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Current Selection
Socio-Economic Objective : Wheat
Australian State/Territory : QLD
Research Topic : VESTIBULAR DISEASE
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Crop and Pasture Improvement (Selection and Breeding) (4)
Crop and Pasture Production (4)
Quantitative Genetics (incl. Disease and Trait Mapping Genetics) (4)
Agricultural Systems Analysis and Modelling (1)
Optimisation (1)
Plant Cell and Molecular Biology (1)
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Wheat (4)
Barley (1)
Climate Change Adaptation Measures (1)
Environmentally Sustainable Plant Production not elsewhere classified (1)
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  • Active Funded Activity

    Linkage Projects - Grant ID: LP170100317

    Funder
    Australian Research Council
    Funding Amount
    $345,465.00
    Summary
    FastStack - evolutionary computing to stack desirable alleles in wheat. This project aims to investigate rapid development of new, high-yielding wheat varieties with appropriate disease resistance. An emerging challenge in wheat breeding is how to stack desirable alleles for disease resistance, drought, and end-use quality into new varieties with high yielding backgrounds in the shortest time. As the number of known desirable alleles for these traits increases, the number of possible crossing c .... FastStack - evolutionary computing to stack desirable alleles in wheat. This project aims to investigate rapid development of new, high-yielding wheat varieties with appropriate disease resistance. An emerging challenge in wheat breeding is how to stack desirable alleles for disease resistance, drought, and end-use quality into new varieties with high yielding backgrounds in the shortest time. As the number of known desirable alleles for these traits increases, the number of possible crossing combinations that need to be considered increases. This project aims to use evolutionary computing with speed breeding and genomic selection, in the partners breeding program, to address this challenge. Potential outcomes will lead to more profitable wheat varieties for Australian growers, and expanded exports to high value markets that require quality grain.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP210200723

    Funder
    Australian Research Council
    Funding Amount
    $1,062,378.00
    Summary
    Enhancing Genomic Prediction for Changing Environments in Wheat. Adverse weather is the primary risk faced by the Australian agriculture industry. This Project aims to develop the next generation of agriculture tools to unlock natural potential in wheat and improve yield stability across seasons and regions. Drawing on crop physiology, genetics and integrated modelling, this Project expects to generate new knowledge and technologies to untangle genetic and environmental interactions that affect .... Enhancing Genomic Prediction for Changing Environments in Wheat. Adverse weather is the primary risk faced by the Australian agriculture industry. This Project aims to develop the next generation of agriculture tools to unlock natural potential in wheat and improve yield stability across seasons and regions. Drawing on crop physiology, genetics and integrated modelling, this Project expects to generate new knowledge and technologies to untangle genetic and environmental interactions that affect productivity, enhance predictive capability, and initiate advanced breeding strategies to develop new crop varieties with superior resilience against changing climates. This should provide significant benefits, such as profit stability for wheat growers, elevated global market position and improved food security.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP200200927

    Funder
    Australian Research Council
    Funding Amount
    $785,312.00
    Summary
    Digging deeper to improve yield stability. This project aims to provide innovative breeding solutions that harness the ‘hidden’ part of the plant, roots, to support the development of more productive crops in the face of climate variability. The project expects to generate new insights into the biology and genetics of root development in barley, a model cereal crop, by applying cutting-edge genome editing, phenotyping and genomics technologies. Anticipated outcomes include novel methodologies to .... Digging deeper to improve yield stability. This project aims to provide innovative breeding solutions that harness the ‘hidden’ part of the plant, roots, to support the development of more productive crops in the face of climate variability. The project expects to generate new insights into the biology and genetics of root development in barley, a model cereal crop, by applying cutting-edge genome editing, phenotyping and genomics technologies. Anticipated outcomes include novel methodologies to accelerate breeding for diverse production environments, with direct applications in barley, and other major cereals including wheat and oats. This should provide significant economic and social benefits to the Australian grains industry through yield stability amidst climate variability.
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    Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE210101407

    Funder
    Australian Research Council
    Funding Amount
    $447,524.00
    Summary
    Revealing and navigating a path to climate-ready crops. This project aims to investigate how well multi-dimensional biological and environmental data can be integrated to improve the prediction of plant performance under climatic fluctuations. This project expects to generate new knowledge in the area of quantitative genetics using an approach that combines trans-disciplinary research fields. Expected outcomes of this project include an example for how to advance conventional prediction methods .... Revealing and navigating a path to climate-ready crops. This project aims to investigate how well multi-dimensional biological and environmental data can be integrated to improve the prediction of plant performance under climatic fluctuations. This project expects to generate new knowledge in the area of quantitative genetics using an approach that combines trans-disciplinary research fields. Expected outcomes of this project include an example for how to advance conventional prediction methods using fundamental biological models that underlie plant growth. This will provide significant benefits, such as an enhancement of collaborative research across areas with the potential to significantly advance the general understanding of how plants interact with the environment.
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    Showing 1-4 of 4 Funded Activites

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