PhD defence by Rasmus Kranold Mikkelsen

Principal supervisor:

• Professor Charlotte Jacobsen

Co-supervisors:

• Senior Researcher Betül Yesiltas Svensson
• Associate Professor Timothy John Hobley

Examiners:

• Senior Researcher Claus Bang-Berthelsen, DTU Food
• Professor Mette Lübeck, Aalborg University
• Associate Professor Marie Hennebelle, Wageningen University

Chairperson at defence:

• Senior Researcher Jette Jakobsen, DTU Food

Resume
Moving towards a more sustainable and environmentally friendly food production means rethinking how we handle waste and instead look at it as potential side streams that contribute added value. One such side streams could be brewers’ spent grain (BSG) which constitutes around 85% of the total brewing waste, equaling around 20 kg per 100 L of beer brewed. Currently, utilization of BSG has mostly been limited to cattle feed and as a flour in bakery products, but there is a huge untapped potential.

In this PhD thesis, proteins from BSG were extracted under mild conditions using different pretreatment strategies, namely microwave assisted, ultrasound, pulsed electric field, and ohmic heating. Furthermore, previously published predictive models were used to identify emulsifying and antioxidant peptides embedded within the proteins. A selected set of synthetically produced peptides were then purchased, and their predicted properties were validated. Finally, a targeted enzymatic hydrolysis was performed to release the best performing peptides to a greater extent.

It was possible to extract proteins without pH adjustment (pH 6), but slight alkaline conditions (pH 9) significantly increased both recovery and content. Still, there is more to investigate, especially how to reduce the impurities that may affect performance.

The study showed great potential for BSG peptides as a new emulsifying and/or antioxidant ingredient, that would not only increase the sustainability of the brewing industry but also be a plant-based alternative to commonly used synthetic or animalbased ingredients. Similarly, the study demonstrated the usefulness of machine learning tools in screening starting materials for emulsifying or antioxidant activities.

A copy of the thesis is available for reading at the department.