Students in our Food Science department conduct their own sensory evaluations and consumer tests, giving them extensive hands-on experience in real-world research and development of food products. By the end of their studies at ISA Lille, our Food Science students are well-versed in running consumer tests and analyzing the results.
The expertise of ISA Lille’s Food Quality laboratory is focused on sensory analysis. The main research area of the team is based on a better understanding of the mechanisms of product evaluation.
We conduct experiments with different panelists to improve the training techniques used to make “experts”, and also to develop new methodologies for product sensory evaluation.
The laboratory has, among others, developed a specific expertise on beers, sugars and milk sensory evaluation. The main problem in sensory analysis is to educate sensory “experts” who will be able to describe and compare products. This training of expert panelists needs time and represents a high level of investment, so it is important to understand how experts differ from untrained consumers during testing evaluations. Finally, it is also a way to see if one day experts could be replaced by non-expert panelists while keeping the same level of product evaluation performance.
Expert vs novice panelists
Alternative sensory methodologies (Sorting Task, Pivot profil, CATA)
Cultural differences in perception
Tools and Methodologies
Sensory lab with 24 individual testing booths
Industrial kitchen Data software (Fizz)
Experimental food plant allowing the making of cheese and beer with controlled flora
HPLC, gas chromatography
Scientific and Professional Partnerships
Mc Cain, Canadian multinational frozen food company
Symoneaux R., Baron A., Marnet N., Bauduin R., Chollet S., (2014) Impact of apple procyanidins on sensory perception in model cider (Part 1): polymerisation degree and concentration. LWT - Food Science and Technology, 57, 22 -27.
Galmarini M.V., Symoneaux R., Chollet S., Zamora M.C. (2013) Understanding apple consumers’ expectations in terms of likes and dislikes: use of comment analysis in a cross- cultural study. Appetite, 62, 27-36.
Valentin D., Chollet S., Lelièvre M. & Abdi H. (2012) Quick and dirty but still pretty good: a review of new descriptive methods in food science. International Journal of Food Science and Technology, 47, 1-16.
Chollet S., Lelièvre M., Abdi H. & Valentin D. (2011) Sort and Beer: Everything you wanted to know about the sorting task but did not dare to ask. Food Quality and Preference, 22, 507-520.
Lelièvre M., Chollet S., Abdi H. & Valentin D. (2009) Beer trained and untrained assessors rely more on vision than on taste when they categorize beers. Chemosensory Perception, 2, 143-153.
Lelièvre M., Chollet S., Abdi H. & Valentin D. (2008) What is the validity of the sorting task for describing beers? A study using trained and untrained assessors. Food Quality and Preference, 19, 697-703.
Blancher G., Lê S., Sieffermann J-M. & Chollet S. (2008) Comparison of visual appearance and texture profiles of jellies in France and Vietnam and validation of attribute transfer between the two countries. Food Quality and Preference, 19, 185-196.
Valentin D., Chollet S., Béal S. & Patris B. (2007) Expertise and memory for beers and beer olfactory compounds. Food Quality and Preference, 18, 776-785.