Estimation of genomic breeding values for residual feed intake in a multibreed cattle population1

2014 ◽  
Vol 92 (8) ◽  
pp. 3270-3283 ◽  
Author(s):  
M. Khansefid ◽  
J. E. Pryce ◽  
S. Bolormaa ◽  
S. P. Miller ◽  
Z. Wang ◽  
...  
2013 ◽  
Vol 91 (10) ◽  
pp. 4669-4678 ◽  
Author(s):  
L. Chen ◽  
F. Schenkel ◽  
M. Vinsky ◽  
D. H. Crews ◽  
C. Li

2011 ◽  
Vol 89 (11) ◽  
pp. 3353-3361 ◽  
Author(s):  
F. D. N. Mujibi ◽  
J. D. Nkrumah ◽  
O. N. Durunna ◽  
P. Stothard ◽  
J. Mah ◽  
...  

Author(s):  
Hadi Esfandyari ◽  
Just Jensen

Abstract Rate of gain and feed efficiency are important traits in most breeding programs for growing farm animals. Rate of gain (GAIN) is usually expressed over a certain age period and feed efficiency is often expressed as residual feed intake (RFI), defined as observed feed intake (FI) minus expected feed intake based on live weight (WGT) and GAIN. However, the basic traits recorded are always WGT and FI and other traits are derived from these basic records. The aim of this study was to develop a procedure for simultaneous analysis of the basic records and then derive linear traits related to feed efficiency without retorting to any approximations. A bivariate longitudinal random regression model was employed on 13,791 individual longitudinal records of WGT and FI from 2,827 bulls of six different beef breeds tested for own performance in the period from 7 to 13 months of age. Genetic and permanent environmental covariance functions for curves of WGT and FI were estimated using Gibbs sampling. Genetic and permanent covariance functions for curves of GAIN were estimated from the first derivative of the function for WGT and finally the covariance functions were extended to curves for RFI, based on the conditional distribution of FI given WGT and GAIN. Furthermore, the covariance functions were extended to include GAIN and RFI defined over different periods of the performance test. These periods included the whole test period as normally used when predicting breeding values for GAIN and RFI for beef bulls. Based on the presented method, breeding values and genetic parameters for derived traits such as GAIN and RFI defined longitudinally or integrated over (parts of) of the test period can be obtained from a joint analysis of the basic records. The resulting covariance functions for WGT, FI, GAIN and RFI are usually singular but the method presented here do not suffer from the estimation problems associated with defining these traits individually before the genetic analysis. All results are thus estimated simultaneously, and the set of parameters are consistent.


2018 ◽  
Vol 58 (1) ◽  
pp. 103
Author(s):  
L. Anderton ◽  
J. M. Accioly ◽  
K. J. Copping ◽  
M. P. B. Deland ◽  
M. L. Hebart ◽  
...  

The present paper focuses on the economic evaluation of the observed differences in maternal productivity of different genetic lines in Angus cattle that were managed under contrasting nutritional regimes typical of southern Australia. Five hundred Angus cows were managed concurrently at two locations in southern Australia. On each site, the cows were managed under the following two different nutritional treatments: High and Low, to simulate different stocking rates. Cows selected for a divergence in either carcass rib-fat depth or residual feed intake based on mid-parent estimated breeding values for those traits, were allocated in replicate groups to either High- or Low-nutrition treatments. By design, the supplementary feeding regime was the same for the High and Low genetic lines to ensure genetic differences were not confounded with management differences. Animal productivity results from the experiment were used as input data to evaluate the economic performance of the four genetic lines under the two nutritional treatments. Two methods were used; the first was a gross-margin calculation of income minus variable costs as AU$ per breeding cow for a 1000-cow herd; the second was a whole-farm linear programming model maximising the gross margin. Stocking rates were optimised by matching the energy requirements for the whole herd with the energy available from pasture and supplementary feed on a representative 700-ha farm. Using the two methods of calculating gross margin (per cow and optimised per hectare), including examination of sensitivity to changes in prices of cattle and supplementary feed, the present study demonstrated that genetically leaner cows due to selection of low fat or low residual feed intake, had gross margins superior to those of genetically fatter cows. They generated more income by selling more liveweight due to heavier weights and higher stocking rates. The results are affected by the management system utilised and some confounding with growth (leaner genetic lines had higher growth estimated breeding values), but will assist producers to make more informed decisions about how to manage animal breeding and nutritional interactions.


2018 ◽  
Vol 58 (1) ◽  
pp. 67
Author(s):  
J. M. Accioly ◽  
K. J. Copping ◽  
M. P. B. Deland ◽  
M. L. Hebart ◽  
R. M. Herd ◽  
...  

The productivity of 500 Angus cows, divergently selected for either rib fat or residual feed intake (RFI) based on BREEDPLAN estimated breeding values (EBVs) and managed under two levels of nutrition (stocking rates), was evaluated. The study examined the effects of genetic line, nutrition and weaning history on profiles for weight, rib fat depth, fatness (rib fat depth adjusted for weight) and supplementary feed requirements from just before the first joining as heifers through to the weaning of their third calf. Cows gained both weight and fat as they grew older. Observed fluctuations in weight and rib fat depth, within each year, were associated with pasture availability and physiological demands. Cows that did not wean a calf in a given year became heavier and fatter than cows that did; and they remained so when they calved the following year. High-fat and High-RFI were always fatter and lighter than Low-fat and Low-RFI cows, respectively. The difference in rib fat and fatness between High- and Low-RFI lines (P < 0.001) was similar to, although slightly greater than, the difference between High- and Low-fat lines (P = 0.048) reflecting differences in rib fat EBVs between High-RFI (3.2 ± 1.47) and Low-RFI (–0.7 ± 1.3) compared with High-fat (1.1 ± 0.78) and Low-fat (–1.4 ± 0.67). Cows on High-Nutrition were heavier and fatter than those on Low-Nutrition (P < 0.001) but there were no significant interactions between genetic line and nutrition (P > 0.05). Supplementary feeding threshold was reached earlier by Low-fat and Low-RFI cows than their counterparts. Calculations based on the data in the present paper estimate that if cows lose condition at a rapid rate (1 condition score/month), then a cow with an extra 1 mm rib fat EBV would take 7.5 days longer to reach the same supplementary feeding threshold. Fat EBVs can, therefore, be a useful tool in assisting beef producers to match genotype to their production system.


animal ◽  
2013 ◽  
Vol 7 (11) ◽  
pp. 1759-1768 ◽  
Author(s):  
M. Pszczola ◽  
R.F. Veerkamp ◽  
Y. de Haas ◽  
E. Wall ◽  
T. Strabel ◽  
...  

2004 ◽  
Vol 44 (5) ◽  
pp. 441 ◽  
Author(s):  
E. C. Richardson ◽  
R. M. Herd ◽  
J. A. Archer ◽  
P. F. Arthur

Residual feed intake measures variation in feed intake independent of liveweight and liveweight gain. First generation steer progeny (n = 33) of parents previously selected for low or high post-weaning residual feed intake were examined to determine metabolic processes contributing to variation in residual feed intake. Blood samples were taken from the steers from weaning through to slaughter. These samples were analysed for key metabolites and hormones. Total urine and total faecal collections were taken from the steers in an animal-house experiment to estimate dry matter digestibility, microbial protein production and protein turnover. At weaning, there were phenotypic correlations between concentrations in plasma of β-hydroxy butyrate (r = 0.55, P<0.001), aspartate aminotransferase (r = 0.34; P<0.001), urea (r = 0.26, P<0.1) and total plasma protein (r = 0.26, P<0.1), and subsequent residual feed intake over the whole experiment (feedlot plus animal-house phases), but no evidence of associations with genetic variation in residual feed intake. At the start of the feedlot residual feed intake test period plasma levels of glucose, creatinine and aspartate aminotransferase were correlated with residual feed intake over the experiment (r = 0.40, –0.45 and 0.43, respectively, P<0.05), providing evidence of phenotypic associations with residual feed intake, and concentrations of urea and triglycerides were correlated with sire estimated breeding values for residual feed intake (b = 1.20 and –0.08, respectively, P<0.05), providing evidence for genetic associations with residual feed intake. At the end of the experiment, concentrations of plasma insulin, cortisol and leptin were correlated with residual feed intake over the experiment (r = 0.43, –0.40 and 0.31, respectively, P<0.05). Plasma concentrations of urea, insulin and cortisol illustrated trends for an association with sire estimated breeding values for RFI (b = –0.35, 0.98 and 12.19, respectively, P<0.1). The ratio of allantoin : creatinine in urine, as a measure of rumen microbial production, tended to be correlated with residual feed intake in the animal house (r�=�0.32, P<0.1) but not with residual feed intake over the entire experiment (r = 0.10, P>0.05). Neither the ratio of 3-methyl histidine : creatinine in urine, as a measure of rate of muscle breakdown, nor the dry matter digestibility measured in the animal house were correlated with residual feed intake in the animal house (r = 0.04, P>0.05), or residual feed intake over the whole experiment (r = –0.22, P>0.05), and neither were associated with genetic variation in residual feed intake.It is hypothesised that high-RFI (low-efficiency) steers have higher tissue energy requirements, are more susceptible to stress and utilise different tissue substrates (partly as a consequence of differences in body composition) to generate energy required in response to exposure to a stressful stimulus.


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