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Live animal predictions of carcass components and marble score in beef cattle: model development and evaluation

  • M. J. McPhee (a1), B. J. Walmsley (a2), H. C. Dougherty (a1) (a3), W. A. McKiernan (a1) and V. H. Oddy (a1)...

Abstract

Until recently, beef carcass payment grids were predominantly based on weight and fatness categories with some adjustment for age, defined as number of adult teeth, to determine the price received by Australian beef producers for slaughter cattle. With the introduction of the Meat Standards Australia (MSA) grading system, the beef industry has moved towards payments that account for intramuscular fat (IMF) content (marble score (MarbSc)) and MSA grades. The possibility of a payment system based on lean meat yield (LMY, %) has also been raised. The BeefSpecs suite of tools has been developed to assist producers to meet current market specifications, specifically P8-rump fat and hot standard carcass weight (HCW). A series of equations have now been developed to partition empty body fat and fat-free weight into carcass fat-free mass (FFM) and fat mass (FM) and then into flesh FFM (FleshFFM) and flesh FM (FleshFM) to predict carcass components from live cattle assessments. These components then predict denuded lean (kg) and finally LMY (%) that contribute to emerging market specifications. The equations, along with the MarbSc equation, are described and then evaluated using two independent datasets. The decomposition of evaluation datasets demonstrates that error in prediction of HCW (kg), bone weight (BoneWt, kg), FleshFFM (kg), FleshFM (kg), MarbSc and chemical IMF percentage (ChemIMF%) is shown to be largely random error (%) in evaluation dataset 1, though error for ChemIMF% was primarily slope bias (%) in evaluation dataset 1, and BoneWt had substantial mean bias (%) in evaluation dataset 2. High modelling efficiencies of 0.97 and 0.95 for predicting HCW for evaluation datasets 1 and 2, respectively, suggest a high level of accuracy and precision in the prediction of HCW. The new outputs of the model are then described as to their role in estimating MSA index scores. The modelling system to partition chemical components of the empty body into carcass components is not dependent on the base modelling system used to derive empty body FFM and FM. This can be considered a general process that could be used with any appropriate model of body composition.

