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Socio-Economic Objective : Wheat
Research Topic : Predictive Modelling
Australian State/Territory : SA
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Agricultural Systems Analysis and Modelling (2)
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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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    Funded Activity

    Linkage Projects - Grant ID: LP150100055

    Funder
    Australian Research Council
    Funding Amount
    $395,000.00
    Summary
    Co-variant analysis and statistical modelling for improved crop yield. This project plans to develop mathematical tools that will help to identify cereal plant varieties with the highest yield. This is a critical responsibility of plant breeders and many Australian breeders acquire and store important information related to the issue. However, there are as yet no mathematical tools that are able to co-analyse the heterogeneous and high-dimensional data in order to understand how external and int .... Co-variant analysis and statistical modelling for improved crop yield. This project plans to develop mathematical tools that will help to identify cereal plant varieties with the highest yield. This is a critical responsibility of plant breeders and many Australian breeders acquire and store important information related to the issue. However, there are as yet no mathematical tools that are able to co-analyse the heterogeneous and high-dimensional data in order to understand how external and internal factors correlate with the major growth and development stages at the crop level. This project seeks to develop and implement mathematical and statistical tools to analyse genetic, agronomic and phenomic factors that affect plant performance, to deliver advanced yield prediction.
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    Funded Activity

    Linkage Projects - Grant ID: LP120100201

    Funder
    Australian Research Council
    Funding Amount
    $431,000.00
    Summary
    Enhancing stress tolerance in plants by manipulation of properties of stress responsive transcription factors. This project will describe structural and functional properties of cereal transcription factors that are critical to plant development under hostile environmental conditions. The knowledge of the revealed molecular mechanisms of transcription factors will open avenues to developments of improved crop plants.
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    Showing 1-3 of 3 Funded Activites

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