Journal article

Testing options for the commercialization of abalone selective breeding using bioeconomic simulation modelling

Nick Robinson, Xiaoxu Li, Ben Hayes



The genetic response and economic benefit from alternative breeding programme designs for blacklip and greenlip abalone (Haliotis rubra and Haliotis laevigata, respectively) were evaluated using a computer simulation model. Two selection criteria were investigated, one used family breeding values for liability to disease challenge test infection and the other used a direct selection of the best performing individuals across families for growth rate. Five scales of breeding programme were tested and the model predicted that if growth rate is the only selection criterion, breeding programmes of a scale using 150 families of each species each generation would result in 12-13% genetic improvemen..

View full abstract

University of Melbourne Researchers


Funding Acknowledgements

This work formed part of a project of the Australian Seafood Cooperative Research Centre, and received funds from the Australian Government's CRC programme, the Fisheries Research and Development Corporation and other CRC participants. The first author wishes to thank the Australian Seafood Cooperative Research Centre, Fisheries Research and Development Corporation, Australian Abalone Growers Association (AAGA), South Australian Research and Development Institute (SARDI) and Nofima Marine for their support of the project. The first author was employed by Nofima under a service contract with SARDI on this project. Thank you Ann Flemming of AAGA and Mark Gervis of Southern Ocean Mariculture who provided helpful advice, industry parameters and feedback on the project report and findings. Thank you also Graham Mair of Flinders University and Steven Clarke of SARDI who helped to establish the project and working agreements and provided helpful feedback on the work. There are a number of other people who contributed in discussions and workshops to provide information and helpful suggestions for this project, Martin Millar, Nick Elliot, Jonathan Lillie, Mehdi Doroudi, Peter Kube, Nick Savva, Geoff Penfold, Justin Harman and Shane Mclinden. Thanks also to my colleagues at Nofima (formerly Akvaforsk) in Norway, especially the Group Leader Kari Kolstad and Director Camilla Rosjo, who through this and other projects, have supported our work on the bioeconomic model for selective breeding and provided helpful advice. Finally, we would like to thank the anonymous reviewers of the manuscript who provided very useful suggestions and criticisms.