A major Pathways to Market project is creating a traceability system to track and monitor southern rock lobster that will be transferable to other perishables.
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Transforming Food Industry Futures through Improved Sensing, Provenance and Choice
Consumers and regulators around the world are demanding more information about the source, sustainability and quality of food. Growers, processors, distributors, and buyers must respond effectively to compete and remain in business.
Pathways to Market conducts leading edge research in on-farm and supply chain sensing to enhance decision-making from paddock to plate using business and computer and information science. The project develops smart sensing, telemetry, data visualisations applications monitor, predict and model alternative solutions to manage logistics planning, food provenance, safety and quality, environmental performance, food value chain optimisation, consumer choice and market behaviour in diverse food supply chains.
Two prototype digital dashboards have been developed for industry partners that have co-invested in this research and development – one facilitating the optimisation of farm management based on the acquisition and manipulation of disparate, dynamic datasets; and the other supporting marketing decisions based on the application of discrete choice modelling to consumer survey data.
A third dashboard is currently under development to facilitate better informed decision making across the entire supply chain from remote farms to retailers nationally and internationally. The objective being to optimise the supply chain at every opportunity through increasing accuracy and lead time of predictive information – farm management, freight logistics management, marketing and promotion and volume available to retailers.
The Pathways to Market project is a five-year research collaboration providing digitally-backed solutions to Australian food exporters and their supply chains. This $5 million project is funded jointly by the Australian Research Council, the University of Tasmania and industry participants.
Our focus is providing integrated solutions to the difficult multi-mode supply chain problems through generating, aggregating and sharing rich information through food supply chains which creates value for industry, government and community
This Industrial Transformation Research Hub is funded by the Australian Research Council
Using novel approaches to on-farm, post-harvest data collection and management, visualisation and traceability protocols, we are creating real impact along premium beef, cool-water rock lobster and mango supply chains.
The aim is to identify and implement novel digital and modelling solutions that solve challenges and improve decision making at a range of levels, from individual farm to the whole supply chain.
This is a huge opportunity for participants and stakeholders across the Australian produce and food industries, particularly those who are striving to establish, capture and maintain premium status and value in international markets.
In close collaboration with our partners, HW Greenham & Sons Pty Ltd we have been able to investigate and apply concepts of sensing, provenance and choice across multiple aspects of the premium beef supply chain, enabling more informed decision making and providing transparency of many aspects that add or diminish value along the supply chain.
There are many technologies for ‘telemetry’ or transmitting data to a distant receiving station, so Pathways to Market is conducting some world-first research to compare the performance of some of the leading telemetry technologies.
Nano-satellites potentially offer many advantages over alternative technologies for rural areas. Pathways to Market has formed a collaboration with Fleet Space Technologies, an Adelaide-based Australian cubesat company, to include a satellite telemetry option for rural data communications. This will enable choices for chain managers about the most cost-effective means for uplifting data to the cloud taking into account the typography, climatic conditions, distance and interference from other radio transmissions.
This work will be incorporated into Professor Mark Tamplin's food stability sensor to provide real time monitoring, GPS positioning and shelf-life prediction for food products all the way to international markets.
Led by Associate Professor Laurie Bonney together with the team of Research Engineers at Sense-T
Decision Support ‘dashboards’ integrate a variety of public and proprietary information with data from sensors at various points along the value chain to aid management decision making. The Decision Support Systems enables real time data to be reviewed and utilised at the time the decision is required to be made, and the impact of that decision can be monitored in a timely manner.
Led by Associate Professor Laurie Bonney together with Software Engineer Mr Ben Cameron
Generating data-driven models to predict the safety and quality attributes of food products as they move through the supply chain from the farm gate to the consumer.
A model has been developed to predict the growth of microorganisms such as bacteria in vacuum-packed premium beef, validated in both simulated and actual commercial supply chains.
For simulated conditions, meat packs were subjected to static and fluctuating temperatures to simulate increases in temperature during loading operations and potentially abusive temperatures.
For commercial supply chains, temperature sensors were positioned in consignment containers and count levels determined for product prior to shipment. At the end of shipment, sensors were retrieved and count levels measured. The results validated the use of a laboratory-generated model in actual commercial supply chains, providing industry with relevant tools for supply chain risk management.
Led by Professor Mark Tamplin from the University of Tasmania, Tasmanian Institute of Agriculture
Helping to increase brand value by providing buyers and consumers with data-driven information and interactive applications about food provenance and sustainability of source.
We’ve developed a clearer understanding of consumer behaviour in purchasing high quality beef products through application of discrete choice analysis and modelling. The underlying model is derived from a discrete choice experiment investigating 1002 Australian and 946 US consumer preferences and their willingness-to-pay for different beef products.
