Animal Production Science Animal Production Science Society
Food, fibre and pharmaceuticals from animals
RESEARCH ARTICLE

Estimation of genotype × environment interactions for growth, fatness and reproductive traits in Australian Angus cattle

M. G. Jeyaruban A B , D. J. Johnston A and H.-U. Graser A
+ Author Affiliations
- Author Affiliations

A Animal Genetics and Breeding Unit (a joint venture of NSW Department of Primary Industries and University of New England), University of New England, Armidale, NSW 2351, Australia.

B Corresponding author. Email: gjeyarub@une.edu.au

Animal Production Science 49(1) 1-8 https://doi.org/10.1071/EA08098
Submitted: 17 March 2008  Accepted: 11 July 2008   Published: 5 January 2009

Abstract

The magnitude of genotype × environment interactions (G × E) were estimated for growth, real time ultrasound scanned carcass and reproductive traits in Angus cattle. Traits measured in the states of Victoria and Queensland were assumed as different traits and the genetic correlations between them were estimated. Estimated heritabilities across states were similar for all traits. However, additive genetic variances of fat depth at the P8 (rump) site for bulls (BP8), intramuscular fat percent at the 12/13th rib for bulls (BIMF) and heifers (HIMF) were significantly different between states. Estimated genetic correlations across states for direct genetic effects were high for growth traits and ranged from 0.89 to 1.00. For the maternal genetic effects the correlations across states ranged from 0.66 to 0.87. The across state correlations for scanned traits were also high. The exception was for BIMF (0.65), where measurement procedures were observed to influence the result. The genetic correlation between the states increased to 0.94 when the records of bulls with low IMF value were removed. For reproductive traits, the estimated genetic correlations ranged from 0.97 to 1.00. These results indicated little evidence of G × E for growth, ultrasound scanned carcass and reproductive traits of Angus cattle from Victoria and Queensland. Combining performance data across states in a national genetic evaluation is appropriate and it is expected that the progeny of Angus cattle would rank similarly across states.


Acknowledgements

The authors thank Meat and Livestock Australia (MLA) for their financial support and the Angus Breed Society and their members for providing data for this study. The authors also would like to acknowledge the contribution of Kim Bunter, Ron Crump and Andrew Swan for their comments on the manuscript.


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