Hostname: page-component-78c5997874-94fs2 Total loading time: 0 Render date: 2024-11-13T10:27:29.131Z Has data issue: false hasContentIssue false
  • English
  • Français

Multiple trait genetic evaluation of clinical mastitis in three dairy cattle breeds

Published online by Cambridge University Press:  23 November 2015

A. Govignon-Gion ,
R. Dassonneville ,
G. Baloche  and
V. Ducrocq
A. Govignon-Gion*
Affiliation:
Institut National de la Recherche Agronomique (INRA), Génétique Animale et Biologie Intégrative, F-78352 Jouy-en-Josas, France
R. Dassonneville
Affiliation:
AgroParisTech, Génétique Animale et Biologie Intégrative, F-78352 Jouy-en-Josas, France
G. Baloche
Affiliation:
Institut National de la Recherche Agronomique (INRA), Génétique Animale et Biologie Intégrative, F-78352 Jouy-en-Josas, France AgroParisTech, Génétique Animale et Biologie Intégrative, F-78352 Jouy-en-Josas, France
V. Ducrocq
Affiliation:
Institut National de la Recherche Agronomique (INRA), Génétique Animale et Biologie Intégrative, F-78352 Jouy-en-Josas, France
*
†E-mail: armelle.gion@jouy.inra.fr
Get access

Abstract

In 2010, a routine genetic evaluation on occurrence of clinical mastitis in three main dairy cattle breeds – Montbéliarde (MO), Normande (NO) and Holstein (HO) – was implemented in France. Records were clinical mastitis events reported by farmers to milk recording technicians and the analyzed trait was the binary variable describing the occurrence of a mastitis case within the first 150 days of the first three lactations. Genetic parameters of clinical mastitis were estimated for the three breeds. Low heritability estimates were found: between 2% and 4% depending on the breed. Despite its low heritability, the trait exhibits genetic variation so efficient genetic improvement is possible. Genetic correlations with other traits were estimated, showing large correlations (often>0.50, in absolute value) between clinical mastitis and somatic cell score (SCS), longevity and some udder traits. Correlation with milk yield was moderate and unfavorable (ρ=0.26 to 0.30). High milking speed was genetically associated with less mastitis in MO (ρ=−0.14) but with more mastitis in HO (ρ=0.18). A two-step approach was implemented for routine evaluation: first, a univariate evaluation based on a linear animal model with permanent environment effect led to pre-adjusted records (defined as records corrected for all non-genetic effects) and associated weights. These data were then combined with similar pre-adjusted records for others traits in a multiple trait BLUP animal model. The combined breeding values for clinical mastitis obtained are the official (published) ones. Mastitis estimated breeding values (EBV) were then combined with SCSs EBV into an udder health index, which receives a weight of 14.5% to 18.5% in the French total merit index (ISU) of the three breeds. Interbull genetic correlations for mastitis occurrence were very high (ρ=0.94) with Nordic countries, where much stricter recording systems exist reflecting a satisfactory quality of phenotypes as reported by the farmers. They were lower (around 0.80) with countries supplying SCS as a proxy for the international evaluation on clinical mastitis.

Keywords

clinical mastitisgenetic parametersgenetic evaluationmultiple traitudder health
Type
Research Article
Information
animal , Volume 10 , Issue 4 , April 2016 , pp. 558 - 565
Copyright
© The Animal Consortium 2015 

