Quality modeling using detailed genomics

PhD defence by Wenwen Li

Assessment Committee

Associate Professor Henrik Siegumfeldt, Food Science, University of Copenhagen (Chairperson)
Chief Process Developer at Arla Foods Søren Kristian Lillevang, Arla Foods
Professor Pawel Satora, University of Agriculture in Krakow

Supervisors

Associate Professor Lukasz Krych

Professor Dennis Sandris Nielsen

Department

Department of Food Science

Place

Building: Thorvaldsensvej 40, Room: A2-70-03, Thorvaldsensvej 40, 1871 Frederiksberg

Email address to gain access to the thesis: wenwenli@food.ku.dk.
You will either receive a copy of the thesis or be informed where you can read a physical copy.
Recipients of copies of the thesis are not allowed to share or distribute it due to copyright compliance.

Short description of the thesis

Cheese owes much of its flavour, texture and quality to communities of bacteria known as starter cultures. Yet these cultures may contain many closely related strains, making their performance difficult to understand and predict. This PhD thesis uses long-read DNA sequencing to examine starter bacteria at the strain level, including their genes and DNA methylation patterns. It also introduces practical workflows for reconstructing bacterial genomes and monitoring complex starter cultures. Finally, defined bacterial communities, aroma measurements and machine learning are combined to investigate whether gene content can predict compounds produced during fermentation. The work provides new tools and knowledge for characterizing starter cultures and supporting more consistent dairy fermentation.