- In 2007, following extensive industry consultation, Australian Wool Innovation (AWI) & Meat and Livestock Australia (MLA) developed the Visual Sheep Scores to: • Provide the Australian sheep industry with a standardised set of visual assessment scores for the consistent description of important phenotypic traits of all breeds of sheep; • Develop a quick and simple scoring system to help sheep classers and breeders select sheep on visually-assessed traits to accelerate genetic gain; • Enable sheep breeders and classers to record and submit visual score data and genetic information to Sheep Genetics to progress development of across-flock Australian Sheep Breeding Values (ASBVs) for visually-assessed traits; and • Enable researchers to estimate the heritability of visually-assessed sheep traits, and to measure their relationships, if any, on important production traits such as fleece weight, fibre diameter, growth rate and body weight.
- Genetic parameters for a range of sheep production traits have been reviewed from estimates published over the last decade. Weighted means and standard errors of estimates of direct and maternal heritability, common environmental effects and the correlation between direct and maternal effects are presented for various growth, carcass and meat, wool, reproduction, disease resistance and feed intake traits. Weighted means and confidence intervals for the genetic and phenotypic correlations between these traits are also presented. A random effects model that incorporated between and within study variance components was used to obtain the weighted means and variances. The weighted mean heritability estimates for the major wool traits (clean fleece weight, fibre diameter and staple length) and all the growth traits were based on more than 20 independent estimates, with the other wool traits based on more than 10 independent estimates. The mean heritability estimates for the carcass and meat traits were based on very few estimates except for fat (27) and muscle depth (11) in live animals. There were more than 10 independent estimates of heritability for most reproduction traits and for worm resistance, but few estimates for other sheep disease traits or feed intake. The mean genetic and phenotypic correlations were based on considerably smaller numbers of independent estimates. There were a reasonable number of estimates of genetic correlations among most of the wool and growth traits, although there were few estimates for the wool quality traits and among the reproduction traits. Estimates of genetic correlations between the groups of different production traits were very sparse. The mean genetic correlations generally had wide confidence intervals reflecting the large variation between estimates and relatively small data sets (number of sires) used. More accurate estimates of genetic parameters and in particular correlations between economically important traits are required for accurate genetic evaluation and development of breeding objectives.
- Heritabilities, phenotypic correlations and genetic correlations for major traits in sheep.
Preference-Based Approaches to Deriving Breeding Objectives: Application to Sheep and Plant BreedingA preference-based approach, using the internet-based software 1000Minds, was used to derive part-worth utilities of farmers’ assessments with respect to traits in the definition of a breeding objective for sheep in Ireland and pasture plants in Australia. The most critical issue in developing such approaches is the clear definition of traits and the use of realistic ranges of variation in trait performance in order to define alternatives. Conversion of part-worth utilities (percentages) into economic values requires that the economic value is generated within the survey by providing respondents with options that relate to traits which can be defined in economic terms. In presenting alternatives, application of discounted gene-flow principles to breeding objectives in survey-based methods depends on the way questions are asked. It was apparent that respondents’ understanding of traits (attributes, levels), experience with the traits, and how alternatives are presented are very important in using preference-based approaches to define breeding objectives. Issues related to separation of true differences in preferences,confounding and double counting (in animal breeding objectives) are challenges in development of breeding objectives from such preference approaches.