath Donoghue

2. Genetic change in
growth traits
50kg

3. Genetic change in
body composition

4. Genetic change in
profit per cow

5. Changing
Genetic Potential
962 progeny analysed
across 77 herds
623 progeny analysed
across 20 herds
Sire 600d
Wt
(kg)
MCWt
(kg)
Milk
(kg)
DC
(days)
Rib
Fat
(mm)
Rump
Fat
(mm)
RBY
(%)
IMF
%
Long
Fed
Index
($)
1 +122 +119 +20 -8.7 -3.2 -3.2 +1.6 +0.6 +103
2 +57 +50 0 -4.7 +4.5 +3.6 -2.0 +3.7 +98

6. Data collection
 Traits:
– Weight and Height
– P8 and Rib fat and IMF%
– Eye muscle area and Condition Score
 Time of collection:
– 1st
parity: Pre Calving (PC1) and Weaning (W1)
– 2nd
parity: Pre Calving (PC2) and Weaning (W2)

7. Industry herds:
Bald Blair Angus Barwidgee Angus
Booroomooka Angus Chis Angus
Eastern Plains Angus Kenny’s Creek Angus
Rennylea Angus South Boorook Herefords
Te Mania Angus Tuwhareto Angus
Twynam Angus Willalooka Angus
Wirruna Herefords Yalgoo Herefords
Yavenvale Herefords
Ultrasound technicians:
Jim Green
Liam Cardile
Matt Wolcott
Acknowledgements

8. Data structure
Angus (n=5,949) Hereford (n=1,452)
PC1 4,867 1,124
W1 3,735 645
PC2 2,772 918
W2 2,109 485

9. Average (SD) σ2
p (SE) h2
(SE)
A H A H A H
n=3,735 n=645
WT (kg) 515 (64) 503 (43) 2,003 (58) 1,868 (114) 0.39 (0.05) 0.42 (0.12)
P8 (mm) 5.8 (2.9) 6.8 (3.0) 5.4 (0.17) 17 (13) 0.51 (0.06) 0.97 (0.06)
Rib (mm) 5.0 (2.2) 5.0 (1.8) 3.2 (0.10) 3.3 (0.21) 0.49 (0.05) 0.54 (0.14)
EMA (cm2
) 59 (9) 58 (6) 42 (1.2) 40 (2.4) 0.32 (0.05) 0.47 (0.11)
IMF (%) 5.5 (1.9) 2.9 (0.08) 0.39 (0.05)
Descriptive statistics – W1

10. Phenotypic relationships for
same trait over time
Trait PC1-W1 W1-PC2 PC2-W2
WT 0.66 (0.01) 0.79 (0.009) 0.72 (0.01)
P8 0.47 (0.02) 0.74 (0.01) 0.57 (0.02)
Rib 0.49 (0.02) 0.72 (0.01) 0.57 (0.02)
EMA 0.45 (0.02) 0.63 (0.02) 0.50 (0.02)
IMF 0.51 (0.01) 0.69 (0.01) 0.54 (0.02)

11. Trait PC1-W1 W1-PC2 PC2-W2
WT 0.88 (0.03) 0.94 (0.03) 0.95 (0.02)
P8 0.70 (0.05) 0.89 (0.04) 0.92 (0.04)
Rib 0.65 (0.05) 0.96 (0.04) 0.96 (0.03)
EMA 0.68 (0.07) 0.84 (0.06) 0.85 (0.07)
IMF 0.76 (0.06) 0.92 (0.04) 0.86 (0.06)
Genetic relationships for same
trait over time

12. Change in weight:
1st
lactation (n=3,615)
0
100
200
300
400
500
600
-330
-290
-250
-210
-170
-130
-90
-50
-10
30
70
110
150
190
230
270
Change in WT, kg
Numberoffemales

13. 0
100
200
300
400
500
600
-20
-18
-16
-14
-12
-10
-8
-6
-4
-2
0
2
4
6
8
10
12
14
16
18
20
Change in P8 (mm)
Numberoffemales Change in P8:
1st
lactation (n=3,616)

14. 0
100
200
300
400
500
600
-34
-28
-22
-16
-10
-4
2
8
14
20
26
32
Change inEMA,sq.cm
Numberoffemales Change in EMA:
1st
lactation (n=3,623)

