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
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
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
Developing key vision technology for automation of aquaculture factory. This project aims to investigate structural, coloured textural, and hyperspectral analysis approaches to achieve automated lobster molt-cycle staging and classification to the level required for commercial production. High labour cost, water contamination, and disease transmission are major barriers in Australian bay lobster aquaculture inhibiting its large scale production. Automation of the production process and reducing ....Developing key vision technology for automation of aquaculture factory. This project aims to investigate structural, coloured textural, and hyperspectral analysis approaches to achieve automated lobster molt-cycle staging and classification to the level required for commercial production. High labour cost, water contamination, and disease transmission are major barriers in Australian bay lobster aquaculture inhibiting its large scale production. Automation of the production process and reducing the human contact with animals are of high priority in the development of this Australian-led emerging industry. The project aims to develop technology to bring this world- first aquaculture factory to large scale production, and create new export opportunities for lobsters and production systems.Read moreRead less
Flavour enhancing functional feeds for farmed Barramundi. This project aims to improve the flavour quality of Australian farmed barramundi through developing novel functional feeds. The project expects to expand our fundamental knowledge of flavour enhancement, whilst providing practical benefits with respect to final product quality. The project will enable industry to achieve higher product quality benchmarks, towards the ultimate goal of improving the marketability of barramundi both locally ....Flavour enhancing functional feeds for farmed Barramundi. This project aims to improve the flavour quality of Australian farmed barramundi through developing novel functional feeds. The project expects to expand our fundamental knowledge of flavour enhancement, whilst providing practical benefits with respect to final product quality. The project will enable industry to achieve higher product quality benchmarks, towards the ultimate goal of improving the marketability of barramundi both locally and overseas. This project will provide significant benefits to the Australian barramundi industry by increasing product values, thereby facilitating an economically sustainable growth of this important regional industry.Read moreRead less
Protein biosensors for detecting smoke exposure of grapes. Bush fires and controlled burns that take place in the vicinity of vineyards can lead to grape contamination with tasteless phenolic glucosides. Their hydrolysis during wine making leads to “smoke taint” – an unpleasant medicinal taste that can render wine undrinkable. We will apply a combination of organic synthesis, protein engineering and directed evolution to develop protein-based biosensors of phenolic glucosides. These biosensors w ....Protein biosensors for detecting smoke exposure of grapes. Bush fires and controlled burns that take place in the vicinity of vineyards can lead to grape contamination with tasteless phenolic glucosides. Their hydrolysis during wine making leads to “smoke taint” – an unpleasant medicinal taste that can render wine undrinkable. We will apply a combination of organic synthesis, protein engineering and directed evolution to develop protein-based biosensors of phenolic glucosides. These biosensors will be used to devise a simple portable colorimetric test that can be performed in the vineyard or the winery. The ability to rapidly determine the level of grape contamination with phenolic glucosides would give Australian wine growers and wine makers a powerful tool to mitigate the effects of bushfires.Read moreRead less
High performance bioderived hybrid fillers for rubber composite. This project aims to address a significant problem in polymer composite synthesis by production and application of high performance bioderived hybrid silica fillers from renewable biomass feedstock. The project expects to generate new knowledge in the area of advanced manufacturing using interdisciplinary approaches in biorefining, filler and composite production and characterization. Expected outcomes of this project include a mo ....High performance bioderived hybrid fillers for rubber composite. This project aims to address a significant problem in polymer composite synthesis by production and application of high performance bioderived hybrid silica fillers from renewable biomass feedstock. The project expects to generate new knowledge in the area of advanced manufacturing using interdisciplinary approaches in biorefining, filler and composite production and characterization. Expected outcomes of this project include a more sustainable filler production process for producing novel bioderived silica fillers with properties superior to commercial silica fillers. The successful implementation of this project will lead to the development of a new advanced manufacturing industry, creating jobs in regional Australia. Read moreRead less