Intelligent bioprocessing for next-generation nutritional yeast extracts. This project aims to provide new, science-based levers for optimising the industrial production of tailormade yeast extracts for food applications. Advanced biochemical and engineering methods will be used to develop new knowledge of the links between yeast growth conditions, cell biochemistry, processing and the flavour and texture profiles of yeast hydrolysates. This understanding will allow the properties of yeast hydro ....Intelligent bioprocessing for next-generation nutritional yeast extracts. This project aims to provide new, science-based levers for optimising the industrial production of tailormade yeast extracts for food applications. Advanced biochemical and engineering methods will be used to develop new knowledge of the links between yeast growth conditions, cell biochemistry, processing and the flavour and texture profiles of yeast hydrolysates. This understanding will allow the properties of yeast hydrolysates to be accurately tuned during yeast production and processing. The resulting process improvements and innovations will increase the efficiency and quality of current yeast extract products and allow the development of new food products.Read moreRead less
Novel Multilevel Modelling Framework to Design Advanced Food Drying Process. In this project, a novel multilevel modelling framework for food drying will be developed by integrating the micro, macro, and dryer scale transport process and considering the dynamic changes in the drying environment under the intermittent application of microwave energy (IMCD). This modelling framework will be the first comprehensive scientific tool for industry for developing next-generation food drying systems, whi ....Novel Multilevel Modelling Framework to Design Advanced Food Drying Process. In this project, a novel multilevel modelling framework for food drying will be developed by integrating the micro, macro, and dryer scale transport process and considering the dynamic changes in the drying environment under the intermittent application of microwave energy (IMCD). This modelling framework will be the first comprehensive scientific tool for industry for developing next-generation food drying systems, which are expected to deliver significant improvement in energy efficiency and product quality and reduction in drying time and food waste. Finally, based on the outcomes of the modelling framework, a smart IMCD drying system will be developed to demonstrate the feasibility of the framework in industry application.Read moreRead less
A Concurrent Multiscale Model for Improved Prediction of Drying Process. This project aims to develop an innovative multiscale model for food drying, which integrates spatial and temporal nonlinear behaviours at different scales. The proposed unifying theory will capture dynamic micro level features and upscale them to macro level features through a concurrent bridging scheme. As cellular elements critically govern the drying process, the fundamental understanding captured through this theory wi ....A Concurrent Multiscale Model for Improved Prediction of Drying Process. This project aims to develop an innovative multiscale model for food drying, which integrates spatial and temporal nonlinear behaviours at different scales. The proposed unifying theory will capture dynamic micro level features and upscale them to macro level features through a concurrent bridging scheme. As cellular elements critically govern the drying process, the fundamental understanding captured through this theory will lead to more accurate prediction of drying kinetics, deformation and quality changes, and hence the development of efficient drying systems. This project will overcome a longstanding research problem and position Australia at the forefront in world drying research to reap substantial economic benefits for Australia.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC180100045
Funder
Australian Research Council
Funding Amount
$3,582,638.00
Summary
ARC Training Centre for Uniquely Australian Foods. The ARC Training Centre for Uniquely Australian Foods aims to provide a cohort of trained and industry-ready researchers who can lead the native foods industry forward. It plans to transform the native food and agribusiness sector, through the development of selected crops, foods and ingredients. The Centre will use an Indigenous governance group to oversee the process of converting traditional knowledge into branded products. Expected outcomes ....ARC Training Centre for Uniquely Australian Foods. The ARC Training Centre for Uniquely Australian Foods aims to provide a cohort of trained and industry-ready researchers who can lead the native foods industry forward. It plans to transform the native food and agribusiness sector, through the development of selected crops, foods and ingredients. The Centre will use an Indigenous governance group to oversee the process of converting traditional knowledge into branded products. Expected outcomes include technical information to support branding and market development, best practice development in social factors and legal arrangements for benefit sharing. This Centre will help drive sustainable growth of high-value products within the premium Australian food sector.