15. Change in Weight
over time
Trait 1st
lactation
Weaning –
Calving
2nd
lactation
1st
lactation 0.16 (0.04) -0.53 (0.02) 0.10 (0.03)
Weaning –
Calving
-0.51 (0.23) 0.09 (0.04) -0.43 (0.03)
2nd
lactation 0.62 (0.20) -0.30 (0.27) 0.14 (0.05)
rp above; rg below

16. Change in traits:
1st
lactation
Trait WT P8 EMA IMF
WT 0.48 (0.01) 0.43 (0.01) 0.36 (0.02)
P8 0.70 (0.10) 0.39 (0.02) 0.40 (0.02)
EMA 0.70 (0.12) 0.68 (0.11) 0.35 (0.02)
IMF 0.71 (0.12) 0.76 (0.10) 0.74 (0.11)
rp above; rg below

17. Messages
 Currently rapid change in cattle growth, carcass
composition and profit. Will accelerate!
 Cow weight and body composition is heritable
and repeatable over time
 Cows change in weight and composition
substantially throughout year
 Change in weight is lowly heritable

18. Thank you for the
enormous
contribution from
the Vasse team
and for listening!

19. Contemporary groups
Number Avg size Min size Max size
PC1 188 57 2 182
PC2 86 87 2 171
Pre-Calving:
• Preg status
• Parity 1 wean status (PC2 only)
• Season (Autumn, Spring)
• Herd
• Breeder management group

20. Number Avg size Min size Max size
W1 117 110 2 368
W2 87 70 2 161
Weaning:
• Preg status of current parity
• Preg status of future parity
• Wean status of current parity
• Season (Autumn, Spring)
• Herd
• Breeder management group
Contemporary groups

21. Model of analysis
Animal model fitted using ASReml:
 Contemporary group
 Age of animal
 Direct genetic effect
Bivariate analyses:
 Same trait across 4 time points (PC1, W1, PC2,
W2)
 Different traits within same time point

22. Contemporary groups
Number Avg size Min size Max size
PC1 188 57 2 182
PC2 86 87 2 171
Pre-Calving:
• Preg status
• Parity 1 wean status (PC2 only)
• Season (Autumn, Spring)
• Herd
• Breeder management group

23. Number Avg size Min size Max size
W1 117 110 2 368
W2 87 70 2 161
Weaning:
• Preg status of current parity
• Preg status of future parity
• Wean status of current parity
• Season (Autumn, Spring)
• Herd
• Breeder management group
Contemporary groups

24. Model of analysis
Animal model fitted using ASReml:
 Contemporary group
 Age of animal
 Direct genetic effect
Bivariate analyses:
 Same trait across 4 time points (PC1, W1, PC2,
W2)
 Different traits within same time point

25. Descriptive statistics – PC1
Average (SD) σ2
p (SE) h2
(SE)
A H A H A H
n=4,867 n=1,124
WT (kg) 487 (70) 456 (33) 1,209 (33) 1,083 (50) 0.55 (0.05) 0.46 (0.08)
P8 (mm) 5.8 (3.1) 6.4 (2.4) 4.2 (0.11) 6.0 (0.30) 0.52 (0.05) 0.56 (0.09)
Rib (mm) 4.6 (2.2) 4.4 (1.4) 2.1 (0.06) 2.1 (0.10) 0.50 (0.05) 0.65 (0.08)
EMA (cm2
) 57 (10) 50 (6) 36 (0.86) 39 (1.7) 0.30 (0.04) 0.15 (0.06)
IMF (%) 5.2 (2.0) 2.3 (0.06) 0.34 (0.04)

26. Average (SD) σ2
p (SE) h2
(SE)
A H A H A H
n=2,772 n=918
WT (kg) 552 (73) 533 (41) 1,933 (63) 1,671 (80) 0.36 (0.06) 0.07 (0.07)
P8 (mm) 6.1 (3.2) 7.6 (3.0) 5.5 (0.18) 9.1 (0.45) 0.33 (0.06) 0.20 (0.08)
Rib (mm) 4.9 (2.4) 4.9 (1.7) 3.0 (0.10) 3.0 (0.14) 0.28 (0.06) 0.18 (0.08)
EMA (cm2
) 61 (9.8) 55 (7) 45 (1.4) 47 (2.3) 0.25 (0.05) 0.25 (0.09)
IMF (%) 5.5 (2.2) 2.8 (0.09) 0.28 (0.06)
Descriptive statistics – PC2

