TASSOS KOIDIS' RESEARCH GROUP
Pushing the boundaries of Food Science
OURÂ RESEARCH THEMES
Primary Areas of Interest
Research at Tassos Koidis' Group involves understanding the relationship between food constituents and the properties of foods, whether this area its origin, authenticity or nutritional value at various stage in their production or distribution. Read on to find out more about our latest work within the Institute for Global Food Security, Queen's University Belfast.
FOOD HYPERSENSIVITY
(started Jan 2022)
This project is looking at how to improve food safety standards in online food procurement for people with food hypersensitivity. It is a citizen science-led project with citizen scientists contributing to the generation of the results. It is a collaboration with Miss Theano Stoikidou, Prof Michael Walker, Dr Hazel Gowland and Dr Jesus Martinez-Del Rincon
FOOD AUTHENTICITY
Origin and Fraud Detection
In the food authenticity and adulteration area, the group develops innovative analytical methods (LC, GC, IR) and e-decision systems that check the authenticity of foods, such as palm oil, coffee, tea and cheese. The research attracts funders such as DEFRA UK, that police sustainable food labelling.
OLIVE OIL
From soil to the oil
Looking at fundamental links between soil, the olive tree and the olive fruit right across to the olive oil produced, based on soil-plant interactions, the microbiome and its links to food quality.
NOVEL FOOD PROCESSING & PRESERVATION
Quality and Safety
We research the effect of novel food processing technologies have on the safety and quality of foods. The safety related to the survival of pathogenic bacteria and the quality relates to the retention of  bioactive constituents such as vitamins, polyacetylenes. polyphenols and other antioxidants. Technologies include High Pressure Processing, Omhic heating, volumetric microwave heating, time temperature indicators, active packaging and microbial contamination challenge studies with pathogens are also conducted while processing.
MACHINE LEARNING & AUTOMATION
aka Chemometrics
We are conducting curiosity driven, highly innovative fundamental research using multivariate modelling methods such as Partial Least Squares (PLS), Principal Component Analysis (PCA) and Support Vector Machines (SVM) in order to support food analysis. These systems will lead to development of robust e-decision system to support  managers to take informed decisions in real-time and optimise production.
CONTACT
Queen's University Belfast, Belfast, Northern Ireland