Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-18T14:08:05.751Z Has data issue: false hasContentIssue false
  • English
  • Français

Predicting carcass composition of terminal sire sheep using X-ray computed tomography

Published online by Cambridge University Press:  09 March 2007

J. M. Macfarlane ,
R. M. Lewis ,
G. C. Emmans ,
M. J. Young  and
G. Simm
J. M. Macfarlane*
Affiliation:
Sustainable Livestock Systems Group, Scottish Agricultural College, West Mains Road, Edinburgh, EH9 3JG, UK
R. M. Lewis
Affiliation:
Sustainable Livestock Systems Group, Scottish Agricultural College, West Mains Road, Edinburgh, EH9 3JG, UK Department of Animal and Poultry Sciences (0306), Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, USA
G. C. Emmans
Affiliation:
Sustainable Livestock Systems Group, Scottish Agricultural College, West Mains Road, Edinburgh, EH9 3JG, UK
M. J. Young
Affiliation:
Sustainable Livestock Systems Group, Scottish Agricultural College, West Mains Road, Edinburgh, EH9 3JG, UK Sheep Improvement Ltd, PO Box 66, Lincoln University, Canterbury, New Zealand
G. Simm
Affiliation:
Sustainable Livestock Systems Group, Scottish Agricultural College, West Mains Road, Edinburgh, EH9 3JG, UK
*
†E-mail: [email protected]
Get access

Abstract

The best means to utilize X-ray computed tomography (CT) and ultrasound to predict carcass lean, fat and bone weights in vivo in terminal sire sheep were tested. Data on 160 lambs from three breeds were considered: 50 Suffolk males, 50 Suffolk females, 40 Texel males and 20 Charollais males. One-fifth of the lambs within each breed and sex group were slaughtered at each of 14, 18 and 22 weeks of age and the remaining two-fifths at 26 weeks. Carcasses were dissected into lean, fat and bone weights. Prior to slaughter all lambs were CT scanned, with cross-sectional scans taken at seven sites along the body (ischium, hip, mid shaft of femur, 2nd and 5th lumbar vertebrae and 6th and 8th thoracic vertebrae), and ultrasound scanned at the 3rd lumbar vertebra and 13th rib.A set of three CT scans that reliably predicted carcass lean, fat and bone weights was identified which included a scan in each of the three main carcass regions: ischium in the hind leg, 5th lumbar vertebra in the loin and 8th thoracic vertebra in the shoulder. Breed and sex affected the intercepts of the prediction equations but not their slopes. Therefore, a minimal set of equations is likely to be sufficient to predict tissue weights, at least within terminal sire sheep breeds. Equations derived showed high degrees of fit to the data with R2 values of 0·924, 0·978 and 0·830 for lean, fat and bone weights, respectively, when predicted using CT alone, and 0·589 and 0·857 for lean and fat weights, respectively, when predicted using ultrasound alone. Using live weight in addition to CT information only improved prediction accuracy slightly for lean (0·966) and fat (0·986) although more substantially for bone (0·925). Where live and tissue weights are considered contemporaneously in genetic evaluations, excluding live weight from prediction may therefore be preferable to avoid colinearity among weight measures.

Keywords

carcass compositioncomputed tomographypredictionscanningsheep
Type
Research Article
Information
Animal Science , Volume 82 , Issue 3 , June 2006 , pp. 289 - 300
Copyright
Copyright © British Society of Animal Science 2006

