- Start date: 1 October 2022
- End date: 31 October 2025
- Funder: BBSRC/NERC, Molecules to Landscapes
- Value: £1,579,451
- External primary investigator: Marcus Tindall, University of Reading
- Co-investigators: Professor Andy Challinor
Around 90% of the UK population consumes less than the government recommended 30g of fibre per day. Low fibre intake is linked to higher risk of bowel cancer (the second highest mortality rate cancer for men and women in the UK) and long term chronic diseases (particularly type 2 diabetes and cardiovascular disease). White bread accounts for 76% of bread sold in the UK with around 12 million loaves being sold each day. Coupled with its high popularity, the need for increased fibre in the diet and gradual rather than abrupt changes to dietary fibre intakes (e.g. from white to wholegrain) to keep consumers onside, increasing the fibre content of white bread is highly likely to contribute to increasing overall UK dietary fibre intake. Current fibre enhanced white breads (e.g. 50:50) use expensive imported wholemeal wheat, which cannot be grown in the UK. We will use newly developed fibre enhanced white flour, which can grow in the UK, to maintain the white nature of the bread and keep costs down. The white flour also has the potential to be used in other bakery related products such as croissants, naan breads and pizzas, which will be explored by industry stakeholders in this project.
Utilising a combined behavioural, food technology and predictive modelling approach, informed by close collaboration with industry, our project will identify what transformation in the UK wheat agri-food chain is needed to deliver high fibre white loaf bread to consumers. Our project has been developed in collaboration with ASDA, their associated millers and bakers (Allied Technical Centre; ATC), seed producers (Limagrain), UK wheat chain associated bodies (UK Flour Millers and the Agricultural Horticultural Development Board) and a grain broker (Agricole).
Our combined consumer behaviour and food technology studies will determine the acceptability of fibre-rich white bread, whilst economic behavioural studies will focus on how sectors in the wheat agri-food supply chain (production to manufacturing and distribution) relate to one another. The first piece of work will ensure bread is produced which consumers want to purchase, whilst the second will inform the development of our Wheat Chain Model (WCM). This will be developed in collaboration with industry and informed by concurrent modelling of UK farming land usage (LUAM model), UK seasonal weather variation and changing climate impacts on UK domestic wheat production (GLAM-UK model) and international imports (GLAM model). Both the LUAM and GLAM models have previously accounted for wheat, and the GLAM model will be adapted to the UK during our project. Life Cycle Assessment work will help determine which environmental impacts might be affected by the change in wheat cultivars and include an uncertainty and sensitivity analysis of these impacts,
The WCM will account for the dynamics of the UK wheat agri-food chain and take account of domestic production versus flour received from imports. Industry informed modelling with all industry partners and their respective associations will quantify the transformational steps needed to increase fibre-rich flour production against a complex backdrop of domestic and imported wheat demand. We will utilise a range of data to inform the WCM including publicly available data such as the Farm Business Survey, data available via our industry partners, surveys of UK Flour Miller members and other industry stakeholders. Data collected during the project on how participants in the chain relate to one another will be analysed. It will both inform our WCM, and be available to other researchers and the public via our project website. We will create a graphical user interface (GUI) for our Wheat Chain Model. This will allow stakeholders and policy makers access to the model both during and after the project and the generic nature of the model will mean it can easily be applied to other agri-food chains, besides wheat.