Hostname: page-component-cd9895bd7-gvvz8 Total loading time: 0 Render date: 2024-12-26T23:06:14.115Z Has data issue: false hasContentIssue false
  • English
  • Français

Genetic variation in wholesale carcass cuts predicted from digital images in cattle

Published online by Cambridge University Press:  03 June 2011

T. Pabiou ,
W. F. Fikse ,
P. R. Amer ,
A. R. Cromie ,
A. Näsholm  and
D. P. Berry
T. Pabiou*
Affiliation:
The Irish Cattle Breeding Federation, Highfield House, Bandon, Co. Cork, Ireland Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7070, 75009 Uppsala, Sweden
W. F. Fikse
Affiliation:
Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7070, 75009 Uppsala, Sweden
P. R. Amer
Affiliation:
AbacusBio Limited, 442 Moray Place, Dunedin 9058, New Zealand
A. R. Cromie
Affiliation:
The Irish Cattle Breeding Federation, Highfield House, Bandon, Co. Cork, Ireland
A. Näsholm
Affiliation:
Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7070, 75009 Uppsala, Sweden
D. P. Berry
Affiliation:
Animal & Grassland Research and Innovation Centre, Teagasc, Moorepark, Co. Cork, Ireland
*
†E-mail: [email protected]
Get access

Abstract

The objective of this study was to quantify the genetic variation in carcass cuts predicted using digital image analysis in commercial cross-bred cattle. The data set comprised 38 404 steers and 14 318 heifers from commercial Irish herds. The traits investigated included the weights of lower value cuts (LVC), medium value cuts (MVC), high value cuts (HVC), very high value cuts (VHVC) and total meat weight. In addition, the weights of total fat and total bones were available on the steers. Heritability of carcass cut weights, within gender, was estimated using an animal linear model, whereas genetic and phenotypic correlations among cuts were estimated using a sire linear model. Carcass weight was included as a covariate in all models. In the steers, heritability ranged from 0.13 (s.e. = 0.02) for VHVC to 0.49 (s.e. = 0.03) for total bone weight, and in the heifers heritability ranged from 0.15 (s.e. = 0.04) for MVC to 0.72 (s.e. = 0.06) for total meat weight. The coefficient of genetic variation for the different cuts varied from 1.4% to 3.6%. Genetic correlations between the different cut weights were all positive and ranged from 0.45 (s.e. = 0.08) to 0.89 (s.e. = 0.03) in the steers, and from 0.47 (s.e. = 0.14) to 0.82 (s.e. = 0.06) in the heifers. Genetic correlations between the wholesale cut weights and carcass conformation ranged from 0.32 (s.e. = 0.06) to 0.45 (s.e. = 0.07) in the steers, and from 0.10 (s.e. = 0.12) to 0.38 (s.e. = 0.09) in the heifers. Genetic correlations between the same wholesale cut traits in steers and heifers ranged from 0.54 (s.e. = 0.14) for MVC to 0.79 (s.e. = 0.06) for total meat weight; genetic correlations between carcass weight and carcass classification for conformation and fat score in both genders varied from 0.80 to 0.87. The existence of genetic variation in carcass cut traits, coupled with the routine availability of predicted cut weights from digital image analysis, clearly shows the potential to genetically improve carcass value.

Keywords

genetic parameterspredictioncarcassbeefdigital images
Type
Full Paper
Information
animal , Volume 5 , Issue 11 , 26 September 2011 , pp. 1720 - 1727
Copyright
Copyright © The Animal Consortium 2011

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

Benyshek, LL 1981. Heritabilities for growth and carcass traits estimated from data on Herefords under commercial conditions. Journal of Animal Science 53, 49–56.CrossRefGoogle Scholar
Brackelsberg, PO, Kline, EA, Willham, RL, Hazel, LN 1971. Genetic parameters for selected beef-carcass traits. Journal of Animal Science 33, 13–17.CrossRefGoogle ScholarPubMed
Conroy, SB, Drennan, MJ, McGee, M, Keane, MG, Kenny, DA, Berry, DP 2009. Predicting beef carcass meat, fat and bone proportions from carcass conformation and fat scores or hindquarter dissection. Animal 4, 234–241.CrossRefGoogle Scholar
Crump, RE, Wray, NR, Thompson, R, Simm, G 1997. Assigning pedigree beef performance records to contemporary groups taking account of within-herd calving patterns. Animal Science 65, 193–198.CrossRefGoogle Scholar
Cundiff, LV, Gregory, KE, Koch, RM, Dickerson, GE 1969. Genetic variation in total and differential growth of carcass components in beef cattle. Journal of Animal Science 29, 233–244.CrossRefGoogle ScholarPubMed
Department of Agriculture, Fisheries, and Food 2009. Beef carcases classification and price reporting section – Annual report 2009.Google Scholar
Eriksson, S, Näsholm, A, Johansson, K, Philipsson, J 2003. Genetic analysis of field recorded growth and carcass traits for Swedish beef cattle. Livestock Production Science 84, 53–62.CrossRefGoogle Scholar
Gilmour, AR, Gogel, BJ, Cullis, BR, Thompson, R 2009. ASReml user guide release 3.0. VSN International Ltd, Hemel Hempstead, HP1 1ES, UKwww.vsni.co.uk.Google Scholar
Gunsett, FC 1984. Linear index selection to improve traits defined as ratios. Journal of Animal Science 59, 1185–1193.CrossRefGoogle Scholar
Hickey, JM, Keane, MG, Kenny, DA, Cromie, AR, Veerkamp, RF 2007. Genetic parameters for EUROP carcass traits within different groups of cattle in Ireland. Journal of Animal Science 85, 314–321.CrossRefGoogle ScholarPubMed
Houle, D 1992. Comparing evolvability and variability of quantitative traits. Genetics 130, 195–204.CrossRefGoogle ScholarPubMed
Jorjani, H, Klei, L, Emanuelson, U 2003. A simple method for weighted bending of genetic (co)variance matrices. Journal of Dairy Science 86, 677–679.CrossRefGoogle ScholarPubMed
Näsholm, A 2004. Influence of sex on genetic expressions and variance of 4-month weight of Swedish lambs. Livestock Production Science 86, 137–142.CrossRefGoogle Scholar
Pabiou, T, Fikse, WF, Cromie, AR, Keane, MG, Näsholm, A, Berry, DP 2010. Use of digital images to predict carcass cut yields in cattle. Livestock Science 137, 130–140.CrossRefGoogle Scholar
Pabiou, T, Fikse, WF, Näsholm, A, Cromie, AR, Drennan, MJ, Keane, MG, Berry, DP 2009. Genetic parameters for carcass cut weight in Irish beef cattle. Journal of Animal Science 87, 3865–3876.CrossRefGoogle ScholarPubMed
Rios Utrera, A, Van Vleck, LD 2004. Heritability estimates for carcass traits of cattle: a review. Genetics and Molecular Research 3, 380–394.Google Scholar
Robertson, A 1959. The sampling variance of the genetic correlation coefficient. Biometrics 15, 469–485.CrossRefGoogle Scholar
SAS Institute 2007. User's guide version 9.1.3. SAS Institute Inc., Cary, NC, USA.Google Scholar
Stålhammar, H, Philipsson, J 1997. Sex-specific genetic parameters for weaning and post-weaning gain in Swedish beef cattle under field conditions. Acta Agriculturae Scandinavia, Section A 47, 138–147.CrossRefGoogle Scholar