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Genetic parameters between slaughter pig efficiency and growth rate of different body tissues estimated by computed tomography in live boars of Landrace and Duroc

Published online by Cambridge University Press:  19 August 2011

E. Gjerlaug-Enger ,
J. Kongsro ,
J. Ødegård ,
L. Aass  and
O. Vangen
E. Gjerlaug-Enger*
Affiliation:
Department of Animal and Aquaculture Sciences, Norwegian University of Life Sciences, PO Box 5003, 1432 Ås, Norway Norsvin, PO Box 504, 2304 Hamar, Norway
J. Kongsro
Affiliation:
Norsvin, PO Box 504, 2304 Hamar, Norway
J. Ødegård
Affiliation:
Nofima Marin, PO Box 5010, 1432 Ås, Norway
L. Aass
Affiliation:
Department of Animal and Aquaculture Sciences, Norwegian University of Life Sciences, PO Box 5003, 1432 Ås, Norway
O. Vangen
Affiliation:
Department of Animal and Aquaculture Sciences, Norwegian University of Life Sciences, PO Box 5003, 1432 Ås, Norway
*
†E-mail: eli.gjerlaug@norsvin.no
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Abstract

In this study, computed tomography (CT) technology was used to measure body composition on live pigs for breeding purposes. Norwegian Landrace (L; n = 3835) and Duroc (D; n = 3139) boars, selection candidates to be elite boars in a breeding programme, were CT-scanned between August 2008 and August 2010 as part of an ongoing testing programme at Norsvin's boar test station. Genetic parameters in the growth rate of muscle (MG), carcass fat (FG), bone (BG) and non-carcass tissue (NCG), from birth to ∼100 kg live weight, were calculated from CT data. Genetic correlations between growth of different body tissues scanned using CT, lean meat percentage (LMP) calculated from CT and more traditional production traits such as the average daily gain (ADG) from birth to 25 kg (ADG1), the ADG from 25 kg to 100 kg (ADG2) and the feed conversion ratio (FCR) from 25 kg to 100 kg were also estimated from data on the same boars. Genetic parameters were estimated based on multi-trait animal models using the average information–restricted maximum likelihood (AI-REML) methodology. The heritability estimates (s.e. = 0.04 to 0.05) for the various traits for Landrace and Duroc were as follows: MG (0.19 and 0.43), FG (0.53 and 0.59), BG (0.37 and 0.58), NCG (0.38 and 0.50), LMP (0.50 and 0.57), ADG1 (0.25 and 0.48), ADG2 (0.41 and 0.42) and FCR (0.29 and 0.42). Genetic correlations for MG with LMP were 0.55 and 0.68, and genetic correlations between MG and ADG2 were −0.06 and 0.07 for Landrace and Duroc, respectively. LMP and ADG2 were clearly unfavourably genetically correlated (L: −0.75 and D: −0.54). These results showed the difficulty in jointly improving LMP and ADG2. ADG2 was unfavourably correlated with FG (L: 0.84 and D: 0.72), thus indicating to a large extent that selection for increased growth implies selection for fatness under an ad libitum feeding regime. Selection for MG is not expected to increase ADG2, but will yield faster growth of the desired tissues and a better carcass quality. Hence, we consider MG to be a better biological trait in selection for improved productivity and carcass quality. CT is a powerful instrument in conjunction with breeding, as it combines the high accuracy of CT data with measurements taken from the selection candidates. CT also allows the selection of new traits such as real body composition, and in particular, the actual MG on living animals.

Keywords

computed tomographybody compositionlean meat growthmuscle growthgenetic parameters
Type
Full Paper
Information
animal , Volume 6 , Issue 1 , January 2012 , pp. 9 - 18
Copyright
Copyright © The Animal Consortium 2011

