View Full Table | Close Full ViewTable 1.

Overall mean and least square means from the statistical model for initial and final age, initial and final BW, concentrate intake (CI), mid-test metabolic BW (MTW), ADG, fat depth (FAT), and residual feed intake (RFI) across breeds

 
Breeds1
Trait Mean, n = 1,963 AN, n = 183 CH, n = 485 HE, n = 100 LI, n = 821 SI, n = 374 Pooled SEM P-value for breed effect
Initial age, d 314 334 320 307 306 305 31 0.4551
Final age, d 399 418 404 392 390 390 29 0.3857
Initial BW, kg 456.3 436.0a 487.2b 427.9a 437.1a 493.1b 9.12 <0.0001
Final BW, kg 599.2 574.1a 635.5b 574.5a 572.2a 640.0b 9.62 <0.0001
CI, kg/d 10.94 11.71c 11.38b 11.56bc 10.19a 12.24d 0.19 <0.0001
MTW, kg 0.75 113.2 108.4a 117.2b 107.8a 108.3a 118.1b 1.42 <0.0001
ADG, kg/d 1.70 1.63a 1.75b 1.74b 1.60a 1.74b 0.04 <0.0001
FAT, cm 0.309 0.552c 0.256a 0.559c 0.249a 0.316b 0.015 <0.0001
RFI,2 kg/d 0 0.332c –0.124ab 0.025b –0.205a 0.443c 0.12 <0.0001
a,b,c,dLeast square means within a row with different superscripts differ (P < 0.05).
1AN = Angus; CH = Charolais; HE = Hereford; LI = Limousin; SI = Simmental.
2Residuals from the multiple regressions of CI, corrected for contemporary group, on MTW, ADG, and FAT.



View Full Table | Close Full ViewTable 2.

Partial regression coefficients of concentrate intake (CI) on mid-test metabolic BW (MTW), ADG, fat depth (FAT), and their interactions for the phenotypic models that did not contain any genetic effects

 
Model1 MTW ADG FAT MTW × ADG MTW × FAT ADG × FAT R2 Adjusted R2 2 AIC3
[P1] 0.093 0.691 0.679 –497.3
[P2] 0.081 1.887 0.760 0.750 –991.0
[P3] 0.080 1.899 1.132 0.764 0.755 –1,026.5
[P4] 0.104 3.471 1.167 –0.014 0.765 0.756 –1,034.2
[P5] 0.080 1.900 1.254 NS4 –0.001 NS 0.764 0.755 –1,024.5
[P6] 0.080 1.831 0.758 NS 0.213 NS 0.764 0.755 –1,025.0
1Models included the contemporary group (n = 69) and breed (n = 5) as systematic effects.
2Adjusted R2 = 1 – [SSE × (n – 1)]/[SST – (nv)], in which SST is the total sum of squares, SSE is the error sums of squares, n is the number of individuals, and v is the residual degrees of freedom.
3AIC = Akaike information criteria: n × ln (SSE/n) + 2 × k, in which SSE is the error sum of squares and k is the number of independent variables. Lower is the best.
4NS = non-significant (i.e., regression coefficients do not different (P < 0.05) from zero).



View Full Table | Close Full ViewTable 3.

Additive genetic variance for animal-specific random regression on the intercept, mid-test metabolic BW (MTW), ADG, and fat depth (FAT) as well as the residual variance, heritability (h2), and model fit statistics for the genetic models across breeds, which included relationships among animals

 
Additive genetic variance
Residual variance, (kg/d)2 h2 2 Log (likelihood) AIC3
Model1 Intercept, (kg/d)2 MTW, (× 10–4 kg0.75)2 ADG, (kg/d)2 FAT, (cm)2
[G1] 0.317 0.315 0.50 –581.30 1,174.6
[G2] 0 0.4 0.178 0.72 –561.63 1,137.3
[G3] 0.222 0.035 0.306 0.52 –579.41 1,172.8
[G4] 0.299 0.212 0.308 0.51 –580.59 1,175.2
[G5] 0 0.4 0 0.178 0.72 –561.63 1,139.3
[G6] 0 0.4 0.173 0.170 0.73 –561.03 1,138.1
[G7] 0.218 0.032 0.137 0.302 0.52 –579.11 1,174.2
[G8] 0 0.4 0 0.173 0.170 0.73 –561.03 1,140.1
1All models included the contemporary group and breed as systematic effects as well as random animal effects (with relationships) for the intercept, MWT, ADG, and FAT where appropriate.
2Heritability for models [G2] to [G8] were calculated using the phenotypic variance from model [G1] and the residual variance from the tested models.
3AIC = Akaike information criteria: –2 × Log (likelihood) + 2 × k, in which k is the number of parameters in the model. Lower is the best.