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Angus Australia 2020. Retrieved on February 2020 from https://www.angusaustralia.com.au
Bibby, J and Toutenburg, H 1977. Prediction and improved estimation in linear models. John Wiley & Sons Ltd, Berlin.
Cafe, LM, McKiernan, WA and Robinson, DL 2018. Selection for increased muscling is not detrimental to maternal productivity traits in Angus cows. Animal Production Science 58, 185192.
Cianzio, DS, Topel, DG, Whitehurst, GB, Beitz, DC and Self, HL 1982. Adipose tissue growth in cattle representing two frame sizes: distribution among depots. Journal of Animal Science 55, 305312.
Conroy, SB, Drennan, MJ, Kenny, DA and McGee, M 2009. The relationship of live animal muscular and skeletal scores, ultrasound measurements and carcass classification scores with carcass composition and value in steers. Animal 3, 16131624.
Duff, C, Werf, JVD, Parnell, P and Clark, S 2018. Comparison of two live-animal ultrasound systems to predict carcase intramuscular fat and marbling in Australian Angus cattle. In Proceedings of the 11th World Congress on Genetics Applied to Livestock Production, 11–16 February 2018, Auckland, New Zealand, pp. 262265.
Garrett, WN and Hinman, N 1969. Re-evaluation of the relationship between carcass density and body composition of beef steers. Journal of Animal Science 28, 15.
Greenwood, PL, Siddell, JP, Walmsley, BJ, Geesink, GH, Pethick, DW and McPhee, MJ 2015. Postweaning substitution of grazed forage with a high-energy concentrate has variable long-term effects on subcutaneous fat and marbling in Bos taurus genotypes. Journal of Animal Science 93, 41324143.
Gudex, BW, Oddy, VH, McPhee, MJ and Walmsley, BJ 2019. Prediction of ossification from live and carcass traits in young beef cattle: model development and evaluation. Journal of Animal Science 97, 144155.
Haecker, TL 1920. Investigations in beef production: the composition of steers at the various stages of growth and fattening; the relation of feed nutrients consumed to substances stored in the body during the various stages of growth and fattening; nutrient requirements for beef production based upon digestible nutrients. Bulletin 193, 1110. University of Minnesota. Agricultural Experiment Station, Saint Paul, MN, USA.
Johnson, ER, Butterfield, RM and Pryor, WJ 1972a. Studies of fat distribution in the bovine carcass I. The partition of fatty tissues between depots. Australian Journal of Agricultural Research 23, 381388.
Johnson, ER, Pryor, WJ and Butterfield, RM 1972b. Studies of fat distribution in the bovine carcass II. Relationship of intramuscular fat to the quantitative analysis of the skeltal musculature. Australian Journal of Agricultural Research 24, 287296
Keele, JW, Williams, CB and Bennett, GL 1992. A computer model to predict the effects of level of nutrition on composition of empty body gain in beef cattle: I. Theory and development. Journal of Animal Science 70, 841857.
Laurenson, YCSM, Walmsley, BJ, Oddy, VH, Greenwood, PL and McPhee, MJ 2013. Modelling trimmed fat from commercial primal cuts. In Proceedings of the 20th International Congress on Modelling and Simulation, 1–6 December 2013, Adelaide, Australia, pp. 600606.
Mayer, DG and Butler, DG 1993. Statistical validation. Ecological Modelling 68, 2132.
McGilchrist, P, Polkinghorne, RJ, Ball, AJ and Thompson, JM 2019. The Meat Standards Australia Index indicates beef carcass quality. Animal, 13, 18.
McKiernan, WA 2005. Frame scoring of beef cattle. Retrieved on October 2019 from http://www.dpi.nsw.gov.au/agriculture/livestock/beef/appraisal/publications/frame-scoring
McKiernan, WA 2007. Muscle scoring beef cattle. Primefact 328, NSW Department of Primary Industries, pp. 1–5. Orange, NSW, Australia.
McKiernan, WA, Gaden, B and Sundstrom, B 2007. Dressing percentages for cattle. In Primefact 340, pp. 1–3. Orange, NSW, Australia.
McKiernan, WA, Wilkins, JF, Irwin, J, Orchard, B and Barwick, SA 2009. Performance of steer progeny of sires differing in genetic potential for fatness and meat yield following postweaning growth at different rates. 2. Carcass traits. Animal Production Science 49, 525534.
McPhee, MJ, Walmsley, BJ, Mayer, DG and Oddy, VH 2014. BeefSpecs fat calculator to assist decision making to increase compliance rates with beef carcass specifications: evaluation of inputs and outputs. Animal Production Science 54, 20112017.
McPhee, MJ, Walmsley, BJ, Oddy, VH, Andrews, T and Gudex, BW 2016. Enhancing BeefSpecs systems for improving market compliance of pasturefed beef in southern Australia. In MLA Final report B.SBP.00111, Meat & Livestock Australia, Sydney, Australia, pp. 1109. Retrieved on 21 June 2019 from https://www.mla.com.au/research-and-development/search-rd-reports/final-report-details/Productivity-On-Farm/Enhancing-BeefSpecs-systems-for-improving-market-compliance-of-pasturefed-beef-in-southern-Australia/3224.
MLA, Meat and Livestock Australia 2018. Tips and tools – Meat Standards Australia: the effect of marbling on beef eating quality. Retrieved on 21 June 2019 from https://www.mla.com.au/globalassets/mla-corporate/marketing-beef-and-lamb/documents/meat-standards-australia/msa07-beef-tt_the-effect-of-marbling-on-beef-eating-quality-lr.pdf
Moulton, CR, Trowbridge, PF and Haigh, LD 1922. Studies in animal nutrition. 1. Changes in form and weight on different planes of nutrition. In University of Missouri, College of Agriculture, Agricultural Experimental Station, Research Bulletin 55, Columbia, MO, USA.
Perry, D, McKiernan, W and Yeates, A 1993a. Muscle score: its usefulness in describing the potential yield of saleable meat from live steers and their carcasses. Australian Journal of Experimental Agriculture 33, 275281.
Perry, D, Yeates, A and McKiernan, W 1993b. Meat yield and subjective muscle scores in medium weight steers. Australian Journal of Experimental Agriculture 33, 825831.
Prieto, N, Navajas, EA, Richardson, RL, Ross, DW, Hyslop, JJ, Simm, G and Roehe, R 2010. Predicting beef cuts composition, fatty acids and meat quality characteristics by spiral computed tomography. Meat Science 86, 770779.
R Development Core Team 2019. R: A language and environment for statistical computing. In R Foundation for Statistical Computing, Vienna, Austria.
Sainz, RD and Bentley, BE 1997. Visceral organ mass and cellularity in growth-restricted and refed beef steers. Journal of Animal Science 75, 12291236.
Sainz, RD, De la Torre, F and Oltjen, JW 1995. Compensatory growth and carcass quality in growth- restricted and refed beef steers. Journal of Animal Science 73, 29712979.
Upton, W, Burrow, HM, Dundon, A, Robinson, DL and Farrell, EB 2001. CRC breeding program design, measurements and database: methods that underpin CRC research results. Australian Journal of Experimental Agriculture 41, 943952.
Walmsley, BJ, McPhee, MJ and Oddy, VH 2014. Development of the BeefSpecs fat calculator to assist decision making to increase compliance rates with beef carcass specifications. Animal Production Science 54, 20032010.
Watson, R, Polkinghorne, R and Thompson, JM 2008. Development of the Meat Standards Australia (MSA) prediction model for beef palatability. Australian Journal of Experimental Agriculture 48, 13681379.
Wolcott, ML, Thompson, JM and Perry, D 2001. The prediction of retail beef yield from real time ultrasound measurements on live animals at three stages through growout and finishing. Australian Journal of Experimental Agriculture 41, 10051011.

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Live animal predictions of carcass components and marble score in beef cattle: model development and evaluation

  • M. J. McPhee (a1), B. J. Walmsley (a2), H. C. Dougherty (a1) (a3), W. A. McKiernan (a1) and V. H. Oddy (a1)...

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