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Open Access

Genetic analysis of milking ability in Lacaune dairy ewes

  • Christel Marie-Etancelin1Email author,
  • Eduardo Manfredi1,
  • Marie-Rose Aurel1,
  • François Pailler1,
  • Jean Arhainx1,
  • Edmond Ricard1,
  • Gilles Lagriffoul1,
  • Philippe Guillouet1,
  • Bernard Bibé1 and
  • Francis Barillet1
Genetics Selection Evolution200638:183

https://doi.org/10.1186/1297-9686-38-2-183

Received: 2 May 2005

Accepted: 21 October 2005

Published: 24 February 2006

Abstract

The milking ability of Lacaune ewes was characterised by derived traits of milk flow patterns, in an INRA experimental farm, from a divergent selection experiment in order to estimate the correlated effects of selection for protein and fat yields. The analysis of selected divergent line effects (involving 34 616 data and 1204 ewes) indicated an indirect improvement of milking traits (+17% for maximum milk flow and -10% for latency time) with a 25% increase in milk yield. Genetic parameters were estimated by multi-trait analysis with an animal model, on 751 primiparous ewes. The heritabilities of the traits expressed on an annual basis were high, especially for maximum flow (0.54) and for latency time (0.55). The heritabilities were intermediate for average flow (0.30), time at maximum flow (0.42) and phase of increasing flow (0.43), and low for the phase of decreasing flow (0.16) and the plateau of high flow (0.07). When considering test-day data, the heritabilities of maximum flow and latency time remained intermediate and stable throughout the lactation. Genetic correlations between milk yield and milking traits were all favourable, but latency time was less milk yield dependent (-0.22) than maximum flow (+0.46). It is concluded that the current dairy ewe selection based on milk solid yield is not antagonistic to milking ability.

Keywords

dairy sheepmilk flowmilking abilitymilking traitdivergent selection

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Authors’ Affiliations

(1)
Station d'amélioration génétique des animaux, Institut national de la recherche agronomique, France

Copyright

© INRA, EDP Sciences 2006

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