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References

Afonso, JJM 1992. Factors affecting growth and body composition in sheep. PhD, University of New England.Google Scholar
Bennett, GL 1992. Predicting lean growth while accounting for correlated traits. Journal of Animal Science 70, 51–56.Google Scholar
Bidanel, JP, Ducos, A 1996. Genetic correlations between test station and on-farm performance traits in Large White and French Landrace pig breeds. Livestock Production Science 45, 55–62.Google Scholar
Cameron, ND 1994. Selection for components of efficient lean growth-rate in pigs. 1. Selection pressure applied and direct responses in a Large White Herd. Animal Production 59, 251–262.Google Scholar
Cameron, ND, Curran, MK 1994. Selection for components of efficient lean growth-rate in pigs. 2. Selection pressure applied and direct responses in a Landrace Herd. Animal Production 59, 263–269.Google Scholar
Chen, P, Baas, TJ, Mabry, JW, Dekkers, JCM, Koehler, KJ 2002. Genetic parameters and trends for lean growth rate and its components in US Yorkshire, Duroc, Hampshire, and Landrace pigs. Journal of Animal Science 80, 2062–2070.Google Scholar
Chimonyo, M, Dzama, K 2007. Estimation of genetic parameters for growth performance and carcass traits in Mukota pigs. Animal 1, 317–323.CrossRefGoogle ScholarPubMed
Cleveland, ER, Cunningham, PJ, Peo, ER 1982. Selection for Lean Growth in Swine. Journal of Animal Science 54, 719–727.Google 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. CAB International, Wallingford, UK.Google Scholar
de Vries, AG, van der Wal, PG, Long, T, Eikelenboom, G, Merks, JWM 1994. Genetic parameters of pork quality and production traits in Yorkshire populations. Livestock Production Science 40, 277–289.CrossRefGoogle Scholar
Ducos, A, Bidanel, JP, Ducrocq, V, Boichard, D, Groeneveld, E 1993. Multivariate restricted maximum-likelihood-estimation of genetic-parameters for growth, carcass and meat quality traits in French Large White and French Landrace pigs. Genetics Selection Evolution 25, 475–493.CrossRefGoogle Scholar
Fowler, VR, Bichard, M, Pease, A 1976. Objectives in pig breeding. Animal Production 23, 365–387.Google Scholar
Gilbert, H, Bidanel, JP, Gruand, J, Caritez, JC, Billon, Y, Guillouet, P, Lagant, H, Noblet, J, Sellier, P 2007. Genetic parameters for residual feed intake in growing pigs, with emphasis on genetic relationships with carcass and meat quality traits. Journal of Animal Science 85, 3182–3188.CrossRefGoogle ScholarPubMed
Gjerlaug-Enger, E, Aass, L, Ødegård, J, Kongsro, J, Vangen, O 2010a. Genetic parameters of fat quality in pig measured by near infrared spectroscopy. Animal, in press; doi:10.1017/S1751731111000528.CrossRefGoogle Scholar
Gjerlaug-Enger, E, Aass, L, Ødegård, J, Vangen, O 2010b. Genetic parameters of meat quality traits in two pig breeds measured by rapid methods. Animal 4, 1832–1843.CrossRefGoogle ScholarPubMed
Hammond, J 1950. Measuring growth in farm animals. Proceedings of the Royal Society of London Series B-Biological Sciences 137, 452–461.Google ScholarPubMed
Hermesch, S 2004. Genetic improvement of lean meat growth and feed efficiency in pigs. Australian Journal of Experimental Agriculture 44, 383–391.Google Scholar
Hermesch, S, Luxford, BG, Graser, HU 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.Google Scholar
Hermesch, S, Kanis, E, Eissen, JJ 2003. Economic weights for feed intake in the growing pig derived from a growth model and an economic model. Journal of Animal Science 81, 895–903.Google Scholar
Hetzer, HO, Miller, RH 1972. Rate of growth as influenced by selection for high and low fatness in Swine. Journal of Animal Science 35, 730–742.CrossRefGoogle Scholar
Hoque, MA, Suzuki, K, Kadowaki, H, Shibata, T, Oikawa, T 2007. Genetic parameters for feed efficiency traits and their relationships with growth and carcass traits in Duroc pigs. Journal of Animal Breeding and Genetics 124, 108–116.Google Scholar
Jones, HE, Lewis, RM, Young, MJ, 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
