Hostname: page-component-586b7cd67f-rcrh6 Total loading time: 0 Render date: 2024-11-26T22:53:07.019Z Has data issue: false hasContentIssue false
  • English
  • Français

Genetic parameters of milk traits in Latxa dairy sheep

Published online by Cambridge University Press:  18 August 2016

A. Legarra  and
E. Ugarte
A. Legarra*
Affiliation:
NEIKER, Basque Institute for Agricultural Research and Development, Granja Modelo, Apartado 46, 01080 Vitoria-Gasteiz, Spain
E. Ugarte
Affiliation:
NEIKER, Basque Institute for Agricultural Research and Development, Granja Modelo, Apartado 46, 01080 Vitoria-Gasteiz, Spain
*
E-mail:[email protected]
Get access

Abstract

A total of 7444 lactation records which include milk, fat and protein yields (MY, FY, PY) and fat and protein content (F%, P%) from 6429 Black-Faced Latxa ewes were employed to estimate genetic parameters for milk traits. Traits were standardized to 120 days of lactation. For the calculation of composition traits, not all test-days had their composition measured and therefore a correction taking this into account was included in the analysis. A first-derivative restricted maximum likelihood algorithm was used on an animal model with repeatability analysis, using models including fixed effects (flock-year-season of lambing, age-parity at lambing, number of lambs, interval between lambing and first milk recording and the combination of sampled test-days) and random effects (the additive genetic effect and the permanent environmental effect). The resulting heritabilities were 0·20, 0·16, 0·18, 0·14 and 0·38 for MY, FY, PY, F% and P% respectively. Heritability of F% was much lower than expected, probably due to problems derived from the recording method. Genetic correlations were high and positive between yields and moderately positive between F% and P%, and negative or null between yields and composition, as has been reported for other European dairy sheep breeds. As most of the milk produced by Latxa dairy sheep is processed into cheese, the inclusion of milk sampling in official milk recording and a change in the selection criterion are recommended to avoid a long-term worsening in milk composition.

Keywords

dairy sheepgenetic parametersheritabilitymilk composition.
Type
Breeding and genetics
Information
Animal Science , Volume 73 , Issue 3 , December 2001 , pp. 407 - 412
Copyright
Copyright © British Society of Animal Science 2001

