Pictured above (L-R) Sebastian J Schultheiss, Mark Cooper, Rupashree Dass, Owen Powell, István Dékány Computomics and the Australian Research Council (ARC) Centre of Excellence for Plant Success in Nature and Agriculture administered by The University of Queensland will collaborate on the investigation of machine learning methods to enhance complex trait predictions and accelerate genetic gain for plant breeding. Under this
Following the success of the 2022 Symposium in Brisbane, the Centre partnered with the University of Florida (UF) Institute of Food and Agricultural Sciences and UF Horticultural Sciences Department to host the two-day hybrid Genotype x Environment x Management (GxExM) Symposium II in Gainesville, Florida and online. Through his work with the Centre, Chief Investigator Mark Cooper led the creation
Phenotypic prediction based on genotypic make-up is a key challenge in plant improvement. It relies on access to large data sets on breeding populations and advanced genome-to-phenome (G2P) prediction methods. One of the challenges of public sector research on plant breeding is in the scale of investment and experimentation possible. Universities do not have the funding capacity to do testing
Nobel laureate Sydney Brenner famously said that all problems in biology are versions of three basic questions: How does it work? How is it built? How did it get that way? I’m both pleased and excited, to be one of the members of the Scientific Advisory Panel for the Centre. My background is a bit like the infinitesimal model, in that I know a
Researchers have unravelled the mystery of sugarcane genetics, finding the crop’s genome is three times the size of the human genome and more complex. After a decade of research, scientists from The University of Queensland, Australia’s national science agency CSIRO and Sugar Research Australia (SRA) have been able to fully map the sugarcane genome for the first time. Co-author Professor
