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Sort and beer: Everything you wanted to know about the sorting task but did not dare to ask
- Source :
- Food Quality and Preference, Food Quality and Preference, Elsevier, 2011, 22 (6), pp.507-520. ⟨10.1016/j.foodqual.2011.02.004⟩, Food Quality and Preference, 2011, 22 (6), pp.507-520. ⟨10.1016/j.foodqual.2011.02.004⟩
- Publication Year :
- 2011
- Publisher :
- HAL CCSD, 2011.
-
Abstract
- author cannot archive publisher's version/PDF; International audience; In industries, the sensory characteristics of products are key points to control. The method commonly used to characterize and describe products is the conventional profile. This very efficient method requires a lot of time to train assessors and to teach them how to quantify the sensory characteristics of interest. Over the last few years, other faster and less restricting methods have been developed, such as free choice profile, flash profile, projective mapping or sorting tasks. Among these methods, the sorting task has recently become quite popular in sensory evaluation because of its simplicity: it only requires assessors to make groups of products perceived as similar. Previous studies have shown that this method produces sensory spaces similar to those obtained with conventional profiles but that the descriptions of the products are coarser than the descriptions yielded by sensory profiles. The aim of the present paper is to further evaluate the efficiency of the sorting task as a sensory tool. We present a series of studies highlighting the advantages and delineating the limits of the sorting task and illustrate advantages and limits using beer as the common type of stimuli. These studies underline the main issues encountered when designing sorting tasks. More precisely, we examine the potential of the sorting task to describe beer sensory characteristics, we determine the type of assessors able to perform a sorting task and we evaluate the stability of the results as well as some important methodological points (e.g. number of beers to be sorted, instructions given to the judges) that might impact the efficiency of the task.
- Subjects :
- 030309 nutrition & dietetics
Computer science
media_common.quotation_subject
Control (management)
Novices
Stability (learning theory)
Sensory system
Machine learning
computer.software_genre
Task (project management)
03 medical and health sciences
0404 agricultural biotechnology
sort
Simplicity
Sorting task
media_common
0303 health sciences
Nutrition and Dietetics
business.industry
Sorting
Beer
04 agricultural and veterinary sciences
040401 food science
Key (cryptography)
Artificial intelligence
business
computer
[SDV.AEN]Life Sciences [q-bio]/Food and Nutrition
Food Science
Experts
Subjects
Details
- Language :
- English
- ISSN :
- 09503293
- Database :
- OpenAIRE
- Journal :
- Food Quality and Preference, Food Quality and Preference, Elsevier, 2011, 22 (6), pp.507-520. ⟨10.1016/j.foodqual.2011.02.004⟩, Food Quality and Preference, 2011, 22 (6), pp.507-520. ⟨10.1016/j.foodqual.2011.02.004⟩
- Accession number :
- edsair.doi.dedup.....b65f88f44b22cf0c111f1776b26b3e12
- Full Text :
- https://doi.org/10.1016/j.foodqual.2011.02.004⟩