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Quick and dirty but still pretty good: a review of new descriptive methods in food science
Author(s) -
Valentin Dominique,
Chollet Sylvie,
Lelièvre Maud,
Abdi Hervé
Publication year - 2012
Publication title -
international journal of food science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.831
H-Index - 96
eISSN - 1365-2621
pISSN - 0950-5423
DOI - 10.1111/j.1365-2621.2012.03022.x
Subject(s) - computer science , aka , profiling (computer programming) , descriptive statistics , sensory analysis , sorting , data mining , artificial intelligence , data science , statistics , mathematics , algorithm , library science , operating system
Summary For food scientists and industrials, descriptive profiling is an essential tool that involves the evaluation of both the qualitative and quantitative sensory characteristics of a product by a panel. Recently, in response to industrial demands to develop faster and more cost‐effective methods of descriptive analysis, several methods have been offered as alternatives to conventional profiling. These methods can be classified in three families: (i) verbal‐based methods (flash profile and check‐all‐that‐apply), (ii) similarity‐based methods (free sorting task and projective mapping aka Napping ® ) and (iii) reference‐based methods (polarised sensory positioning and pivot profile). We successively present these three classes of methods in terms of origin, principles, statistical analysis, applications to food products, variations of the methods and the Pros and Cons.