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Chemicals in compostable food contact paper packaging materials. The aim of this project is to understand the presence of persistent chemicals in recyclable and compostable food contact materials (FCMs). These types of products are destined for recycling or biowaste streams that bridge the gap from take-make-dispose and into a circular economy. Currently, the knowledge of the chemicals in these products is limited but we need to ensure that they are safe and do not unnecessarily contaminate reso ....Chemicals in compostable food contact paper packaging materials. The aim of this project is to understand the presence of persistent chemicals in recyclable and compostable food contact materials (FCMs). These types of products are destined for recycling or biowaste streams that bridge the gap from take-make-dispose and into a circular economy. Currently, the knowledge of the chemicals in these products is limited but we need to ensure that they are safe and do not unnecessarily contaminate resource recovery streams. It is expected that this project will develop a framework that could be used by industry and government to prevent chemicals of concern persisting in a circular economy, providing environmental and economic benefits through reduced risk of chemical exposure and unnecessary remediation costs.Read moreRead less
Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning proc ....Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning procedures. The new framework will recognise different conditions of city assets in real-time to make decisions. Expected outcomes of this Project include integration and easy access of assets with unique digital identities to help city councils, governments, and navigation services for real-time asset monitoring.Read moreRead less
Plant based foods: Towards sustainable and acceptable meat analogues. The project aims to address the need for engineering plant-based food products to deliver a sensory experience akin to meat. The project expects to generate new knowledge on the structural drivers for emulating meat-like texture and taste within burger products. Expected outcomes of this project include new ingredients and food characterisation methodologies, including rheology and sensory, which can be employed in rational ....Plant based foods: Towards sustainable and acceptable meat analogues. The project aims to address the need for engineering plant-based food products to deliver a sensory experience akin to meat. The project expects to generate new knowledge on the structural drivers for emulating meat-like texture and taste within burger products. Expected outcomes of this project include new ingredients and food characterisation methodologies, including rheology and sensory, which can be employed in rational food structure design. This should provide significant benefits in enhancing the consumer acceptance of plant-based foods that is required to support the rapidly growing market opportunity for them and sustainable food production.Read moreRead less
Transforming Australian bio-based industries through multiscale modelling. Agricultural and forestry biomass can be converted into feedstocks for production of biofuels and biomaterials via synthetic biology. A key challenge is the complex biomass microstructure renders it highly resistant to conversion, and pretreatment is crucial for enhancing process efficiency. Micro-CT imaging will enable particle characterisation and identification of changes in the fibre composition during pretreatment. T ....Transforming Australian bio-based industries through multiscale modelling. Agricultural and forestry biomass can be converted into feedstocks for production of biofuels and biomaterials via synthetic biology. A key challenge is the complex biomass microstructure renders it highly resistant to conversion, and pretreatment is crucial for enhancing process efficiency. Micro-CT imaging will enable particle characterisation and identification of changes in the fibre composition during pretreatment. This information will be used to create a virtual biomass particle model for an in silico investigation to inform optimal process design. The framework will transform the way biomass is processed, contributing to the growth of the Australian bio-manufacturing industry by making it more productive, profitable and sustainable.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210101297
Funder
Australian Research Council
Funding Amount
$429,000.00
Summary
A novel, dictionary-free, multi-contrast MRI method for microscopic imaging. This project aims to develop a novel quantitative imaging technique for comprehensive in vitro and in vivo tissue characterisation on the microscopic scale. The technology innovated in the project could revolutionise microscopic imaging techniques by breaking through the sub-millimetre image resolution bottleneck of current magnetic resonance imaging (MRI) methods. This project expects to generate new knowledge in the e ....A novel, dictionary-free, multi-contrast MRI method for microscopic imaging. This project aims to develop a novel quantitative imaging technique for comprehensive in vitro and in vivo tissue characterisation on the microscopic scale. The technology innovated in the project could revolutionise microscopic imaging techniques by breaking through the sub-millimetre image resolution bottleneck of current magnetic resonance imaging (MRI) methods. This project expects to generate new knowledge in the emerging field of biological imaging and to deliver an integrated imaging platform for mapping various tissue microscopic components at the cellular level. Successful outcomes have the potential for commercialisation and will accelerate a range of fundamental science and engineering studies requiring imaging techniques.Read moreRead less
Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it i ....Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it is not clear to the end user how reliable the results are. The outcomes intend to deliver advanced knowledge and capability in artificial intelligence and machine learning that Australia urgently needs to capitalise on bringing deep learning into practical applications delivering economic, commercial and social impact.Read moreRead less