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

Arranz, J. and Legarra, A. 2001. [Importance of methodology in the taking of a correct sample for composition in sheep milk.] ITEA 22: (supplement) 649–651.Google Scholar
Barillet, F. 1985. [Genetic improvement of the composition of sheep milk. The example of the Lacaune breed.] Ph.D. dissertation, Institute National Agronomique, Paris-Grignon.Google Scholar
Barillet, F. 1989. [Expression of milk yield at milking period for Lacaune ewes bred in dual-purpose system suckling ✕ milking by machine.] In Proceedings of the fourth international symposium on the milking of small ruminants, Tel Aviv, Israel (ed. Eitam, M.), pp. 463–495.Google Scholar
Barillet, F. 1990. [Report of the CICPLB group on sheep milk recording: simplification of the A-method official milk recording.] In Proceedings of the 27th biennial session of ICAR, Paris, France, 2-6 July 1990. European Association for Animal Production publication no. 50, 1991, pp. 119–125.Google Scholar
Barillet, F. 1997. Genetics of milk production. In The genetics of the sheep (ed. Piper, L. and Ruvinsky, A.), pp. 539–564. CAB International, Oxford.Google Scholar
Barillet, F. and Boichard, D. 1987. Studies on dairy production of milking ewes. I. Estimates of genetic parameters for total milk composition and yield. Génétique, Sélection, Évolution 19: 459–474.CrossRefGoogle Scholar
Barillet, F. and Boichard, D. 1994. Use of first lactation test-day data for genetic evaluation of the Lacaune dairy sheep. Proceedings of the fifth world congress on genetics applied to livestock production, Guelph, vol. 18, pp. 111–114.Google Scholar
Bergonier, D., Berthelot, X., Romeo, M., Contreras, A., Coni, V., Santis, E.de, Rolesu, S., Barillet, F., Lagriffoul, G. and Marco, J. 1998. [Frequency of different germs causing clinical and subclinical mastitis in dairy small ruminants.] In Milking and milk production of dairy sheep and goats (ed Barillet, F. and Zervas, N.P.). Proceedings of the sixth international symposium on the milking of small ruminants, pp. 130–136. Wageningen Pers, The Netherlands.Google Scholar
Dekkers, J. C. M. and Gibson, J. P. 1998. Applying breeding objectives to dairy cattle improvement. Journal of Dairy Science 81: (suppl. 2) 19–35.CrossRefGoogle ScholarPubMed
Fernando, R. L., Gianola, D. and Grossman, M. 1983. Identifying connected subsets in a two-way classification without interaction. Journal of Dairy Science 66: 1399–1402.CrossRefGoogle Scholar
Gabiña, D., Arrese, F., Arranz, J. and Beltrán de Heredia, I. 1993. Average milk yields and environmental effects on Latxa sheep. Journal of Dairy Science 76: 1191–1198.CrossRefGoogle Scholar
International Committee for Animal Recording. 1995. Recording guidelines. Appendices to the International Agreement of Recording Practices. ICAR, Rome, Italy/RVN, Arnhem, The Netherlands. Available at http://www.icar.org/ recordin.htm.Google Scholar
Maria, G. A. 1989. [Study and development of a simplified milk recording scheme for milk contents in the Latxa sheep.] Ph.D. dissertation, University of Zaragoza, Spain.Google Scholar
Maria, G. A. and Gabiña, D. 1992. Simplification of milk recording scheme in Latxa milking sheep. Livestock Production Science 31: 313–320.CrossRefGoogle Scholar
Neumaier, A. and Groeneveld, E. 1998. Restricted maximum likelihood estimation of covariances in sparse linear models. Genetics, Selection, Evolution 30: 3–26.CrossRefGoogle Scholar
Sanna, S. R., Carta, A. and Casu, S. 1997. (Co)variance component estimates for milk composition traits in Sarda dairy sheep using a bivariate animal model. Small Ruminant Research 25: 77–82.CrossRefGoogle Scholar
Serrano, M., Pérez-Guzmán, M. D., Montoro, V. and Jurado, J. J. 1996. Genetic parameters estimation and selection progress for milk yields in Manchega sheep. Small Ruminant Research 23: 51–57.CrossRefGoogle Scholar
Statistical Analysis Systems Institute. 1988. SAS/STAT user’s guide. Statistical Analysis Systems Institute, Cary, NC.Google Scholar
Ugarte, E., Ruiz, R., Gabiña, D. and Beltrán de Heredia, I. 2001. Impact of high-yielding foreign breeds on the Spanish dairy sheep industry. Livestock Production Science 71: 3–10.CrossRefGoogle Scholar
Ugarte, E., Urarte, E., Arranz, J., Arrese, F., Rodríguez, C. and Silió, L. 1997. [Use of genetic groups in the genetic evaluation of the Black-Faced Latxa sheep.] ITEA 18: (supplement) 397–399.Google Scholar
Ugarte, E., Urarte, E., Arrese, F., Arranz, J., Beltrán de >Heredia, I. and Gabiña, D. 1995. Technical organization and economic needs of the breeding programme of Latxa and Carranzana dairy sheep in the Spanish Basque country. In Strategies for sheep and goat breeding (ed. Gabina, D.). Proceedings of the meeting of the joint FAO/CIHEAM Network on Sheep and Goats, Subnetwork on Animal Resources, Sidi-Taheb, Tunisia, 26-28 March 1995. Cahiers Options Méditerranéenes, vol. 11, pp. 155–164.Google Scholar
Ugarte, E., Urarte, E., Arrese, F., Arranz, J., Silió, L. and Rodríguez, C. 1996. Genetic parameters and trends for milk production of Blond-Faced Latxa sheep using Bayesian analysis. Journal of Dairy Science 79: 2268–2277.CrossRefGoogle ScholarPubMed