My research interests centre on using quantitative genetics to drive genetic gain and efficiency in plant and animal breeding programmes.
Previous work in the UK focused on using genomic information prediction to demonstrate and exploit synergies between plant and animal breeding. Stochastic simulations were used to quantify the impact of new genomic breeding strategies in a wide variety of settings; from low to middle-income (LMIC) dairy cattle breeding programs to large, well-funded maize breeding programs.
My work at QAAFI and the ARC Centre of Excellence for Plant Success in Nature & Agriculture focuses on the development of prediction methods that combine biological, environmental and management information under a unifying framework, to enhance our ability to identify breeding parents, varieties and genotype-by-agronomic management (GxM) solutions that are best suited for future climates.
Dr Powell helps public and private genetic improvement programs to find better ways to predict the outcomes of selective breeding.
His core work focuses on developing, applying and optimising prediction methods to accelerate rates of sustainable genetic improvement.
Dr Powell is involved in the research and HDR student supervision on projects that span plant, animal and aquaculture species.
Journal Article: Advancing artificial intelligence to help feed the world
Hayes, Ben J., Chen, Chensong, Powell, Owen, Dinglasan, Eric, Villiers, Kira, Kemper, Kathryn E. and Hickey, Lee T. (2023). Advancing artificial intelligence to help feed the world. Nature Biotechnology, 41 (9), 1-2. doi: 10.1038/s41587-023-01898-2
Journal Article: Investigations into the emergent properties of gene-to-phenotype networks across cycles of selection: a case study of shoot branching in plants
Powell, Owen M., Barbier, Francois, Voss-Fels, Kai P., Beveridge, Christine and Cooper, Mark (2022). Investigations into the emergent properties of gene-to-phenotype networks across cycles of selection: a case study of shoot branching in plants. in silico Plants, 4 (1) diac006, 1-9. doi: 10.1093/insilicoplants/diac006
Other Outputs: Designing breeding programs in the genomic era
Owen Powell (2021). Designing breeding programs in the genomic era. PhD Thesis, The Roslin Institute, The University of Edinburgh . doi: 10.7488/era/1463
Journal Article: Perspectives on applications of hierarchical gene-to-phenotype (G2P) maps to capture non-stationary effects of alleles in genomic prediction
Powell, Owen M., Voss-Fels, Kai P., Jordan, David R., Hammer, Graeme and Cooper, Mark (2021). Perspectives on applications of hierarchical gene-to-phenotype (G2P) maps to capture non-stationary effects of alleles in genomic prediction. Frontiers in Plant Science, 12 663565, 663565. doi: 10.3389/fpls.2021.663565/full
ON the Pulse - benchmarking protein quality for chickpea
(2023–2024) UQ Knowledge Exchange & Translation Fund
Predicting Plant Success For Future Generations
Doctor Philosophy
Experimental investigation in Arabidopsis thaliana of realised selection trajectories for complex branching and flowering traits under the control of gene networks following application of genomic prediction methods.
