SFN virtual sandpit 2020


SFN virtual sandpit 2020

The Science and Technology Facilities Council (STFC) Food Network+ (SFN) brings together STFC researchers and facilities with research and industry in the agri-food sector. The SFN is building an interdisciplinary community working to provide a sustainable, secure supply of safe, nutritious, and affordable high-quality food using less land, with reduced inputs, and in the context of global climate change and declining natural resources.

The SFN recently hosted a virtual sandpit. During the event, sandpit participants develop ideas for collaborative projects in response to food-related challenges and present their proposals to each other.

Bringing together experts from food systems research, industries, policy, and STFC scientists to innovate and co-design scoping projects that can address the current challenges faced by food systems across food production, supply chain, nutritional security and consumer behaviour in the UK, Africa and Asia through the applications of data science, technologies and STFC facilities.

The winning projects for each theme are decided by democratic vote and receive funding to deliver their projects.

Resilient food supply chains at uncertain times.

We presented a collaboration between Edward Smart from Portsmouth university; Jan Soon from Lancaster university, Femke van den Berg from Fera Science and STFC data scientists to look at metrics for food fraud. Can we identify increased food fraud during shock events? and if so, what are the key indicators for early warning of these increased fraud events. 

Food fraud costs, the UK Food economy more than 11 billion pounds a year. It is a massive threat to food security, nutrition, public health and the wider environment. Impacting all 17 of the UN Sustainable Development Goals.

Drivers and indicators of food fraud remain largely uncertain. Hence, it is the objective of our project to explore and identify correlations between shock events and food fraud. Helping us further understand these indicators that contribute to food fraud.

The project will utilise global food integrity data such as those from Horizonscan. Coupled with metrics from Eurostat Trade Import Records, FAOSTAT indexes of production and climate change.

Once we have scanned and identified the shock events and matrix. We can use the data to build our Bayesian network model to improve the predictive capability of our fraud indicators.

The team are pleased to announce our proposal was chosen as one of the winners at this year's SFN virtual sandpit and are excited to continue our research and help protect the global food supply chains.


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