27. Average (SD) σ2
p (SE) h2
(SE)
A H A H A H
n=2,109 n=485
WT (kg) 585 (74) 588 (49) 2,981 (119) 2,539 (173) 0.54 (0.07) 0.30 (0.14)
P8 (mm) 7.9 (4.1) 11 (4.8) 9.8 (0.42) 23 (1.6) 0.64 (0.08) 0.37 (0.17)
Rib (mm) 6.6 (3.1) 6.7 (2.6) 5.7 (0.24) 6.7 (0.44) 0.57 (0.08) 0.05 (0.11)
EMA (cm2
) 63 (9.4) 62 (7) 42 (1.5) 48 (3.2) 0.23 (0.06) 0.14 (0.12)
IMF (%) 6.1 (1.8) 2.5 (0.09) 0.37 (0.07)
Descriptive statistics – W2

28. Trait WT-P8 WT-EMA WT-IMF P8-EMA P8-IMF EMA-IMF
PC1
0.18
(0.02)
0.41
(0.02)
0.20
(0.02)
0.30
(0.02)
0.42
(0.02)
0.32
(0.02)
W1
0.39
(0.02)
0.53
(0.01)
0.35
(0.02)
0.45
(0.02)
0.57
(0.01)
0.45
(0.02)
PC2
0.30
(0.02)
0.46
(0.02)
0.24
(0.02)
0.36
(0.02)
0.51
(0.02)
0.35
(0.02)
W2
0.39
(0.02)
0.49
(0.02)
0.29
(0.03)
0.47
(0.02)
0.49
(0.02)
0.39
(0.02)
Phenotypic relationships
between traits

29. Trait WT-P8 WT-EMA WT-IMF P8-EMA P8-IMF EMA-IMF
PC1
0.09
(0.08)
0.48
(0.07)
0.21
(0.08)
0.28
(0.08)
0.42
(0.07)
0.31
(0.09)
W1
0.27
(0.09)
0.51
(0.08)
0.29
(0.10)
0.44
(0.08)
0.70
(0.06)
0.42
(0.09)
PC2
0.12
(0.13)
0.53
(0.10)
-0.04
(0.15)
0.13
(0.15)
0.47
(0.11)
0.21
(0.15)
W2
0.45
(0.09)
0.66
(0.09)
0.15
(0.13)
0.68
(0.09)
0.57
(0.09)
0.37
(0.15)
Genetic relationships
between traits

30.  Moderate, consistent phenotypic relationships
 Mostly consistent genetic relationships
 WT higher rg with EMA than fat
 Fat traits (P8, Rib, IMF) appear highly correlated
 Reanalyse when data collection complete
Messages

31. 0
50
100
150
200
250
300
350
-330
-290
-250
-210
-170
-130
-90
-50
-10
30
70
110
150
190
230
270
Change in WT, kg
Numberoffemales Change in weight:
Between parities (n=1,614)

32. 0
50
100
150
200
250
300
350
-330
-290
-250
-210
-170
-130
-90
-50
-10
30
70
110
150
190
230
270
Change in WT, kg
Numberoffemales Change in weight:
Parity 2 (n=2,062)

33. Trait Parity 1 Between parities Parity 2
Parity 1 0.30 (0.05) -0.44 (0.02) 0.11 (0.03)
Between parities -0.72 (0.13) 0.16 (0.05) -0.46 (0.02)
Parity 2 0.97 (0.10) -0.67 (0.18) 0.26 (0.06)
rp above; rg below
Change in P8 over time

34. Trait Parity 1 Between parities Parity 2
Parity 1 0.16 (0.04) -0.46 (0.02) 0.04 (0.03)
Between parities -0.85 (0.13) 0.11 (0.04) -0.52 (0.02)
Parity 2 0.34 (0.30) -0.72 (0.23) 0.06 (0.03)
rp above; rg below
Change in EMA over time

