The benefits of carcass estimated breeding values for pasture-finished cattle are not as great as for long-fed cattle
M. L. Hebart
A B , S. J. Lee A and W. S. Pitchford A
A Davies Livestock Research Centre, School of Animal and Veterinary Sciences, The University of Adelaide, Roseworthy Campus, Mudla Wirra Road, Roseworthy, SA 5371, Australia.
B Corresponding author. Email: michelle.hebart@adelaide.edu.au
Animal Production Science 61(3) 326-332 https://doi.org/10.1071/AN20153
Submitted: 4 April 2020 Accepted: 24 September 2020 Published: 24 November 2020
Abstract
Context: BREEDPLAN reports estimated breeding values (EBVs) for many traits, but there are few EBVs specifically for the inputs into the Meat Standards Australia (MSA) index for producers, so as to make genetic progress. It is not known how selection on current BREEDPLAN EBVs influences the MSA index and whether these relationships are the same for different market end-points.
Aims: The aim of the present study was to examine the extent to which the MSA index of commercial animals is related to sire EBVs.
Methods: Data from 12 industry or research datasets (6997 animals) from four breeds (Angus, Charolais, Hereford and Limousin), three feeding regimes (pasture-, short- and long-fed) and 433 sires have been included for analysis. Carcass traits (intramuscular fat (IMF), MSA marbling, eye-muscle area, MSA index, rib, ossification and hot standard carcass weight) were regressed on BREEDPLAN sire EBVs (IMF EBV, eye-muscle area EBV, 600-day weight EBV, rib EBV). Sire ariance components were estimated for each of the 12 datasets, to determine whether the genetic variance in the MSA index and its indicator traits changed with carcass weight.
Key results: Sire variation in carcass traits changed with market end-point (or feeding regime) for all carcass traits except ossification, where there was no difference between long- and pasture-finished systems. One of the biggest differences between market end-points was observed in marbling where there was a 5.5-fold increase in the sire standard deviation for a long-feedlot finish system relative to pasture (1619 long vs 352 pasture finish). The sire EBV that had the greatest effect on the MSA index was IMF. A 1-unit increase in IMF EBV was associated with an improvement in the MSA index by only 0.34 units for long-fed cattle or 0.12 units for cattle finished on pasture. Furthermore, the regression coefficient between carcass traits and the sire EBV for the same trait was significantly lower for pasture-finished than for long-fed cattle.
Conclusions and implications: This means that commercial producers are unlikely to be receiving the full benefits of purchasing superior eating-quality sires unless they receive a premium from the finishing or wholesale meat sectors where the benefits are captured or they retain ownership through to heavier finish weights.
Keywords: commercial producers, intra-muscular fat, MSA index.
References
Angus Australia (2020) ‘Angus Australia mid-March 2020 Angus BREEDPLAN reference tables.’ Available at https://angus.tech/enquiry/animal/ebv-percs [Verified 10 March 2020]Arthur PF, Herd RM, Wilkins JF, Archer JA (2005) Maternal productivity of Angus cows divergently selected for post-weaning residual feed intake. Australian Journal of Experimental Agriculture 45, 985–993.
| Maternal productivity of Angus cows divergently selected for post-weaning residual feed intake.Crossref | GoogleScholarGoogle Scholar |
Barwick SA, Johnston DJ, Wolcott ML, Wilkins JF, McKiernan WA (2009) Evaluation of the Angus BREEDPLAN IMF% EBV in 100d-fed Angus × Hereford steer progeny. In ‘Proceedings of the Association for the Advancement of Animal Breeding and Genetics. Vol. 18’, 28 September – 1 October 2009, Barossa Valley, SA, Australia. (Eds A Safari, B Pattie, B Restall) pp. 484–487. (The Association for the Advancement of Animal Breeding and Genetics: Armidale, NSW, Australia)
Fuller FA (1987) ‘Measurement error models.’ (Wiley: New York, NY, USA)
Gilmour AR, Gogel BJ, Cullis BR, Thompson R (2009) ‘ASReml user guide release 2.0.’ (VSN International: Hemel Hempstead, UK)
Herd RM, Arthur PF, Bottema CDK, Egarr AR, Geesink GH, Lines DS, Piper S, Siddell JP, Thompson JM, Pitchford WS (2018) Genetic divergence in residual feed intake affects growth, feed efficiency, carcass and meat quality characteristics of Angus steers in a large commercial feedlot. Animal Production Science 58, 164–174.
| Genetic divergence in residual feed intake affects growth, feed efficiency, carcass and meat quality characteristics of Angus steers in a large commercial feedlot.Crossref | GoogleScholarGoogle Scholar |
Johnston DJ, Reverter A, Burrow HM, Oddy VH, Robinson DL (2003) Genetic and phenotypic characterisation of animal, carcass, and meat quality traits from temperate and tropically adapted beef breeds. 1. Animal measures. Australian Journal of Agricultural Research 54, 107–118.
| Genetic and phenotypic characterisation of animal, carcass, and meat quality traits from temperate and tropically adapted beef breeds. 1. Animal measures.Crossref | GoogleScholarGoogle Scholar |
McKiernan WA, Wilkins JF, Barwick SA, Tudor GD, McIntyre BL, Graham JF, Deland MPB, Davies L (2005) CRC Regional Combinations Project: effects of genetics and growth path on beef production and meat quality: experimental design, methods and measurements. Australian Journal of Experimental Agriculture 45, 959–969.
| CRC Regional Combinations Project: effects of genetics and growth path on beef production and meat quality: experimental design, methods and measurements.Crossref | GoogleScholarGoogle Scholar |
Pitchford WS, Accioly JM, Banks RG, Barnes AL, Barwick SA, Copping KJ, Deland MPB, Donoghue KA, Edwards N, Hebart ML, Herd RM, Jones FM, Laurence M, Lee SJ, McKiernan WA, Parnell PF, Speijers EJ, Tudor GD, Graham JF (2018) Genesis, design and methods of the Beef CRC Maternal Productivity Project. Animal Production Science 58, 20–32.
| Genesis, design and methods of the Beef CRC Maternal Productivity Project.Crossref | GoogleScholarGoogle Scholar |
Polkinghorne R, Thompson JM, Watson R, Gee A, Porter M (2008) Evolution of the Meat Standards Australia (MSA) beef grading system. Australian Journal of Experimental Agriculture 48, 1351–1359.
| Evolution of the Meat Standards Australia (MSA) beef grading system.Crossref | GoogleScholarGoogle Scholar |
Reverter A, Johnston DJ, Perry D, Goddard ME, Burrow HM (2003) Genetic and phenotypic characterisation of animal, carcass, and meat quality traits from temperate and tropically adapted beef breeds. 2. Abattoir carcass traits. Australian Journal of Agricultural Research 54, 119–134.
| Genetic and phenotypic characterisation of animal, carcass, and meat quality traits from temperate and tropically adapted beef breeds. 2. Abattoir carcass traits.Crossref | GoogleScholarGoogle Scholar |
Robertson A (1959) The sampling variance of the genetic correlation coefficient. Biometrics 15, 469–485.
| The sampling variance of the genetic correlation coefficient.Crossref | GoogleScholarGoogle Scholar |
Robinson DL (2005) Accounting for bias in regression coefficients with example from feed efficiency. Livestock Production Science 95, 155–161.
| Accounting for bias in regression coefficients with example from feed efficiency.Crossref | GoogleScholarGoogle Scholar |
Te Mania Angus (2020) Team Te Mania. Available at https://angus.tech/enquiry/animal/ebv-percs [Verified 10 March 2020]
