Open Access

Measuring connectedness among herds in mixed linear models: From theory to practice in large-sized genetic evaluations

  • Marie-Noëlle Fouilloux1Email author,
  • Virginie Clément2 and
  • Denis Laloë3
Genetics Selection Evolution200840:145

https://doi.org/10.1186/1297-9686-40-2-145

Received: 8 February 2007

Accepted: 16 October 2007

Published: 15 March 2008

Abstract

A procedure to measure connectedness among groups in large-sized genetic evaluations is presented. It consists of two steps: (a) computing coefficients of determination (CD) of comparisons among groups of animals; and (b) building sets of connected groups. The CD of comparisons were estimated using a sampling-based method that estimates empirical variances of true and predicted breeding values from a simulated n-sample. A clustering method that may handle a large number of comparisons and build compact clusters of connected groups was developed. An aggregation criterion (Caco) that reflects the level of connectedness of each herd was computed. This procedure was validated using a small beef data set. It was applied to the French genetic evaluation of the beef breed with most records and to the genetic evaluation of goats. Caco was more related to the type of service of sires used in the herds than to herd size. It was very sensitive to the percentage of missing sires. Disconnected herds were reliably identified by low values of Caco. In France, this procedure is the reference method for evaluating connectedness among the herds involved in on-farm genetic evaluation of beef cattle (IBOVAL) since 2002 and for genetic evaluation of goats from 2007 onwards.

Keywords

connectednessclusteringBLUPaccuracy

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Authors’ Affiliations

(1)
Institut de l'Élevage, Station de génétique quantitative et appliquée, INRA
(2)
Institut de l'Élevage, Station d'amélioration génétique des animaux, INRA
(3)
Station de génétique quantitative et appliquée UR337, INRA

Copyright

© INRA, EDP Sciences 2008

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