Performance of Angus weaner heifers varying in residual feed intake-feedlot estimated breeding values grazing severely drought-affected pasture

2020 ◽  
Author(s):  
F. A. P. Alvarenga ◽  
H. Bansi ◽  
R. C. Dobos ◽  
K. L. Austin ◽  
A. J. Donaldson ◽  
...  
Keyword(s):  
Feed Intake ◽  
Residual Feed Intake ◽  
Breeding Values ◽  
Estimated Breeding Values

Divergent genotypes for fatness or residual feed intake in Angus cattle. 7. Low-fat and low-RFI cows produce more liveweight and better gross margins than do high-fat and high-RFI cows when managed under the same conditions

2018 ◽  
Vol 58 (1) ◽  
pp. 103
Author(s):  
L. Anderton ◽  
J. M. Accioly ◽  
K. J. Copping ◽  
M. P. B. Deland ◽  
M. L. Hebart ◽  
...  
Keyword(s):  
Feed Intake ◽  
Residual Feed Intake ◽  
Low Fat ◽  
Gross Margin ◽  
Breeding Values ◽  
Angus Cattle ◽  
Estimated Breeding Values ◽  
Supplementary Feed ◽  
Gross Margins ◽  
Stocking Rates

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.

Metabolic differences in Angus steers divergently selected for residual feed intake

2004 ◽  
Vol 44 (5) ◽  
pp. 441 ◽  
Author(s):  
E. C. Richardson ◽  
R. M. Herd ◽  
J. A. Archer ◽  
P. F. Arthur
Keyword(s):  
Genetic Variation ◽  
Feed Intake ◽  
Aspartate Aminotransferase ◽  
Dry Matter ◽  
Residual Feed Intake ◽  
Breeding Values ◽  
Dry Matter Digestibility ◽  
Total Plasma Protein ◽  
Estimated Breeding Values ◽  
Animal House

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.

Divergent breeding values for fatness or residual feed intake in Angus cattle. 6. Dam-line impacts on steer carcass compliance

2018 ◽  
Vol 58 (1) ◽  
pp. 94
Author(s):  
M. P. B. Deland ◽  
J. M. Accioly ◽  
K. J. Copping ◽  
J. F. Graham ◽  
S. J. Lee ◽  
...  
Keyword(s):  
Feed Intake ◽  
South Australia ◽  
Residual Feed Intake ◽  
Carcass Weight ◽  
Research Centre ◽  
High Fat ◽  
The South ◽  
Low Fat ◽  
Breeding Values ◽  
Estimated Breeding Values

The present study determined the impact of maternal genetics for estimated breeding values for rib fat (High-Fat, Low-Fat) or residual feed intake (RFI; High-RFI, Low-RFI) on the carcass compliance of Angus steer progeny when reared pre-weaning under High or Low-Nutrition and post-weaning under various finishing system (grazing versus short-term feedlot). The dams were joined to sires of similar genetic background (close to average estimated breeding values) and sires were rotated among all dam genotypes, with herds located at either Struan Research Centre, near Naracoorte in the south-east of South Australia, or Vasse Research Station, in the south-west of Western Australia. The breeding herd was part of the Beef CRC maternal productivity project and cows were managed under either High or Low-Nutrition, achieved by adjustments to stocking rate in rotational grazing systems and supplementary feeding, so as to maintain ~20% difference in cow liveweight. The steer progeny were weaned at ~7 months of age, with individuals from both pre-weaning nutritional treatments being treated the same from then on at each site. Steers from Struan Research Centre in South Australia born in 2008 and 2009 were sold and grown out on pasture on a local commercial property. Steer calves born in 2010 at Vasse remained on the station where they were backgrounded on hay, followed by a short period (111 days) total mixed ration containing 40% grain. In the first year, steers from Struan (n = 58) were slaughtered together at ~2 years of age, and in the second year (n = 85), consigned to six slaughter groups as their ultrasound-scanned subcutaneous P8 (rump) fat reached 7 mm and their liveweight exceeded 550 kg. Steers from Vasse (n = 101) were slaughtered at ~12 months of age, all on the same day. High-Fat-line dams produced steers with carcasses with greater P8 fat than did Low-Fat-line dams at both sites. At Struan, when the 2008-born steers were slaughtered together, more steers from Low-Fat dams failed to meet minimum fat specifications, than steers from High-Fat dams (28% vs 9% respectively). The steers born in 2009 at Struan all met processor fat specifications but steers from the Low-Fat dams took longer to reach the fat threshold, and so had greater carcass weight, but attracted more price penalties because of increased dentition. All steers from Vasse met minimum requirements for fat, with none penalised for dentition. Vasse steers from High- or Low-RFI dams performed in a manner similar to that from High- and Low-Fat dams, respectively, in that the High-RFI group produced fatter carcasses than did the Low-RFI group. Steers reared under low pre-weaning nutrition weighed less at weaning than did those on High-Nutrition, but had higher weight gains after weaning, although insufficient to result in the same carcass weight. The results showed that commercial cattle producers need to be aware of the balance and trade-off among fat breeding value, effect of pre-weaning nutrition and post-weaning growth required to ensure their cattle meet market specifications and to avoid price penalties.

