This project began in 2019 as part of a search for methods for linking food production (crops and livestock), food processing (preservation, blending and value adding) and nutritional density (fibre and nutrients for optimal health). While a great deal of work has been and is being done in each of these three areas, there are no models that put them together in a fully integrated way. An unusual feature of this model is that it starts with the theoretical maximum potential for a wide range of food stuffs. It then identifies and quantifies the impact of limiting factors that reduce these maxima during the production and processing phases.
It enables users of the model to identify crucial success factors and potential leverage points and to ask ‘what-if’ questions for a wide range of food stuffs. The model is cumulative so that, as data is added, its predictive value is expected to increase. A crucial requirement of the model is that it is simple to use and be available to food producers, processors and policy advisors.
A proof of concept was completed in May 2020 using conceptual templates that are now ready for wider application. Early testing on wheat in Australia and Germany and rice in the Philippines, Vietnam and Australia has shown the model is capable of making reasonably accurate predictions. We are now looking for research students and potential partners to apply the model to a wider range of food stuffs from the horticulture, aquaculture and the live stock industries. We are particularly interested in people with programming experience and an interest in food and nutrition.
This Project is open to Honours or Masters students. To find out more, please contact Dr Rob Dyball.