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RESEARCH ARTICLE

Genetic parameters for visually assessed traits and their relationships to wool production and liveweight in Australian Merino sheep

S. I. Mortimer A G , D. L. Robinson B , K. D. Atkins C , F. D. Brien D , A. A. Swan E F , P. J. Taylor C and N. M. Fogarty C
+ Author Affiliations
- Author Affiliations

A NSW Department of Primary Industries, Agricultural Research Centre, Trangie, NSW 2823, Australia.

B Primary Industries Innovation Centre, NSW Department of Primary Industries, University of New England, Armidale, NSW 2351, Australia.

C NSW Department of Primary Industries, Orange Agricultural Institute, Orange, NSW 2800, Australia.

D South Australian Research and Development Institute, Roseworthy, SA 7371, Australia.

E CSIRO Livestock Industries, Armidale, NSW 2350, Australia.

F Present address: Animal Genetics and Breeding Unit, University of New England, Armidale, NSW 2351, Australia.

G Corresponding author. Email: sue.mortimer@dpi.nsw.gov.au

Animal Production Science 49(1) 32-42 https://doi.org/10.1071/EA08074
Submitted: 15 February 2008  Accepted: 8 August 2008   Published: 5 January 2009

Abstract

Heritability was estimated for a range of visually assessed traits recorded on Merino sheep, together with the phenotypic and genetic correlations among the visually assessed traits and correlations of the visually assessed traits with measured wool production traits and liveweight. Data were derived from four research resource flocks, with a range of 12 958 to 57 128 records from animals with 478 to 1491 sires for the various traits. The estimates of heritability were high for the wool quality traits of handle, wool character and wool colour (0.33–0.34) and the conformation traits of face cover, neck wrinkle and body wrinkle (0.42–0.45), moderate for front leg structure (0.18) and low for back leg structure (0.13). Fleece rot score had low heritability (0.14), while classer grade was moderately heritable (0.20). Estimates of genetic correlations among the visually assessed wool quality traits were low to moderate in size and positive (0.17–0.47). Genetic correlation estimates among the assessed conformation traits were generally very low, except for the genetic correlations between scores for neck and body wrinkle (0.92 ± 0.01) and front and back leg structure (0.31 ± 0.09). Fleece rot score had low positive genetic correlations with neck and body wrinkle scores (0.18 ± 0.05 and 0.15 ± 0.05, respectively) and classer grade (0.26 ± 0.06). Classer grade was slightly positively correlated with the wool quality traits (0.17–0.45) and leg structure traits (0.21–0.25). The genetic correlations among the visually assessed traits were generally neutral to favourable. The visually assessed wool quality traits had low to moderate favourable genetic correlations with mean and coefficient of variation of fibre diameter (0.19 –0.47), but negative correlations with clean wool yield (–0.26 to –0.37). Face cover was unfavourably correlated with staple length (–0.27 ± 0.04) and liveweight (–0.23 ± 0.02). Neck and body wrinkle scores were genetically associated with higher greasy (0.33–0.39) and clean fleece weights (0.19–0.22), greater coefficient of variation of fibre diameter (0.24–0.26) and fibre curvature (0.27–0.28), but with reduced yield (–0.26 to –0.28) and staple length (–0.34 to –0.41). Fleece rot score was genetically correlated with clean fleece weight (0.26 ± 0.05) and coefficient of variation of fibre diameter (0.27 ± 0.04). Classer grade was favourably correlated with greasy and clean fleece weights (–0.41 to –0.43), staple length (–0.29 ± 0.04), liveweight (–0.36 ± 0.03) and coefficient of variation of fibre diameter (0.27 ± 0.03). Most genetic correlations between the visually assessed traits and the measured production traits and liveweight were close to zero and less than 0.2 in magnitude. This study provides accurate values for the parameter matrix required to incorporate visually assessed traits into breeding objectives and the genetic evaluation programs used in the Australian sheep industry, allowing the development of breeding objectives and indexes that optimally combine visually assessed performance and measured production in Merino sheep.

Additional keyword: visual traits.


Acknowledgements

Financial support for this study was provided by Australian Wool Innovation Limited. Dr Arthur Gilmour is thanked for his critical support of the study, as is Mrs Amity Chase for assistance with data collation. Data were made available to the project by the NSW Department of Primary Industries, CSIRO Livestock Industries and the South Australian Research and Development Institute. We gratefully acknowledge the contributions to flock management and data collection of the scientists, many of whom were involved also in the design and establishment of each of the flocks, and the technical and management staff of these organisations at the Agricultural Research Centre, Trangie, Armidale and the Turretfield Research Centre, respectively. These contributions over many years were supported by sheep breeders and industry funding bodies, such as Australian Wool Innovation Limited and its predecessors.


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