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USING THE INTERNET FOR DESCRIPTIVE SENSORY ANALYSIS: FORMATION, TRAINING AND FOLLOW‐UP OF A TASTE‐TEST PANEL OVER THE WEB
Author(s) -
NOGUEIRATERRONES H.,
TINET C.,
CURT C.,
TRYSTRAM G.,
HOSSENLOPP J.
Publication year - 2006
Publication title -
journal of sensory studies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.61
H-Index - 53
eISSN - 1745-459X
pISSN - 0887-8250
DOI - 10.1111/j.1745-459x.2006.00060.x
Subject(s) - the internet , computer science , descriptive statistics , product (mathematics) , test (biology) , sensory analysis , training (meteorology) , statistics , artificial intelligence , mathematics , world wide web , paleontology , physics , geometry , meteorology , biology
A remote descriptive analysis panel was formed and trained over the Internet. This article outlines the steps involved in this method: (1) creation of Web sensory sessions; (2) recruitment and selection of assessors; (3) generation of descriptors; (4) training using generated descriptors; and (5) check‐up sessions. A reference panel was formed and trained conventionally: it aimed, on the one hand, at providing the necessary reference points for training the Internet panel and on the other hand, at validating the proposed method by the comparison of the results assessed on the same product by both panels. We applied our methodology to a dry sausage. Sixteen assessors carried out the complete training on 10 descriptors during 10 sessions. The results of the analysis of variance with (panel–product) interactions considering each attribute separately showed that product classification is the same for the two panels on the basis of seven descriptors out of 10. The results concerned with the performance of individual assessors showed that training duration seemed to be the most important feature in determining the level of performance of assessors remotely trained over the Internet.