Active Engineering Food & Agriculture

Utilising food waste as a feedstock for the production of functional food ingredients from yeast

In plain English

AI plain-English summary

Every year, the UK throws away millions of tonnes of food waste that could instead be fed to yeast to produce valuable ingredients for the food industry. This project trains doctoral students to turn that waste into a resource. The core problem is simple: food waste is both an environmental and economic liability, while the food industry relies on imported or resource-intensive ingredients. Yeast can be grown on waste streams—like fruit peels or spent grains—and engineered to produce functional food ingredients, such as natural flavours, colours, or texturisers. The research addresses a gap in how to do this efficiently and at scale. If successful, this work could help shift food manufacturing from a linear "take-make-dispose" model toward a circular one. Instead of sending waste to landfill or anaerobic digestion, processors could use it as a low-cost feedstock. The result would be cheaper, more sustainable ingredients for products people already eat, and a reduced environmental footprint for the food supply chain. Because this is a training grant, the primary output is skilled researchers who can take these ideas into industry or academia. The immediate practical application is not guaranteed, but the fundamental science of yeast metabolism and waste valorisation is a necessary step toward making food production more resource-efficient.

View original technical description
Doctoral Training Partnerships: a range of postgraduate training is funded by the Research Councils. For information on current funding routes, see the common terminology at https://www.ukri.org/apply-for-funding/how-we-fund-studentships/. Training grants may be to one organisation or to a consortia of research organisations. This portal will show the lead organisation only.

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Original classification

Training Grant

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.