Doctor Philosophy
Optimising Genomic Selection for Sugarcane
(2023) Doctor Philosophy
Advancing artificial intelligence to help feed the world
Hayes, Ben J., Chen, Chensong, Powell, Owen, Dinglasan, Eric, Villiers, Kira, Kemper, Kathryn E. and Hickey, Lee T. (2023). Advancing artificial intelligence to help feed the world. Nature Biotechnology, 41 (9), 1-2. doi: 10.1038/s41587-023-01898-2
Powell, Owen M., Barbier, Francois, Voss-Fels, Kai P., Beveridge, Christine and Cooper, Mark (2022). Investigations into the emergent properties of gene-to-phenotype networks across cycles of selection: a case study of shoot branching in plants. in silico Plants, 4 (1) diac006, 1-9. doi: 10.1093/insilicoplants/diac006
Designing breeding programs in the genomic era
Owen Powell (2021). Designing breeding programs in the genomic era. PhD Thesis, The Roslin Institute, The University of Edinburgh . doi: 10.7488/era/1463
Powell, Owen M., Voss-Fels, Kai P., Jordan, David R., Hammer, Graeme and Cooper, Mark (2021). Perspectives on applications of hierarchical gene-to-phenotype (G2P) maps to capture non-stationary effects of alleles in genomic prediction. Frontiers in Plant Science, 12 663565, 663565. doi: 10.3389/fpls.2021.663565/full
Cooper, Mark, Messina, Carlos D., Tang, Tom, Gho, Carla, Powell, Owen M., Podlich, Dean W., Technow, Frank and Hammer, Graeme L. (2023). Predicting Genotype × Environment × Management (G × E × M) interactions for the design of crop improvement strategies: Integrating breeder, agronomist, and farmer perspectives. Plant breeding reviews. (pp. 467-585) edited by Irwin Goldman. Hoboken, NJ, United States: Wiley Blackwell. doi: 10.1002/9781119874157.ch8
Adaptation and plasticity of yield in hybrid and inbred sorghum
Otwani, Daniel, Hunt, Colleen, Cruickshank, Alan, Powell, Owen, Koltunow, Anna, Mace, Emma and Jordan, David (2023). Adaptation and plasticity of yield in hybrid and inbred sorghum. Crop Science. doi: 10.1002/csc2.21160
Use of continuous genotypes for genomic prediction in sugarcane
Yadav, Seema, Ross, Elizabeth M., Wei, Xianming, Liu, Shouye, Nguyen, Loan To, Powell, Owen, Hickey, Lee T., Deomano, Emily, Atkin, Felicity, Voss‐Fels, Kai P. and Hayes, Ben J. (2023). Use of continuous genotypes for genomic prediction in sugarcane. The Plant Genome e20417, e20417. doi: 10.1002/tpg2.20417
Yadav, Seema, Ross, Elizabeth M., Wei, Xianming, Powell, Owen, Hivert, Valentin, Hickey, Lee T., Atkin, Felicity, Deomano, Emily, Aitken, Karen S., Voss-Fels, Kai P. and Hayes, Ben J. (2023). Optimising clonal performance in sugarcane: leveraging non-additive effects via mate-allocation strategies. Frontiers in Plant Science, 14 1260517, 1260517. doi: 10.3389/fpls.2023.1260517
de Jong, Guilherme, Powell, Owen, Gorjanc, Gregor, Hickey, John M. and Gaynor, R. Chris (2023). Comparison of genomic prediction models for general combining ability in early stages of hybrid breeding programs. Crop Science, 63 (6), 3338-3355. doi: 10.1002/csc2.21105
Chen, Chensong, Powell, Owen, Dinglasan, Eric, Ross, Elizabeth M., Yadav, Seema, Wei, Xianming, Atkin, Felicity, Deomano, Emily and Hayes, Ben J. (2023). Genomic prediction with machine learning in sugarcane, a complex highly polyploid clonally propagated crop with substantial non‐additive variation for key traits. The Plant Genome, 16 (4) e20390, 1-13. doi: 10.1002/tpg2.20390
Advancing artificial intelligence to help feed the world
Hayes, Ben J., Chen, Chensong, Powell, Owen, Dinglasan, Eric, Villiers, Kira, Kemper, Kathryn E. and Hickey, Lee T. (2023). Advancing artificial intelligence to help feed the world. Nature Biotechnology, 41 (9), 1-2. doi: 10.1038/s41587-023-01898-2
Extending the breeder’s equation to take aim at the target population of environments
Cooper, Mark, Powell, Owen, Gho Brito, Carla, Tang, Tom and Messina, Carlos (2023). Extending the breeder’s equation to take aim at the target population of environments. Frontiers in Plant Science, 14 1129591, 1-10. doi: 10.3389/fpls.2023.1129591
Yadav, Seema, Ross, Elizabeth, Wei, Xianming, Powell, Owen, Hivert, Valentin, Hickey, Lee T., Atkin, Felicity, Deomano, Emily, Aitken, Karen S., Voss-Fels, Kai P. and Hayes, Ben J. (2022). Genomic mate-allocation strategies exploiting additive and non-additive genetic effects to maximise total clonal performance in sugarcane.
