Screening for outliers in multiple trait genetic evaluation

Authors

  • Per Madsen Aarhus University Dept. of Molecular Biology and Genetics
  • Jukka Pösö Faba co-op
  • Jørn Pedersen Knowledge Centre for Agriculture, Cattle
  • Martin Lidauer MTT, Agrifood Research Finland, Biotechnology and Food Research, Genetic Research Group
  • Just Jensen Aarhus University Dept. of Molecular Biology and Genetics

Keywords:

cattle, genetic evaluation, multivariate, outliers

Abstract

Use of multivariate models in genetic evaluation requires a multivariate method for detecting erroneous outliers that cannot be detected using univariate methods. A simple rule for detecting outliers based on an approximated Mahanalobis distance was applied to Jersey data from the routine Nordic genetic evaluation in dairy cattle. Application of such is simple to implement and increased the accuracy of predicted breeding values for animals that has one or more records edited. Potential biases in evaluations for contemporary animals were also reduced. Optimum editing rules can be determined using the same data structures as used in the standard INTERBULL test for model verification.

Author Biographies

Per Madsen, Aarhus University Dept. of Molecular Biology and Genetics

Jukka Pösö, Faba co-op

Jørn Pedersen, Knowledge Centre for Agriculture, Cattle

Martin Lidauer, MTT, Agrifood Research Finland, Biotechnology and Food Research, Genetic Research Group

Just Jensen, Aarhus University Dept. of Molecular Biology and Genetics

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Published

2012-05-29

Issue

No. 46 (2012): Proceedings of the 2012 Interbull meeting

Section

Articles

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