35. Trait Parity 1
Between
parities
Parity 2
Parity 1 0.17 (0.04) -0.39 (0.02) 0.09 (0.03)
Between parities -0.51 (0.23) 0.10 (0.05) -0.52 (0.02)
Parity 2 0.63 (0.23) -0.73 (0.28) 0.10 (0.04)
rp above; rg below
Change in IMF over time

36. Messages
 Other composition traits have similar trends to WT
 Do we need to scan cows?
 Seedstock sector – selection for adaptation
 Breeder sector – monitoring condition/adaptation
 Reanalyse when data collection complete

37. Trait WT P8 EMA IMF
WT 0.34 (0.02) 0.31 (0.02) 0.26 (0.02)
P8 0.57 (0.20) 0.32 (0.02) 0.28 (0.02)
EMA 0.84 (0.17) 0.79 (0.24) 0.29 (0.02)
IMF 0.79 (0.18) 0.51 (0.24) 0.62 (0.29)
rp above; rg below
Change in traits:
Parity 2

38. Trait WT P8 EMA IMF
WT 0.20 (0.03) 0.23 (0.02) 0.18 (0.03)
P8 0.29 (0.28) 0.15 (0.03) 0.26 (0.03)
EMA 0.79 (0.19) -0.13 (0.30) 0.24 (0.02)
IMF 0.49 (0.36) 0.42 (0.31) 0.70 (0.20)
rp above; rg below
Change in traits:
Between parities

39. Messages
 Phenotypic correlations still moderate
 Most genetic correlations lower than Parity 1 & 2
 May need to scan cows?
 High SE on all rg
 Reanalyse when data collection complete

40.  All traits are moderately heritable
 EMA & IMF similar to published estimates in
yearling heifers
 P8 & Rib higher than published estimates- stage
of physiology??
 WT similar to Angus MCW (0.41)
 Reanalyse when data collection complete
Messages

41. Messages
 Phenotypic correlations moderate to high
 Genetic correlations high to very high
 May not need repeated measures on cows
 PC1-W1 phenotypic & genetic correlations lowest
 Only first 2 parities measured
 Need to compare to young measures
 Reanalyse when data collection complete

42.  Low h2
for change in weight
 Change in parity 1 reasonable indicator of change in
parity 2, genetically (rg = 0.62)
 But rp is 0 so environmental correlation must be
negative???
 Change in parity 1 is in opposite direction to change
between parities, (rg = -0.51, rp = -0.53 )
Messages

43. Messages
 Genetically – all traits changing in same direction
 Phenotypic is more moderate
 Do we need to scan cows?
 Seedstock sector – selection for adaptation
 Breeder sector – monitoring condition/adaptation

44. Change in body composition
and maternal output
Trait change:
 Have to be in same CG at both time points
 Age at first time point
 Direct genetic effect
Maternal output (Calf weaning weight):
 Unadjusted calf WWT
 CG: CG of dam for trait change
 PRELIMINARY ANALYSIS!

45. Trait change & maternal output:
Parity 1
Calf WWT (h2
=0.12)
Phenotypic correlation Genetic correlation
WT -0.13 (0.02) -0.24 (0.20)
P8 -0.12 (0.02) -0.31 (0.18)
Rib -0.11 (0.02) -0.26 (0.17)
EMA -0.12 (0.02) -0.50 (0.19)
IMF -0.14 (0.02) -0.51 (0.18)

46. Calf WWT (h2
=0.17)
Trait Phenotypic correlation Genetic correlation
WT -0.15 (0.02) -0.54 (0.19)
P8 0.04 (0.02) -0.10 (0.25)
Rib 0.02 (0.02) -0.10 (0.26)
EMA 0.04 (0.02) -0.47 (0.28)
IMF -0.05 (0.02) -0.67 (0.23)
Trait change & maternal output:
Parity 2

47. Messages
 Increased calf WWT moderately associated
genetically with loss of condition in cows
 Low to zero phenotypic correlations
 h2
of calf WWT low, but is maternal genetic
component (1/4 Vdir + Vmat)
 High SE on all rg
 Make further refinements to model
 Reanalyse when data collection complete

48. Future analyses
 Yearling measures with later life traits
 Fertility analyses
 Lifetime maternal productivity