Abstract :
A linear assessment scheme for sheep was introduced in Belgium to generate more accurate and objective information
on body characteristics of breeding stock. Body weight and six body dimensions were measured. Additionally, 14 exterior
traits were scored on a nine-point scale. Data on 11 354 animals, from 15 pure breeds were recorded from 1993 to 2000.
Breed averages and standard deviations are presented for sheep at 18 months of age. The data have served already in the
discussion on standards and breeding objectives for different breeds by providing clear and indisputable figures on weight,
body dimensions and type traits.
Training sessions and exam trials for assessors were organised to ensure the quality of the scheme. Exam data from 2
years were analysed and revealed significant differences between assessors and breeds. For some traits, a significant breed by
assessor interaction effect was found. Repeatabilities of traits ranged from 0.28 to 0.93 with higher values for the measured
traits. Assessors were individually rated on five criteria of which consistency and conformability were the most important.
When combining all 21 traits, consistency of assessors ranged from 0.62 to 0.81. Most assessors performed accurately for
the measured traits, for fatness and for the muscularity of the gigot. Traits related to leg quality, top line and tail traits were
poorly repeatable for most assessors. Conformability of assessors with the reference was on average 0.63. The traits for which
consistencywas lowwere also accompanied by lowconformability values. Further comparisons of assessors with the reference
included the difference in median value, the difference in range and the difference in proportion of the scores. Comparison of
assessors in subsequent years showed that most of them improved in consistency and approached the reference. Continued
training seemed worthwhile to improve assessor quality.
© 2003 Elsevier B.V. All rights reserved.
Keywords :
Linear type traits , body dimensions , Assessor quality , Sheep