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RESEARCH ARTICLE
Contents Vol 57(9)

Genetics of flight time and other measures of temperament and their value as selection criteria for improving meat quality traits in tropically adapted breeds of beef cattle

Meridy J. Kadel A , David J. Johnston A D , Heather M. Burrow B , Hans-U. Graser A and Drewe M. Ferguson C
+ Author Affiliations
- Author Affiliations

Cooperative Research Centre for Cattle and Beef Quality.

A Animal Genetics and Breeding Unit*, University of New England, Armidale, NSW 2351, Australia.

B CSIRO Livestock Industries, Box 5545, Rockhampton Mail Centre, Qld 4702, Australia.

C CSIRO Livestock Industries, Locked Bag 1, Armidale, NSW 2351, Australia.

D Corresponding author. Email djohnsto@pobox.une.edu.au

*AGBU is a joint venture of NSW Department of Primary Industries and The University of New England.

Australian Journal of Agricultural Research 57(9) 1029-1035 https://doi.org/10.1071/AR05082
Submitted: 3 March 2005  Accepted: 24 April 2006   Published: 30 August 2006

Abstract

Flight time, an objective measure of temperament, was recorded in 3594 Brahman, Belmont Red, and Santa Gertrudis heifers and steers. Two subjective measures of temperament (crush score and flight speed score) were also available for over 2000 of these animals. Temperament measures were recorded post-weaning (average age 8 months) and again at the start of finishing (average age 19 months) on a subset of the animals. Nine meat quality traits were measured on these animals and included measures on 2 different muscles [M. longissimus thoracis et lumborum (LTL) and M. semitendinosus (ST)]. The heritability of flight time measured post-weaning and at the start of finishing was 0.30 and 0.34, respectively, with a repeatability of 0.46 across the measurement times. Heritabilities for scored temperament traits were 0.21, 0.19, and 0.15 for post-weaning flight speed score, post-weaning crush score, and start of finishing crush score, respectively. Genetic correlations across measurement times for flight time were 0.98 and 0.96 for crush score, indicating a strong underlying genetic basis of these temperament measures over time; however, the corresponding phenotypic correlations were lower (0.48 and 0.37, respectively). Longer flight times (i.e. better temperament) were genetically correlated with improved tenderness (i.e. lower shear force and higher tenderness scores), with genetic correlations of –0.42 and 0.33 between LTL shear force, and Meat Standards Australia (MSA) tenderness, respectively. Genetic correlations between post-weaning crush score and the same meat quality traits were 0.39 and –0.47, respectively. However, genetic and phenotypic correlations between measures of temperament and other meat quality traits were generally low, with the exception of crush scores with LTL Minolta a* value (–0.37 and –0.63 for post-weaning and start of finishing measurement time, respectively). Predicted correlated responses of –0.17 kg LTL shear force and 2.6 MSA tenderness points per generation were predicted based on the genetic parameter estimates and a recording regime of both flight time and crush scores. Selection based on the measures of temperament described in this study could be used to improve temperament itself and correlated improvements can also occur in meat tenderness and eating quality traits in tropically adapted breeds of cattle.

Additional keywords: flight speed, tenderness, heritability, genetic correlation.


Acknowledgments

The authors acknowledge the core partners of the Cooperative Research Centre for Cattle and Beef Quality (The University of New England, New South Wales Department of Primary Industries, CSIRO, and Queensland Department of Primary Industries and Fisheries), the Commonwealth funding through the CRC’s Program, and the generous financial support of Meat and Livestock Australia. We also gratefully thank all Beef CRC participants, both scientists and technical staff, who contributed to or supported the work, including those involved in cattle management, data collection, laboratory analyses, and data handling. We especially thank our cooperator breeders and acknowledge the contributions of Phil Fraser, Warren Simm, Nick Corbet, Reid Geddes, Stewart Murphy, Janet Stark, David Edmonds, Chris Jones, Elmarie Bradfield, Elke Stephens, Andrew Blakely, Matt Kelly, Don Menzies, and Paul Reynolds and the database managers Mrs Elaine Farrell and Mrs Joanne Dullaway.


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