Prediction of lamb carcass composition and meat quality using combinations of post-mortem measurements
Various post-mortem measurements (carcass weights, conformation and fatness classes, external carcass dimensions, eye muscle dimensions, subcutaneous fat depth, pH and temperature) were recorded on 197 Texel (TEX) and 200 Scottish Blackface (SBF) lamb carcasses. The potential use of these measuremen...
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Published in | Meat science Vol. 81; no. 4; pp. 711 - 719 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Kidlington
Elsevier Ltd
01.04.2009
[Amsterdam]: Elsevier Science Elsevier |
Subjects | |
Online Access | Get full text |
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Summary: | Various post-mortem measurements (carcass weights, conformation and fatness classes, external carcass dimensions, eye muscle dimensions, subcutaneous fat depth, pH and temperature) were recorded on 197 Texel (TEX) and 200 Scottish Blackface (SBF) lamb carcasses. The potential use of these measurements to predict carcass composition and key meat quality traits was investigated, to enable categorisation of carcasses in the abattoir and/or for use in genetic improvement programmes. By combining different measurements, accurate predictions of dissected carcass muscle weight (adjusted
R
2 0.93 in TEX, 0.88 in SBF) and fat weight (adjusted
R
2 0.84 in TEX, 0.87 in SBF) were achieved, and moderate predictions of intra-muscular fat (adjusted
R
2 0.56 in TEX, 0.48 in SBF), whilst shear force was predicted with low to moderate accuracy (adjusted
R
2
<
0.33 across breeds and cuts). Sex, eye muscle dimensions and subcutaneous fat depth improved predictions of carcass composition and intra-muscular fat, whilst pH or temperature provided little additional benefit for these traits, but increased prediction accuracies for shear force. These results could contribute to the development of automated carcass grading systems or help inform breeding decisions. |
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Bibliography: | http://dx.doi.org/10.1016/j.meatsci.2008.10.025 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0309-1740 1873-4138 |
DOI: | 10.1016/j.meatsci.2008.10.025 |