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Development and implementation of multi-breed genetic evaluation systems for the Australian beef industry

Did you know multi-breed genetic evaluations can allow comparison of animals of different breeds?

Project start date: 01 June 2017
Project end date: 31 December 2019
Publication date: 25 February 2020
Project status: In progress
Livestock species: Grassfed cattle, Grainfed cattle
Relevant regions: National
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Multi-breed genetic evaluation tools optimise genetic gain by providing clear comparisons between different genes across breed types. This allows producers to select the genetics that best suit their production environment, breeding objectives and target markets.

This project reviewed stud client and industry databases, including the BREEDPLAN software, to investigate which ones link to other breed databases to effectively perform multi-breed genetic evaluations.

BREEDPLAN has capacity to accommodate multi-breed datasets and, at the completion of this project, several BREEDPLAN evaluations are now routinely using multi-breed data to calculate estimated breeding values for beef producers.


The project's objectives were to identify all multi-breed datasets within the current breed and research databases and use this information to:

  • update multi-breed evaluations for British, European and tropical breeds
  • determine the extent to which the commercial data improves the scope (breed and trait coverage) and accuracy of the evaluations
  • create a strategy for ongoing multi-breed evaluation and data collection to support reliable multi-breed genetic evaluation.

Key findings

  • The current BREEDPLAN software can accommodate multi-breed datasets, but there is scope for improvement to better handle genetic information from multiple breeds in a 'single-step' analysis.
  • At the completion of this project, several BREEDPLAN evaluations are now using multi-breed data on a routine basis to calculate estimated breeding values for Southern Limousin, Brahman, Santa Gertrudis, Droughtmaster and Belmont Red.
  • Tropically-adapted breeds in Australia are best positioned to use multi-breed data in their respective BREEDPLAN evaluations. There is further potential for these breeds to combine for a single Northern Tropical BREEDPLAN evaluation.

Benefits to industry

Multi-breed performance data can show the differences between genetic characteristics, which allows for breed differences in animals to be modelled, including changes over time in each population. This provides clear and readily-available comparisons for producers to select the bulls that best suit the production environment, breeding objective and target markets, irrespective of breed.

MLA action

From the results of this project, the Agricultural Business Research Institute has transitioned some clients to using multi-breed data on a routine basis to calculate estimated breeding values for their breed's analyses where data is available. This effort has largely focused on the tropically adapted breeds.

Further work is continuing (MLA project L.GEN.1704) with the Animal Genetics and Breeding Unit at the University of New England, to enable genotypes from multiple breeds to be used in a multi-breed Single-Step BREEDPLAN analysis.

MLA has also commenced work with NSW Department of Primary Industries to capture structured multi-breed data for the major temperate breeds to address the gaps in current datasets identified by this project.

Future research

Several important knowledge gaps were identified during the review of databases, including:

  • The data currently available from commercial sources is insufficient quality to successfully develop multi-breed evaluations.
  • Apart from four tropical breeds, there is little or no linkage between breeds and for traits other than growth. There are also no sound research datasets that allow for breed and trait comparisons.
  • It is essential to develop a more sophisticated yet flexible suite of BREEDPLAN software to complete multi-breed evaluations.

More information

Contact email:
Primary researcher: Agricultural Business Research Inst