Kohn, F, Sharifi, AR, Simianer, H 2007. Modeling the growth of the Goettingen minipig. Journal of Animal Science 85, 84–92.Google 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
Kolstad, K, Vangen, O 1996. Breed differences in maintenance requirements of growing pigs when accounting for changes in body composition. Livestock Production Science 47, 23–32.CrossRefGoogle Scholar
Kolstad, K, Vegusdal, A, Baeverfjord, G, Einen, O 2004. Quantification of fat deposits and fat distribution in Atlantic halibut (Hippoglossus hippoglossus L.) using computerised X-ray tomography (CT). Aquaculture 229, 255–264.CrossRefGoogle Scholar
Kongsro, J, Roe, M, Aastveit, AH, Kvaal, K, Egelandsdal, B 2008. Virtual dissection of lamb carcasses using computer tomography (CT) and its correlation to manual dissection. Journal of Food Engineering 88, 86–93.CrossRefGoogle Scholar
Krieter, J, Kalm, E 1989. Growth, feed-intake and mature size in Large White and Pietrain pigs. Journal of Animal Breeding and Genetics-Zeitschrift Fur Tierzuchtung Und Zuchtungsbiologie 106, 300–311.Google Scholar
Kvame, T, Vangen, O 2007. Selection for lean weight based on ultrasound and CT in a meat line of sheep. Livestock Science 106, 232–242.Google Scholar
Luiting, P, Kolstad, K, Enting, H, Vangen, O 1995. Pig breed comparison for body-composition at maintenance – analysis of computerized-tomography data by mixture distributions. Livestock Production Science 43, 225–234.CrossRefGoogle Scholar
Madsen, P, Jensen, J 2008. A user's guide to DMU. A package for analysing multivariate mixed models. Version 6, release 4.7. Danish Institute of Agricutural Sciences (DIAS), Department of Animal Breeding and Genetics, Research Center Foulum, Tjele, Denmark.Google Scholar
Mcphee, CP, Brennan, PJ, Duncalfe, F 1979. Genetic and phenotypic parameters of Australian Large White and Landrace Boars performance-tested when offered food ad-libitum. Animal Production 28, 79–85.Google Scholar
Mrode, RA, Kennedy, BW 1993. Genetic-variation in measures of food efficiency in pigs and their genetic-relationships with growth-rate and backfat. Animal Production 56, 225–232.Google Scholar
Solanes, FX, Reixach, J, Tor, M, Tibau, J, Estany, J 2009. Genetic correlations and expected response for intramuscular fat content in a Duroc pig line. Livestock Science 123, 63–69.CrossRefGoogle Scholar
Sonesson, AK, de Greef, KH, Meuwissen, THE 1998. Genetic parameters and trends of meat quality, carcass composition and performance traits in two selected lines of large white pigs. Livestock Production Science 57, 23–32.CrossRefGoogle Scholar
Stern, S, Johansson, K, Rydhmer, L, Andersson, K 1993. Performance testing of pigs for lean tissue-growth rate in a selection experiment with low and high-protein diets.1. Experimental-design and efficiency of selection. Acta Agriculturae Scandinavica Section A – Animal Science 43, 136–143.Google Scholar
Suzuki, K, Irie, M, Kadowaki, H, Shibata, T, Kumagai, M, Nishida, A 2005. Genetic parameter estimates of meat quality traits in Duroc pigs selected for average daily gain, longissimus muscle area, backfat thickness, and intramuscular fat content. Journal of Animal Science 83, 2058–2065.CrossRefGoogle ScholarPubMed
Vangen, O 1977. Studies on A 2 trait selection experiment in pigs. 1. Growth, feed consumption and feed conversion ratio after 10 years of selection for growth-rate and backfat thickness. Acta Agriculturae Scandinavica 27, 331–340.Google Scholar
Vangen, O 1979. Studies on A 2 trait selection experiment in pigs. 2. Genetic changes and realized genetic-parameters in the traits under selection. Acta Agriculturae Scandinavica 29, 305–319.CrossRefGoogle Scholar
Vangen, O, Thompson, J 1992. The use of CAT-scanning to measure maintenance efficiency in genetic lines of sheep. In: Spain, 43rd Meeting of the European Association for Animal Production.Google Scholar
Webster, AJF 1977. Selection for leanness and energetic efficiency of growth in meat animals. Proceedings of the Nutrition Society 36, 53–59.Google Scholar
Webster, AJF 1981. The energetic efficiency of metabolism. Proceedings of the Nutrition Society 40, 121–128.CrossRefGoogle ScholarPubMed