Powell, Owen M., Barbier, Francois, Voss-Fels, Kai P., Beveridge, Christine and Cooper, Mark (2022). Investigations into the emergent properties of gene-to-phenotype networks across cycles of selection: a case study of shoot branching in plants. in silico Plants, 4 (1) diac006, 1-9. doi: 10.1093/insilicoplants/diac006
Crop improvement for circular bioeconomy systems
Messina, Carlos D., van Eeuwijk, Fred, Tang, Tom, Truong, Sandra K., McCormick, Ryan F., Technow, Frank, Powell, Owen, Mayor, Laura, Gutterson, Neal, Jones, James W., Hammer, Graeme and Cooper, Mark (2022). Crop improvement for circular bioeconomy systems. Journal of the ASABE, 65 (3), 491-504. doi: 10.13031/ja.14912
A linkage disequilibrium-based approach to position unmapped SNPs in crop species
Yadav, Seema, Ross, Elizabeth M., Aitken, Karen S., Hickey, Lee T., Powell, Owen, Wei, Xianming, Voss-Fels, Kai P. and Hayes, Ben J. (2021). A linkage disequilibrium-based approach to position unmapped SNPs in crop species. BMC Genomics, 22 (1) 773, 1-9. doi: 10.1186/s12864-021-08116-w
Owen Powell, Raphael Mrode, R. Chris Gaynor, Martin Johnsson, Gregor Gorjanc and John M.Hickey (2021). Genomic evaluations using data recorded on smallholder dairy farms in low- to middle-income countries. JDS Communications, 2 (6), 366-370. doi: 10.3168/jdsc.2021-0092
Powell, Owen M., Voss-Fels, Kai P., Jordan, David R., Hammer, Graeme and Cooper, Mark (2021). Perspectives on applications of hierarchical gene-to-phenotype (G2P) maps to capture non-stationary effects of alleles in genomic prediction. Frontiers in Plant Science, 12 663565, 663565. doi: 10.3389/fpls.2021.663565/full
Cooper, M., Powell, O., Voss-Fels, K. P., Messina, C. D., Gho, C., Podlich, D. W., Technow, F., Chapman, S. C., Beveridge, C. A., Ortiz-Barrientos, D. and Hammer, G. L. (2021). Modelling selection response in plant breeding programs using crop models as mechanistic gene-to-phenotype (CGM-G2P) multi-trait link functions. in silico Plants, 3 (1) diaa016, 1-21. doi: 10.1093/insilicoplants/diaa016
Spatial modelling improves genetic evaluation in smallholder breeding programs
Selle, Maria L., Steinsland, Ingelin, Powell, Owen, Hickey, John M. and Gorjanc, Gregor (2020). Spatial modelling improves genetic evaluation in smallholder breeding programs. Genetics Selection Evolution, 52 (1) 69. doi: 10.1186/s12711-020-00588-w
A two-part strategy using genomic selection in hybrid crop breeding programs
Powell, Owen, Gaynor, R. Chris, Gorjanc, Gregor, Werner, Christian and Hickey, John (2020). A two-part strategy using genomic selection in hybrid crop breeding programs.
Cowling, Wallace A., Gaynor, R. Chris, Antolin, Roberto, Gorjanc, Gregor, Edwards, Stefan M., Powell, Owen and Hickey, John M. (2020). In silico simulation of future hybrid performance to evaluate heterotic pool formation in a self-pollinating crop. Scientific Reports, 10 (1) 4037. doi: 10.1038/s41598-020-61031-0
APSIM-WGP: A Software Platform to Predict Crop GxExM Interactions
Powell, Owen, McLean, Greg, Brider, Jason, Hammer, Graeme and Cooper, Mark (2023). APSIM-WGP: A Software Platform to Predict Crop GxExM Interactions. GxExM Symposium II, Gainesville, FL United States, 6-7 November 2023.