Accuracy of predicting genomic breeding values for residual feed intake in Angus and Charolais beef cattle1

2013 ◽  
Vol 91 (10) ◽  
pp. 4669-4678 ◽  
Author(s):  
L. Chen ◽  
F. Schenkel ◽  
M. Vinsky ◽  
D. H. Crews ◽  
C. Li
Keyword(s):  
Feed Intake ◽  
Residual Feed Intake ◽  
Genomic Breeding ◽  
Breeding Values

scholarly journals Simultaneous Bayesian estimation of genetic parameters for curves of weight, feed intake and residual feed intake in beef cattle

2021 ◽  
Author(s):  
Hadi Esfandyari ◽  
Just Jensen
Keyword(s):  
Feed Intake ◽  
Feed Efficiency ◽  
Genetic Parameters ◽  
Residual Feed Intake ◽  
Test Period ◽  
Random Regression ◽  
Farm Animals ◽  
Joint Analysis ◽  
Breeding Values ◽  
Covariance Functions

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.

Divergent breeding values for fatness or residual feed intake in Angus cattle. 4. Fat EBVs’ influence on fatness fluctuation and supplementary feeding requirements

2018 ◽  
Vol 58 (1) ◽  
pp. 67
Author(s):  
J. M. Accioly ◽  
K. J. Copping ◽  
M. P. B. Deland ◽  
M. L. Hebart ◽  
R. M. Herd ◽  
...  
Keyword(s):  
Feed Intake ◽  
Residual Feed Intake ◽  
Supplementary Feeding ◽  
Genetic Line ◽  
High Fat ◽  
Low Fat ◽  
Breeding Values ◽  
Angus Cattle ◽  
The Difference ◽  
Supplementary Feed

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.

Using genes differentially expressed in bulls to classify steers divergently selected for high and low residual feed intake

2012 ◽  
Vol 52 (7) ◽  
pp. 608 ◽  
Author(s):  
Y. Chen ◽  
P. F. Arthur ◽  
R. M. Herd ◽  
K. Quinn ◽  
I. M. Barchia
Keyword(s):  
Real Time ◽  
Feed Intake ◽  
Real Time Pcr ◽  
Calcium Binding ◽  
Correlation Coefficients ◽  
Residual Feed Intake ◽  
Differentially Expressed ◽  
Quantitative Real Time Pcr ◽  
The Difference ◽  
Estimated Breeding Values