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

Bonaïti, B, Moureaux, S and Mattalia, S 2005. Bilan et paramètres génétiques des mammites cliniques collectées par le contrôle laitier dans les races Montbéliarde, Normande et Prim’Holstein. Rencontres Recherches Ruminants 12, 271–274. Retrieved October 12, 2014, from http://www.journees3r.fr/IMG/pdf/2005_sante_04_bonaiti.pdf.Google Scholar
Carlén, E, Emanuelson, U and Strandberg, E 2006. Genetic evaluation of mastitis in dairy cattle using linear models, threshold models, and survival analysis: a simulation study. Journal of Dairy Science 89, 4049–4057.Google Scholar
Carlén, E, Strandberg, E and Roth, A 2004. Genetic parameters for clinical mastitis, somatic cell score, and production in the first three lactations of Swedish Holstein cows. Journal of Dairy Science 87, 3062–3070.CrossRefGoogle ScholarPubMed
Dassonneville, R, Barbat-Leterrier, A, Gion, A, Larroque, H and Ducrocq, V 2009. Estimation de paramètres génétiques de nouveaux caractères fonctionnels pour les bovins laitiers. Rencontres Recherches Ruminants 16, 301. Retrieved October 12, 2014, from http://www.journees3r.fr/IMG/pdf/2009_09_10_Dassonneville.pdf.Google Scholar
De Haas, Y, Ouweltjes, W, ten Napel, J, Windig, JJ and de Jong, G 2008. Alternative somatic cell count traits as mastitis indicators for genetic selection. Journal of Dairy Science 91, 2501–2511.Google Scholar
Ducrocq, V 2001. A two-step procedure to get animal model solutions in Weibull survival models used for genetic evaluations on length of productive life. Interbull Bulletin 27, 147–152.Google Scholar
Ducrocq, V, Boichard, D, Barbat, A and Larroque, H 2001. Implementation of an approximate multitrait BLUP evaluation to combine production traits and functional traits into a total merit index. 52nd Annual Meeting of the European Association for Animal Production, Budapest, Hungary, August 26–29.Google Scholar
Ducrocq, V, Delaunay, I, Boichard, D and Mattalia, S 2003. A general approach for international genetic evaluations robust to inconsistencies of genetic trends in national evaluations. Interbull Bulletin 30, 101–111.Google Scholar
Gianola, D and Foulley, JL 1983. Sire evaluation for ordered categorical data with a threshold model. Genetics Selection Evolution 15, 201–224.Google Scholar
Harris, B and Johnson, D 1998. Approximate reliabilities of genetic evaluation under an animal model. Journal of Dairy Science 81, 2723–2728.Google Scholar
Heringstad, B, Chang, YM, Gianola, D and Klemetsdal, G 2004. Multivariate threshold model analysis of clinical mastitis in multiparous Norwegian dairy cattle. Journal of Dairy Science 87, 3038–3046.Google Scholar
Heringstad, B, Gianola, D, Chang, YM, Odegård, J and Klemetsdal, G 2006. Genetic associations between clinical mastitis and somatic cell score in early first-lactation cows. Journal of Dairy Science 89, 2236–2244.Google Scholar
Heringstad, B, Rekaya, R, Gianola, D, Klemetsdal, G and Weigel, KA 2003. Genetic change for clinical mastitis in Norwegian cattle: a threshold model analysis. Journal of Dairy Science 86, 369–375.Google Scholar
Hinrichs, D, Stamer, E, Junge, W and Kalm, E 2005. Genetic analyses of mastitis data using animal threshold models and genetic correlation with production traits. Journal of Dairy Science 88, 2260–2268.Google Scholar
Interbull 2014. Interbull Routine genetic evaluation for udder health traits. August. Retrieved October 12, 2014, from http://www.interbull.org/web/static/mace_evaluations/1408r/uder1408r.pdf.Google Scholar
Jamrozik, K, Koeck, A, Miglior, F, Kistemaker, GJ, Shenkel, FS, Kelton, DF and Van Doormaal, BJ 2013. Genetic and genomic evaluation of mastitis resistance in Canada. Interbull Bulletin 47, 23–26.Google Scholar
Koeck, A, Heringstad, B, Egger-Danner, C, Fuerst, C, Winter, P and Fuerst-Waltl, B 2010. Genetic analysis of clinical mastitis and somatic cell count traits in Austrian Fleckvieh cows. Journal of Dairy Science 93, 5987–5995.Google Scholar
Lassen, J, Sorensen, MK, Madsen, P and Ducrocq, V 2007. A stochastic simulation study on validation of an approximate multitrait model using preadjusted data for prediction of breeding values. Journal of Dairy Science 90, 3002–3011.Google Scholar
Lund, MS, Jensen, J and Petersen, PH 1999. Estimation of genetic and phenotypic parameters for clinical mastitis, somatic cell production deviance, and protein yield in dairy cattle using Gibbs sampling. Journal of Dairy Science 82, 1045–1051.CrossRefGoogle ScholarPubMed
Meyer, K 2007. Wombat, a tool for mixed model analyses in quantitative genetics by restricted maximum likelihood. Journal of Zhejiang University Science B 8, 815–821.Google Scholar
Miglior, F, Muir, BL and Van Doormaal, BJ 2005. Selection indices in Holstein cattle of various countries. Journal of Dairy Science 88, 1255–1263.Google Scholar
Ødegård, J, Heringstad, B and Klemetsdal, G 2004. Short communication: bivariate genetic analysis of clinical mastitis and somatic cell count in Norwegian dairy cattle. Journal of Dairy Science 87, 3515–3517.Google Scholar
Pérez-Cabal, MA, de los Campos, G, Vazquez, AI, Gianola, D, Rosa, GJM, Weigel, K and Alenda, R 2009. Genetic evaluation of susceptibility to clinical mastitis in Spanish Holstein cows. Journal of Dairy Science 9, 3472–3480.CrossRefGoogle Scholar
Robert-Granié, C, Bonaïti, B, Boichard, D and Barbat, A 1999. Accounting for variance heterogeneity in French dairy cattle genetic evaluation. Livestock Productions Sciences 62, 343–357.Google Scholar
Rupp, R and Boichard, D 1999. Genetic parameters for clinical mastitis, somatic cell score, production, udder type traits, and milking ease in first lactation Holsteins. Journal of Dairy Science 82, 2198–2204.Google Scholar
Sørensen, LP, Mark, T, Madsen, P and Lund, MS 2009. Genetic correlations between pathogen-specific mastitis and somatic cell count in Danish Holsteins. Journal of Dairy Science 92, 3457–3471.Google Scholar
Vazquez, AI, Perez-Cabal, MA, Heringstad, B, Rodrigues-Motta, M, Rosa, GJM, Gianola, D and Weigel, KA 2012. Predictive ability of alternative models for genetic analysis of clinical mastitis. Journal of Animal Breeding and Genetics 12, 120–128.Google Scholar