This baseline has been utilised to construct a decision support system (DSS) dashboard, a tool which allows complex market analyses to be presented via a visual decision-making device, facilitating experimentation with “what if” scenarios through an easy-to-interpret web-based interface. The interface includes an intuitive web-based visual representation of a supermarket meat cabinet shelf, allowing easier elicitation of marketing and sales data required for product pricing and positioning decisions. The system creates real-market scenarios, building visual pictures of merchandising displays, the set-up of simulated supermarket shelves, and the ability to save scenarios and generate likelihood-of-purchase information and market share data. A smart phone visualisation app has also been designed, focussing on the premium beef consumer experience.
Led by Professor Joffre Swait (formerly of UniSA), in collaboration with Greenham Pty Ltd.
Monitoring water quality in waterways is like taking a blood test to monitor the health of the human body. No solution is currently available for effective real time monitoring of dissolved inorganic nitrogen.
We have developed breakthrough technology for real-time monitoring of agricultural runoff and pollution dissolved in water. Current monitoring programs are slow to produce results and samples that are not tested real time are known to alter in composition from the time the sample is taken to the time it is tested.
With future water quality market requirements increasing, the technology will fulfil immediate unmet needs in providing an accurate, real-time monitoring solution to replace current monitoring programs for councils, local water authorities and the like.
In collaboration with Grey innovation
Consumers are demanding more information on the food they purchase and consume, and they want this information readily available and easy to access. Understanding the information that consumers are seeking and the behavioural impact that information has once it is received provides valuable insights to producers.
This research stream has developed a smartphone visualisation app, designed to better understand the role of images in situational consumer behaviour. APIs have been compiled to capture brand imaging data from social media. Images are being accrued in a data platform in order to build a big data set, which will allow the application of machine learning to develop empirical approaches to predicting consumer behaviour.
Supporting better production and environmental resource management practices through novel modelling, environmental sensing and data acquisition strategies.
A natural capital indicator (NCI) model has been developed to help evaluate the dynamics of natural capital on farms. It focuses on soils as the natural capital asset for the purpose of the modelling but is easily adaptable for other natural capital elements. Using historical data collected for an individual farm, the NCI provides an indication of the changes in natural soil capital over time. The approach enables tracking of changes in the contribution that soil natural capital makes to the agricultural production process over time, and highlights the impact of all relevant inputs: labour, chemical inputs, weather, over time.
The NCI can be used for ongoing monitoring of the stock of natural capital on farm. Once fully validated, this indicator model will provide a guide to the impact of farming practices on soil sustainability.
The demonstration applications will be used as the foundation for the evaluation of the efficacy of the modelling, the development of provenance-driven sustainable business models supported by the research and for overall evaluating the impact of the research program.
The impact assessment of the research will be done collaboratively between the academic and commercial partners. The impact assessment report will be generated at the end of the program and will involve a combination of quantitative and qualitative measures and draw on field experiments where appropriate.
Led by Associate Professor Laurie Bonney, in Collaboration with Greenham Pty Ltd.
Defined by the EU as the 'ability to track any food, feed or food-producing animal or substance that will be used for human consumption through all the stages of production, processing and distribution', Pathways to Market is creating systems to track and monitor food items as they move from production to the consumer.
This project component aims to address issues of resource management and food safety and respond to a range of supply chain requirements, including those of regulators, buyers/importers, as well as end-point consumers.
A number of trial mechanisms for traceability are in place across Tasmanian and South Australian supply chains. These include a suite of apps to convert traceability paperwork into digital forms for processors; low cost 'real time' water quality sensors for processors and boats to evaluate mortality and water quality; individual fish tagging technologies including QR-codes; integration of GS1 GTIN barcodes; and tamper evident bagging.
These systems are undergoing benchmarking to audit, assess and guide traceability improvements post implementation of specific technologies, processes or systems during impact evaluation and to date have received positive feedback from industry participants.
Developing novel digital solutions in design collaboration with Sense-T to assist performance management in the supply chain, and assessing how the economic benefits can be shared equitably by the businesses involved.
Long supply chains from remote fruit growing areas present significant logistics challenges in supplying the domestic Australian and international markets with high quality product. This element of research seeks to develop an extensible and scalable computer 'dashboard' or Decision Support System (DSS) that integrates key datasets from orchard to the retailers' DCs, to provide descriptive, predictive and prescriptive data analysis and visualisation to support managerial decision-making across the entire value chain. This includes delivering:
Led by Associate Professor Laurie Bonney from the University of Tasmania in collaboration with Perfection Fresh Australia