Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-26T10:34:35.072Z Has data issue: false hasContentIssue false
  • English
  • Français

Genetic relationships between composition of pork bellies and performance, carcase and meat quality traits

Published online by Cambridge University Press:  01 August 2008

S. Hermesch
S. Hermesch*
Affiliation:
Animal Genetics and Breeding Unit (AGBU), University of New England, Armidale, Australia
*
E-mail: [email protected]
Get access

Abstract

Belly traits including predicted fat percentage of the belly (FATPC), combined area of the rib bone and muscle (RBMA), intermuscular fat area (IMFA) and subcutaneous fat area (SFA) were recorded on 2403 pigs along with carcase fat depth at the P2 site (P2). Belly traits were derived from image analysis of the anterior side of pork bellies. Further data available for pigs with belly data and their contemporaries included lifetime growth rate, ultrasound backfat and loin muscle depth (35 406 records), along with meat quality traits (3935 records). There were 4586 feed intake records and 18 398 juvenile insulin-like growth factor-I (IGF-I) records available, which included the majority of pigs with belly data. Genetic parameters were estimated based on an animal model using Residual Maximum Likelihood procedures. Heritability estimates for belly traits ranged from 0.23 to 0.34 (±0.05 to 0.06) while the common litter effect varied from 0.04 to 0.07 (±0.03). Genetic correlations between FATPC, individual belly fat measurements and carcase P2 fat depth differed significantly from unity, ranging from 0.71 to 0.85 (±0.05 to 0.08). Genetic correlations between IMFA and subcutaneous fat measurements varied from 0.47 to 0.63 (±0.08 to 0.13). Genetic correlations between belly and performance traits show that selection for reduced juvenile-IGF-I, reduced feed intake and reduced backfat along with increased loin muscle depth will reduce overall fat levels in the belly. Only loin muscle depth had a significant genetic correlation with RBMA (0.32 ± 0.10), thereby assisting selection for improved lean meat content of the belly. Ultimately, genetic improvement of belly muscles requires specific measurements of lean meat content of the belly. For this to be effective, measurements are required that can be routinely recorded on the slaughter line, or preferably on the live animal.

Keywords

belly compositiongenetic parametersfeed intakepig
Type
Full Paper
Information
animal , Volume 2 , Issue 8 , August 2008 , pp. 1178 - 1185
Copyright
Copyright © The Animal Consortium 2008

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.)

Footnotes

a

AGBU is a joint venture of NSW Department of Primary Industries and University of New England.

References

Baulain, U, Henne, H 1999. Variation of lean content in pig bellies of dam lines. Archiv für Tierzucht 42, 593–600.Google Scholar
Bunter, KL, Hermesch, S, Luxford, BG, Graser, H-U, Crump, RE 2005. Insulin-like growth factor-I measured in juvenile pigs is genetically correlated with economically important performance traits. Australian Journal of Experimental Agriculture 45, 783–792.CrossRefGoogle Scholar
Clutter, AC, Brascamp, EW 1998. Genetics of performance traits. In The genetics of the pig (ed. MF Rothschild and A Ruvinsky), pp. 427–462. CABI Publishing, Wallingford, UK.Google Scholar
Gilmour AR, Cullis BR, Welham SJ and Thompson R 1999. NSW Agriculture Biometric Bulleting No. 3. ASReml Reference Manual. NSW Agriculture, Orange, NSW, Australia.Google Scholar
Hermesch, S 2004. Genetic improvement of lean meat growth and feed efficiency in pigs. Australian Journal of Experimental Agriculture 44, 383–391.CrossRefGoogle Scholar
Hermesch, S, Luxford, BG, Graser, H-U 2000. Genetic parameters for lean meat yield, meat quality, reproduction and feed efficiency traits for Australian pigs. 1. Description of traits and heritability estimates. Livestock Production Science 65, 239–248.CrossRefGoogle Scholar
Kolstad, K 2001. Fat deposition and distribution measured by computer tomography in three genetic groups of pigs. Livestock Production Science 67, 281–292.CrossRefGoogle Scholar
Kouba, M, Bonneau, M, Noblet, J 1999. Relative development of subcutaneous, intermuscular, and kidney fat in growing pigs with different body compositions. Journal of Animal Science 77, 622–629.CrossRefGoogle ScholarPubMed
McSweeny JM 2002. Genetic analysis of feed intake patterns and performance traits recorded in group-housed pigs. Masters’ thesis, University of New England, Australia.Google Scholar
Newcom, DW, Baas, TJ, Mabry, JW, Goodwin, RN 2002. Genetic parameters for pork carcass components. Journal of Animal Science 80, 3099–3106.CrossRefGoogle ScholarPubMed
Statistical Analysis Systems Institute 1999. SAS user’s guide, version 8, http://v8doc.sas.com/sashtml. SAS Institute Inc., Cary, NC, USA.Google Scholar
Seifert, H, Zimmermann, P, Seifert, G, Kumpfert, L 2002. Tissue differentiation of pork by way of ultrasonic measuring process – Method for an objective classification of belly quality. Fleischwirtschaft 82, 100–103.Google Scholar
Shaw, T, Rosetto, J 2003. Belly fat determination using digital analysis. In Manipulating pig production IX (ed. JE Paterson), p. 22. Australasian Pig Science Association (Inc.), Werribee, Australia.Google Scholar
Sönnichsen, M, Dobrowolski, A, Höreth, R, Branscheid, W 2002. Commercial valuation of pig carcases by using Video Image Analysis. Fleischwirtschaft 82, 98–101.Google Scholar
Tholen, E, Brandt, H, Henne, H, Stork, FJ, Schellander, K 2001. Genetic foundation of AutoFOM-traits. Archiv für Tierzucht 44, 167–179.Google Scholar
Tholen, E, Baulain, U, Henning, MD, Schellander, K 2003. Comparison of different methods to assess the composition of pig bellies in progeny testing. Journal of Animal Science 81, 1177–1184.CrossRefGoogle ScholarPubMed