Hostname: page-component-848d4c4894-tn8tq Total loading time: 0 Render date: 2024-06-19T06:26:13.506Z Has data issue: false hasContentIssue false

Genetic parameters for growth and carcass traits of Japanese Black (Wagyu) cattle

Published online by Cambridge University Press:  18 August 2016

T. Oikawa
Affiliation:
Faculty of Agriculture, Okayama University, Okayama 700-8530, Japan
T. Sanehira
Affiliation:
Faculty of Agriculture, Okayama University, Okayama 700-8530, Japan
K. Sato
Affiliation:
Faculty of Agriculture, Okayama University, Okayama 700-8530, Japan
Y. Mizoguchi
Affiliation:
Okayama Prefecture Animal Industry Center, Asahi-cho, Kume-gun, Okayama 709-3401, Japan
H. Yamamoto
Affiliation:
Okayama Prefecture Animal Industry Center, Asahi-cho, Kume-gun, Okayama 709-3401, Japan
M. Baba
Affiliation:
Okayama Prefecture Animal Industry Center, Asahi-cho, Kume-gun, Okayama 709-3401, Japan
Get access

Abstract

Restricted maximum likelihood analyses fitting an animal model were conducted to estimate genetic parameters with a pooled-data set of performance tests (growth traits and food intake) on 661 bulls and progeny tests (growth traits and carcass traits) on 535 steers. Traits studied included concentrate intake (CONC), roughage intake (ROU), TDN conversion (TCNV), TDN intake (TINT) of bulls; rib eye area (REA), marbling score (MARB), dressing proportion (DRES) and subcutaneous fat depth (SCF) of steers. Body weight at start (BWS), body weight at finish (BWF) and average daily gain (ADG) of all animals were measured. Estimated heritabilities were 0·18 (CONC), 0·71 (ROU), 0·11 (TCNV) and 0·36 (TINT); 0·02 (REA), 0·49 (MARB), 0·15 (DRES), 0·15 (SCF), and from 0·20 to 0·38 for growth traits. Genetic correlations of ROU were different from those of CONC, probably due to inconsistent restrictions on concentrate intake; those of TINT with the weights, ADG and SCF were high. MARB showed positive genetic correlations with growth traits and low correlations with TINT and SCF. High potentiality for improvement of marbling score was suggested.

Type
Breeding and genetics
Copyright
Copyright © British Society of Animal Science 2000

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

Brown, A. H. Jr., Johnson, Z. B., Chewning, J. J. and Brown, C. J. 1988. Relationship among absolute growth rate, relative growth rate and feed conversion during postweaning feedlot performance tests. Journal of Animal Science 66: 25242529.CrossRefGoogle ScholarPubMed
Fan, L. Q., Bailey, D. R. C. and Shannon, N. H. 1995. Genetic parameter estimation of postweaning gain, feed intake, and feed efficiency for Hereford and Angus bulls fed two different diets. Journal of Animal Science 73: 365372.Google Scholar
Groeneveld, E. 1994. VCE a multivariate multimodel REML (co)variance component estimation package. Proceedings of the fifth world congress on genetics applied to livestock production, Guelph, vol. 22, pp. 4748.Google Scholar
Henderson, C. R. 1973. Sire evaluation and genetic trends. Proceedings of the animal breeding genetics symposium in honor of Dr Jay L. Lush, pp. 1041. ASAS and ADSA, Champaign, IL.Google Scholar
Hirooka, H., Groen, A. F. and Matsumoto, M. 1996. Genetic parameters for growth and carcass traits in Japanese Brown cattle estimated from field records. Journal of Animal Science 74: 21122116.Google Scholar
Japan Meat Grading Association. 1988. New beef carcass grading standards. Japan Meat Grading Association, Tokyo, Japan.Google Scholar
Kemp, R. A. 1994. Genetics of meat quality in cattle. Proceedings of the fifth world congress on genetics applied to livestock production, Guelph, vol. 19, pp. 439445.Google Scholar
Koots, K. R., Gibson, J. P., Smith, C. and Wilton, J. W. 1994a. Analyses of published genetic parameters for beef production traits. 1. Heritability. Animal Breeding Abstracts 62: 309338.Google Scholar
Koots, K. R., Gibson, J. P. and Wilton, J. W. 1994b. Analyses of published genetic parameters for beef production traits. 2. Phenotypic and genetic correlations. Animal Breeding Abstracts 62: 825853.Google Scholar
Korver, S., Eekelen, E. A. M. van, Vos, H., Nieuwhof, G. J. and Arendonk, J. A. M. van. 1991. Genetic parameters for feed intake and feed efficiency in growing dairy heifers. Livestock Production Science 29: 4959.Google Scholar
Marshall, D. M. 1994. Breed differences and genetic parameters for body composition traits in beef cattle. Journal of Animal Science 72: 27452755.Google Scholar
Mavrogenis, A. P., Dillard, E. U. and Robison, O. W. 1978. Genetic analysis of postweaning performance of Hereford bulls. Journal of Animal Science 47: 10041013.Google Scholar
Mukai, F., Oyama, K. and Kohno, S. 1995. Genetic relationships between performance test traits and field carcass traits in Japanese Black cattle. Livestock Production Science 44: 199205.CrossRefGoogle Scholar
Nieuwhof, G. J., Arendonk, J. A. M. van, Vos, H. and Kover, S. 1992. Genetic relationships between feed intake, efficiency and production traits in growing bulls, growing heifers, and lactating heifers. Livestock Production Science 32: 189202.Google Scholar
Oikawa, T., Sato, K., Kawamoto, Y., Mizoguchi, Y., Nakahara, H. and Hiramoto, K. 1994. The effect of pedigree information on variance components estimation with field carcass records of beef cattle. Animal Science and Technology 65: 7577.Google Scholar
Quaas, R. L. and Pollak, E. J. 1980. Mixed model methodology for farm and ranch beef cattle testing programs. Journal of Animal Science 51: 12771287.CrossRefGoogle Scholar
Sasaki, Y., Iwaisaki, H., Masuno, T. and Asoh, S. 1982. Interaction of sire ✕ length of testing period and estimation of genetic parameters for performance testing traits of Japanese Black bulls. Journal of Animal Science 55: 771779.CrossRefGoogle Scholar
Schleppi, Y., Hofer, A., Quaas, R. L., Shmitz, F. and Kunzi, N. 1994. Relationship between own performance test and progeny test for beef production traits in Swiss dual-purpose cattle. Livestock Production Science 39: 173181.CrossRefGoogle Scholar
Statistical Analysis Systems Institute. 1992. SAS/STAT user’s guide, release 6·07. Statistical Analysis Systems Institute Inc., Cary, NC.Google Scholar