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alliston, J. C. 1983. Evaluation of carcass quality in the live animal. In Sheep production (ed. Haresign, W.), pp. 75–95. Butterworths, London.Google Scholar
Bishop, S. C. 1994. Genetic relationships between predicted and dissected carcass composition in Scottish Blackface sheep. Animal Production 59: 321–478.Google Scholar
Cuthbertson, A., Harrington, G. and Smith, R.J. 1972. Tissue separation–to assess beef and lamb variation. Proceedings of the British Society of Animal Production, 1972, pp. 113–122.Google Scholar
Genstat 6 Committee. 2002. Genstat Committee, PC/Windows NT version. Lawes Agricultural Trust, Rothamsted Experimental Station, HarpendenGoogle Scholar
Jones, H. E., Lewis, R. M., Young, M. J. and Simm, G. 2004. Genetic parameters for carcass composition and muscularity in sheep measured by X-ray computer tomography, ultrasound and dissection. Livestock Production Science 90: 167–179.CrossRefGoogle Scholar
Jones, H. E., Lewis, R. M., Young, M. J. and Wolf, B. T. 2002a. The use of X-ray computer tomography for measuring the muscularity of live sheep. Animal Science 75: 387–399.CrossRefGoogle Scholar
Jones, H. E., Lewis, R. M., Young, M. J., Wolf, B. T. and Warkup, C. C. 2002b. Changes in muscularity with growth and its relationships with other carcass traits in Suffolk, Charollais and Texel breeds of sheep. Animal Science 74: 265–275.CrossRefGoogle Scholar
Jopson, N. B., Amer, P. R. and McEwan, J. C. 2004b. Comparison of two-stage selection breeding programmes for terminal sire sheep. Proceedings of the New Zealand Society of Animal Production 64: 212–216.Google Scholar
Jopson, N. B., McEwan, J. C., Dodds, K. G. and Young, M. J. 1995. Economic benefits of including computed tomography measurements in sheep breeding programmes. Proceedings of the Australian Association of Animal Breeding and Genetics 11: 194–197.Google Scholar
Jopson, N. B., McEwan, J. C., Fennessy, P. F., Dodds, K. G., Nicoll, G. B. and Wade, C. M. 1997. Economic benefits of including computer tomography measurements in a large terminal sire breeding programme. Proceedings of the Association for the Advancement of Animal Breeding and Genetics 12: 72–76.Google Scholar
Kempster, A. J. 1983. Carcass quality and its measurement in sheep. In Sheep production (ed. Haresign, W.), pp. 59–74. Butterworths, London.Google Scholar
Lambe, N. R., Young, M. J., McLean, K. A., Conington, J. and Simm, G. 2003. Prediction of total body tissue weights in Scottish Blackface ewes using computed tomography scanning. Animal Science 76: 191–197.CrossRefGoogle Scholar
Lawrence, T. L. J. and Fowler, V. R. 2002. Growth of farm animals, second edition. CABI, Wallingford.CrossRefGoogle Scholar
Lewis, R. M. and Simm, G. 2002. Small ruminant breeding programmes for meat: progress and prospects. Proceedings of the seventh world congress on genetics applied to livestock production, CD-ROM communication no. 02–01.Google Scholar
McCullagh, P. and Nelder, J. A. 1989. Generalized linear models, second edition. Chapman and Hall, London.CrossRefGoogle Scholar
Nicoll, G. B., McEwan, J. C., Dodds, K. G. and Jopson, N. B. 1997. Genetic improvement in Landcorp Lamb Supreme terminal sire flocks. Association for the Advancement of Animal Breeding and Genetics 12: 68–71.Google Scholar
Sehested, E. 1984. Computerised tomography in sheep. In vivo measurement of body composition in meat animals (ed. Lister, D.), pp. 67–74. Elsevier, London.Google Scholar
Simm, G. 1987. Carcass evaluation in sheep breeding programmes. In New techniques in sheep production (ed. Marai, I. F. M. and Owen, J. B.), pp. 125–144. Butterworths, London.CrossRefGoogle Scholar
Simm, G. 1994. Developments in improvement of meat sheep. Proceedings of the fifth world congress on genetics applied to livestock production, vol. 18, pp. 3–10.Google Scholar
Simm, G. and Dingwall, W. S. 1989. Selection indices for lean meat production in sheep. Livestock Production Science 21: 223–233.CrossRefGoogle Scholar
Simm, G., Lewis, R. M., Grundy, B. and Dingwall, W. S. 2002. Responses to selection for lean growth in sheep. Animal Science 74: 39–50.CrossRefGoogle Scholar
Stanford, K., Jones, S. D. M. and Price, M. A. 1998. Methods of predicting lamb carcass composition: a review. Small Ruminant Research 29: 241–254.CrossRefGoogle Scholar
Vangen, O. and Jopson, N.B. 1996. Research application of non-invasive techniques for body composition. Proceedings of the 47th annual meeting of the European Association for Animal Production, Lillehammer, Norway, pp. 25–29.Google Scholar
Vangen, O., Kvame, T., Haugen, S., Avdem, F. and Eikje, S. 2003. Use of a meat sheep sire line to improve product quality in a national sheep breeding system. Proceedings of the 54th annual meeting of the European Association for Animal Production, Rome, Italy.Google Scholar
Ward, C. E., Trent, A. and Hildebrand, J. L. 1995. Consumer perceptions of lamb compared with other meats. Sheep and Goat Research Journal 11: 64–70.Google Scholar
Wolf, B. T., Jones, D. A. and Owen, M. G. 2001. Carcass composition, conformation and muscularity in Texel lambs of different breeding history, sex and leg shape score. Animal Science 72: 465–475.CrossRefGoogle Scholar
Wolf, B. T., Smith, C., King, J. W. B. and Nicholson, D. 1981. Genetic parameters of growth and carcass composition in crossbred lambs. Animal Production 32: 1–7.Google Scholar
Woodward, J. and Wheelock, V. 1990. Consumer attitudes to fat in meat. In Reducing fat in meat animals (ed. Wood, J. D. and Fisher, A. V.), pp. 66–100. Elsevier, London.Google Scholar
Young, M. J., Nsoso, S. J., Logan, C. M. and Beatson, P. R. 1996. Prediction of carcass tissue weight in vivo using live weight, ultrasound or X-ray CT measurements. Proceedings of the New Zealand Society of Animal Production 56: 205–211.Google Scholar
Young, M.J., Simm, G. and Glasbey, C.A. 2001. Computerised tomography for carcass analysis. Proceedings of the British Society of Animal Science, pp. 250–254.Google Scholar