Feed efficiency is an economically important trait in livestock and residual feed intake (RFI) is a commonly used measure of the trait in beef cattle. Residual feed intake is the difference between the actual feed intake recorded over a test period and the expected feed intake of an animal based on its size and growth rate. It is a heritable trait, and efficient animals have lower RFI values. Several genes have been identified as being differentially expressed in the liver of Angus bulls that have been divergently selected for RFI. The objective of this study was to use genes that are differentially expressed in bulls to classify Angus steers from the same divergent RFI selection lines. Liver samples were collected at slaughter from 40 high RFI and 40 low RFI steers that were ~23 months old, and had just completed a 251-day feedlot feeding period. RNA samples from the livers were assayed by quantitative real-time PCR for 14 genes, which have been identified previously in bulls. Steers were not measured for RFI, hence the estimated breeding values (EBV) for RFI of their parents were used to calculate their mid-parent (average of the two parents) RFI-EBV. Correlation and discriminant analyses were conducted on the normalised quantitative real-time PCR data from the steers. Discriminant analysis was also conducted on the bull data for comparison. In the steers, 8 out of the 14 genes were significantly (P < 0.05) correlated with RFI-EBV. Two genes from the glutathione S-transferase mu family (GSTM1 and GSTM2) and the S100 calcium-binding protein A10 (S100A10) had the highest correlations with RFI-EBV, with correlation coefficients of 0.59, 0.44 and 0.36, respectively. Based on the 14 expressed genes, 84% of the steers and 98% of the bulls were correctly classified into their respective RFI selection lines. The results of this study indicate that a high proportion of the genes that were differentially expressed in the original study with bulls were also differentially expressed in this study with steers. The high accuracy in classification obtained in this study shows that the transcriptional approach to the study of the biological processes involved in variation in RFI has great potential for identification of candidate genes.

scholarly journals New residual feed intake criterion for longitudinal data

2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Ingrid David ◽  
Van-Hung Huynh Tran ◽  
Hélène Gilbert
Keyword(s):  
Regression Model ◽  
Feed Intake ◽  
Genetic Correlations ◽  
Residual Feed Intake ◽  
Repeated Measurements ◽  
Regression Coefficients ◽  
Production Traits ◽  
Breeding Values ◽  
Time Points ◽  
Heritability Estimates

Abstract Background Residual feed intake (RFI) is one measure of feed efficiency, which is usually obtained by multiple regression of feed intake (FI) on measures of production, body weight gain and tissue composition. If phenotypic regression is used, the resulting RFI is generally not genetically independent of production traits, whereas if RFI is computed using genetic regression coefficients, RFI and production traits are independent at the genetic level. The corresponding regression coefficients can be easily derived from the result of a multiple trait model that includes FI and production traits. However, this approach is difficult to apply in the case of multiple repeated measurements of FI and production traits. To overcome this difficulty, we used a structured antedependence approach to account for the longitudinality of the data with a phenotypic regression model or with different genetic and environmental regression coefficients [multi- structured antedependence model (SAD) regression model]. Results After demonstrating the properties of RFI obtained by the multi-SAD regression model, we applied the two models to FI and production traits that were recorded for 2435 French Large White pigs over a 10-week period. Heritability estimates were moderate with both models. With the multi-SAD regression model, heritability estimates were quite stable over time, ranging from 0.14 ± 0.04 to 0.16 ± 0.05, while heritability estimates showed a U-shaped profile with the phenotypic regression model (ranging from 0.19 ± 0.06 to 0.28 ± 0.06). Estimates of genetic correlations between RFI at different time points followed the same pattern for the two models but higher estimates were obtained with the phenotypic regression model. Estimates of breeding values that can be used for selection were obtained by eigen-decomposition of the genetic covariance matrix. Correlations between these estimated breeding values obtained with the two models ranged from 0.66 to 0.83. Conclusions The multi-SAD model is preferred for the genetic analysis of longitudinal RFI because, compared to the phenotypic regression model, it provides RFI that are genetically independent of production traits at all time points. Furthermore, it can be applied even when production records are missing at certain time points.

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