Tomura, Shunichiro, Powell, Owen and Cooper, Mark (2023). Random Forest Importance Diagnostics can Capture Quantitative Genetic Properties of Markers for Genomic Prediction. International Congress of Genetics, Melbourne, VIC Australia, 16-21 July 2023. figShare. doi: 10.6084/m9.figshare.24211230.v1
GPU can Accelerate the Prediction of Complex Phenotypes
Tomura, Shunichiro, Powell, Owen and Cooper, Mark (2023). GPU can Accelerate the Prediction of Complex Phenotypes. Australasian Leadership Computing Symposium, Canberra, ACT Australia, 14-16 June 2023. doi: 10.6084/m9.figshare.24484831.v1
Hierarchical Gene-Phenotype Maps as a Framework to Predict GxExM Interactions
Powell, Owen, McLean, Greg, Brider, Jason, Technow, Frank, Tang, Tom, Messina, Carlos D., Hammer, Graeme and Cooper, Mark (2023). Hierarchical Gene-Phenotype Maps as a Framework to Predict GxExM Interactions. Quantitative Genetics and Genomics Gordon Research Conference, Ventura, CA, United States, 12-17 February 2023.
Integrating Hierarchical G2P Maps with Genomic Prediction
Powell, Owen, McLean, Greg, Brider, Jason, Technow, Frank, Tang, Tom, Messina, Carlos D., Hammer, Graeme and Cooper, Mark (2022). Integrating Hierarchical G2P Maps with Genomic Prediction. Interdrought VII - The 7th Congress on plant production in water-limited environments, Dakar, Senegal, 1 December 2022.
Utilising prior knowledge to improve breeding
Powell, Owen, Barbier, Francois, Voss-Fels, Kai, Beveridge, Christine and Cooper, Mark (2022). Utilising prior knowledge to improve breeding. GxExM Symposium, Brisbane, QLD Australia, 3-4 November 2022.
Transferring prediction models: from model organisms to crops
Powell, Owen, Barbier, Francois, Fichtner, Franziska, Sukumaran, Sivakumar, McLean, Greg, Brider, Jason, Technow, Frank, Tang, Tom, Messina, Carlos D., Jordan, David, Hammer, Graeme, Beveridge, Christine and Cooper, Mark (2022). Transferring prediction models: from model organisms to crops. TropAg International Agriculture Conference, Brisbane, QLD, Australia, 31 October - 2 November 2022.
Powell, Owen, McLean, Greg, Brider, Jason, Technow, Frank, Sukumaran, Sivakumar, Jordan, David, Hammer, Graeme and Cooper, Mark (2022). Increasing Predictive Ability for Crop Improvement: Linking Crop Growth Models with Whole Genome Prediction. AuSoRGM, Toowoomba, QLD Australia, 18-19 August 2022.
Smith, Millicent, Robinson, Hannah and Powell, Owen (2022). ON the Pulse. Protein Futures, Brisbane, QLD, Australia, 15 June 2022.
An Ecophysiology-Inspired Gene-Phenotype Map for Breeding
Powell, Owen, Technow, Frank, Messina, Carlos D., McLean, Greg, Brider, Jason, Van Oosterom, Erik, Wu, Alex, Jordan, David, Hammer, Graeme and Cooper, Mark (2022). An Ecophysiology-Inspired Gene-Phenotype Map for Breeding. Australasian Plant Breeding Conference, Gold Coast, QLD, Australia, 9-11 May 2022.
A Two-Part Strategy for using Genomic Selection in Hybrid Crop Breeding Programs
Powell, Owen, Gaynor, Chris R., Gorjanc, Gregor, Werner, Christian and Hickey, John (2020). A Two-Part Strategy for using Genomic Selection in Hybrid Crop Breeding Programs. The 6th International Conference of Quantitative Genetics, Brisbane, QLD, Australia, 3-13 November 2020.
