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Selection for components of efficient lean growth rate in pigs 1. Selection pressure applied and direct responses in a Large White herd

Published online by Cambridge University Press:  02 September 2010

N. D. Cameron
N. D. Cameron
Affiliation:
Roslin Institute (Edinburgh), Roslin, Midlothian EH25 9PS
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Abstract

Responses to four generations of divergent selection for lean groivth rate with ad-libitum feeding (LGA), for lean food conversion (LFC) and for daily food intake (DFI) in Large White pigs were studied. The LGA (LFC) selection criterion was designed to obtain equal correlated responses in growth rate (food conversion ratio) and carcass lean content, measured in phenotypic s.d. The selection criteria had phenotypic s.d. of 27, 29 and 253 units, respectively, and results are presented in s.d. units. There was a total of 3537 pigs, with an average of 40 boars and 40 gilts performance tested in each of the high, low and control lines per generation and the lines consisted of 10 sires and 20 dams. The generation interval was equal to 13·5 months. Animals were performance tested in individual pens with mean starting and finishing weights of 30 kg and 85 kg respectively.

Cumulative selection differentials in the three selection groups were 5·8, 3·6 and 3·3 phenotypic s.d. for LGA, LFC and DFI respectively. Direct responses to divergent selection were 1·7, 1·3 and 1·2 (s.e. 0·17) for LGA, LFC and DFI. The correlated response in LFC (1·6 (s.e. 0·18)) with selection on LGA was greater than the direct response in LFC. Conversely, the direct response in LGA was greater than the correlated response (1·1 (s.e. 0·18)) with selection on LFC. The response in LFC (–1·1 (s.e. 0·17)) with selection on DFI was similar in size but opposite in sign to the direct response in LFC. Responses were asymmetric about the control, as the high LGA and LFC responses were proportionately smaller (0·74 and 0·58) than low line responses. In contrast, the difference between the high DFI and control was four times greater than the difference between low line and control.

Heritabilities of LGA, LFC and DFI were 0·38, 0·35 and 0·29 (s.e. 0·03), when estimated by residual maximum likelihood, with common environmental effects of 0·09 (s.e. 0·02). Genetic correlations for LGA with LFC and DFI were positive, 0·76 (s.e. 0·03) and 0·23 (s.e. 0·07), but the genetic correlation between DFI and LFC was negative, –0·45 (s.e. 0·06). The experiment demonstrated that substantial responses to selection can be achieved in LGA, LFC and DFI. Selection on LGA resulted in larger direct and correlated responses than selection on LFC.

Keywords

food intakegenetic parameterslean growthpigsselection
Type
Research Article
Information
Animal Production , Volume 59 , Issue 2 , October 1994 , pp. 251 - 262
Copyright
Copyright © British Society of Animal Science 1994

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References

Atkins, K. D. and Thompson, R. 1986. Predicted and realized responses to selection for an index of bone length and body weight in Scottish Blackface sheep. 1. Responses in the index and component traits. Animal Production 43: 421–435.Google Scholar
Cameron, N. D., Curran, M. K. and Thompson, R. 1988. Estimation of sire with feeding regime interaction in pigs. Animal Production 46: 87–95.Google Scholar
Cleveland, E. R., Cunningham, P. J. and Peo, E. R. 1982. Selection for lean growth in swine. Journal of Animal Science 54: 719–727.CrossRefGoogle Scholar
Crump, R. E. 1992. Quantitative genetic analysis of a commercial pig population undergoing selection. Ph.D. thesis, University of Edinburgh.Google Scholar
Ellis, M., Chadwick, J. P., Smith, W. C. and Laird, R. 1988. Index selection for improved growth and carcass characteristics in a population of Large White pigs. Animal Production 46: 265–275.Google Scholar
Falconer, D. S. 1981. Introduction to quantitative genetics. 2nd ed. Longman, London.Google Scholar
Fowler, V. R., Bichard, M. and Pease, A. 1976. Objectives in pig breeding. Animal Production 23: 365–387.Google Scholar
Graser, H. U., Smith, S. P. and Tier, B. 1987. A derivativefree approach for estimating variance components in animal models by restricted maximum likelihood. Journal of Animal Science 64: 1362–1370.CrossRefGoogle Scholar
Haer, L. C. M. de and Vries, A. G. de. 1993. Effects of genotype and sex on the food intake pattern of group housed growing pigs. Livestock Production Science 36: 223–232.CrossRefGoogle Scholar
Hill, W. G. 1971. Design and efficiency of selection experiments for estimating genetic parameters. Biometrics 27: 293–311.Google Scholar
Hill, W. G. 1972. Estimation of realised heritabilities from selection experiments. 1. Divergent selection. Biometrics 28: 747–765.CrossRefGoogle Scholar
Hill, W. G. 1990. Considerations in the design of animal breeding experiments. In Advances in statistical methods genetic improvement of livestock (ed. Gianola, D. and Hammond, K.), pp. 59–76. Springer-Verlag, Berlin.CrossRefGoogle Scholar
Jungst, S. B., Christian, L. L. and Kuhlers, D. L. 1981. Response to selection for feed efficiency in individually fed Yorkshire boars. Journal of Animal Science 53: 323–331.CrossRefGoogle Scholar
Kennedy, B. W., Johansson, K. and Hudson, G. F. S. 1985. Heritabilities and genetic correlations for backfat and age at 90 kg in performance-tested pigs. Journal of Animal Science 61: 78–82.CrossRefGoogle Scholar
Kuhlers, D. L. and Jungst, S. B. 1991a. Mass selection for increased 200-day weight in a closed line of Duroc pigs. Journal of Animal Science 69: 507–516.CrossRefGoogle Scholar
Kuhlers, D. L. and Jungst, S. B. 1991b. Mass selection for increased 200-day weight in a closed line of Landrace pigs. Journal of Animal Science 69: 977–984.Google Scholar
Lawes Agricultural Trust. 1983. GENSTAT A general statistical program. Numerical Algorithms Group Limited. McPhee, C. P. 1981. Selection for efficient lean growth in a pig herd. Australian journal of Agricultural Research 32: 681–690.Google Scholar
Meyer, K. 1989. Restricted maximum likelihood to estimate variance components for animal models with several random effects using a derivative-free algorithm. Genctique, Selection et Evolution 21: 317–340.CrossRefGoogle Scholar
Mrode, R. A., Smith, C. and Thompson, R. 1990. Selection for rate and efficiency of lean gain in Hereford cattle. 1. Selection pressure applied and direct responses. Animal Production 51: 23–34.Google Scholar
Robertson, A. 1959. The sampling variance of the genetic correlation coefficient. Biometrics 15: 469–485.CrossRefGoogle Scholar
Sather, A. P. and Fredeen, H. T. 1978. Effects of selection for lean growth rate upon feed utilisation by the market hog. Canadian journal of Animal Science 58: 285–289.CrossRefGoogle Scholar
Simm, G., Smith, C. and Thompson, R. 1987. The use of product traits such as lean growth rate as selection criteria in animal breeding. Animal Production 45: 307–316.Google Scholar
Smith, S. P. and Graser, H. U. 1986. Estimating variance components in a class of mixed models by restricted maximum likelihood. Journal of Dairy Science 69: 1156–1165.CrossRefGoogle Scholar
Southwood, O. I., Simpson, S. P., Curran, M. K. and Webb, A. J. 1988. Frequency of the halothane gene in British Landrace and Large White pigs. Animal Production 46: 97–102.Google Scholar
Standal, N. and Vangen, O. 1985. Genetic variation and covariation in voluntary feed intake in pig selection programmes. Livestock Production Science 12: 367–377.Google Scholar
Thompson, R. 1982. Methods of estimation of genetic parameters. Proceedings of second world congress on genetics applied to livestock production, Madrid, vol. 5, pp. 95–103.Google Scholar
Thompson, R. and Atkins, K. D. 1994. Sources of information for estimating heritability from selection experiments. Genctical Research 63: 49–55.CrossRefGoogle Scholar
Thompson, R. and Hill, W. G. 1990. Univariate REML analyses for multivariate data with the animal model. Proceedings of fourth world congress on genetics applied to livestock production, vol. 13, pp. 484–487.Google Scholar
Thompson, R, and Juga, J. 1989. Cumulative selection differentials and realized heritabilities. Animal Production 49: 203–208.Google Scholar
Tier, B. and Smith, S. P. 1989. Use of sparse matrix absorption in animal breeding. Genetics, Selection, Evolution 21: 457–466.CrossRefGoogle Scholar
Vangen, O. 1979. Studies on a two trait selection experiment in pigs. 2. Genetic changes and realised genetic parameters in the traits under selection. Acta Agriculturae Scandinavian 29: 305–319.Google Scholar
Vangen, O. 1980. Studies on a two trait selection experiment in pigs. 3. Correlated responses in daily feed intake, feed conversion and carcass traits. Acta Agriculturae Scandinavica 30: 125–141.CrossRefGoogle Scholar
Van Vleck, D. 1988. Notes on the theory and applications of selection principles for the genetic improvement of animals.Cornell University, Ithaca.Google Scholar
Webb, A. J. and Curran, M. K. 1986. Selection regime by production system interaction in pig improvement: a review of possible causes and solutions. Livestock Production Science 14: 41–54.CrossRefGoogle Scholar
Webb, A. J. and King, J. W. B. 1983. Selection for improved food conversion ratio on ad libitum group feeding in pigs. Animal Production 37: 375–385.Google Scholar
Williams, D. A. 1982. The use of the deviance to test the goodness of fit of a logistic-linear model to binary data. GLIM Newsletter 6: 60–62.Google Scholar
Wyllie, D., Morton, J. R. and Owen, J. B. 1979. Genetic aspects of voluntary food intake in the pig and their association with gain and food conversion efficiency. Animal Production 28: 381–390.Google Scholar