The impact of physiological non-additivity on variance components for complex traits
Voss-Fels, Kai, Powell, Owen, Jordan, David, Hammer, Graeme, Barbier, Francois, Werner, Christian, Hayes, Ben, Beveridge, Christine and Cooper, Mark (2020). The impact of physiological non-additivity on variance components for complex traits. The 6th International Conference on Quantitative Genetics, Brisbane, QLD Australia, 3-13 November 2020.
Can genomic data enable genetic evaluation with phenotypes recorded on smallholder farms?
Powell, Owen, Jenko, Janez, Gorjanc, Gregor, Mrode, Raphael and Hickey, John M. (2019). Can genomic data enable genetic evaluation with phenotypes recorded on smallholder farms?. Interbull Bulletin, Auckland, New Zealand, 7-11 February 2018. Uppsala, Sweden: International Bull Evaluation Service.
Can Genomics Enable Genetic Evaluations with Phenotypes Recorded on Smallholder Dairy Farms?
Powell, Owen, Jenko, Janez, Gaynor, Chris R., Banos, Georgios, Gorjanc, Gregor and Hickey, John (2018). Can Genomics Enable Genetic Evaluations with Phenotypes Recorded on Smallholder Dairy Farms?. Keystone Symposium, Kampala, Uganda, 25-29 November 2018.
Can genomics enable genetic evaluations with phenotypes recorded on smallholder dairy farms?
Powell, Owen, Jenko, Janez, Gaynor, Chris R., Banos, Georgios, Gorjanc, Gregor and Hickey, John (2018). Can genomics enable genetic evaluations with phenotypes recorded on smallholder dairy farms?. Big Data In Agriculture: DuPont Pioneer Symposia Series, Edinburgh, Scotland, United Kingdom, 14-15 May 2018.
Powell, Owen and Cooper, Mark (2023). Stochastic Simulation of Divergent Selection Experiment on a Gene-Phenotype Network: A Case Study of Shoot Branching in Plants. figShare. (Dataset) doi: 10.6084/m9.figshare.23590083
Extending the breeder’s equation to take aim at the Target Population of Environments
Cooper, Mark, Owen Powell, Gho, Carla, Tang, Tom and Messina, Carlos (2022). Extending the breeder’s equation to take aim at the Target Population of Environments.
Powell, Owen M., Barbier, Francois, Voss-Fels, Kai P., Beveridge, Christine A. and Cooper, Mark (2022). Investigations into the emergent properties of gene-to-phenotype networks across cycles of selection: a case study of shoot branching in plants.
Designing breeding programs in the genomic era
Owen Powell (2021). Designing breeding programs in the genomic era. PhD Thesis, The Roslin Institute, The University of Edinburgh . doi: 10.7488/era/1463
Breeding with an eye on genes for paddocks
Powell, Owen and Cooper, Mark (2020, 10 02). Breeding with an eye on genes for paddocks Groundcover
ON the Pulse - benchmarking protein quality for chickpea
(2023–2024) UQ Knowledge Exchange & Translation Fund
Predicting Plant Success For Future Generations
Doctor Philosophy — Principal Advisor
Other advisors:
Experimental investigation in Arabidopsis thaliana of realised selection trajectories for complex branching and flowering traits under the control of gene networks following application of genomic prediction methods.
Doctor Philosophy — Associate Advisor
Other advisors:
Genomic selection for finfish Breeding Programs
Doctor Philosophy — Associate Advisor
Other advisors:
Innovative phenotyping technologies to harness genetic diversity in tropical crops
Doctor Philosophy — Associate Advisor
Assessment of machine learning methods to discover novel models of gene networks to improve genomic prediction for plant breeding
Doctor Philosophy — Associate Advisor
Other advisors:
New mate allocation strategies to accelerate genetic gain in agricultural species.
Doctor Philosophy — Associate Advisor
Other advisors:
Optimising Genomic Selection for Sugarcane
(2023) Doctor Philosophy — Associate Advisor
Other advisors: