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EVALUATION OF PANELIST PERFORMANCE IN DESCRIPTIVE PROFILING OF RANCID SAUSAGES: A MULTIVARIATE STUDY
Author(s) -
SINESIO FIORELLA.,
RISVIK EINAR.,
RØDBOTTEN MARIT.
Publication year - 1990
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.1990.tb00480.x
Subject(s) - partial least squares regression , principal component analysis , multivariate statistics , procrustes analysis , statistics , mathematics , cluster analysis , multivariate analysis , sensory analysis , sensory system , food science , psychology , artificial intelligence , pattern recognition (psychology) , computer science , chemistry , cognitive psychology
. This paper illustrates an application of principal component analysis (PCA), partial least squares regression (PLS) and generalized procrustes analysis (GPA) to evaluate the ability of a trained group of assessors to perceive rancidity in foods. PCA and regression PLS were utilized to determine to which extent sensory attributes capture the information perceived by a trained sensory panel, and if this can be developed into a predictive model for rancidity in sausages. The data were submitted to a GPA to obtain a map of the products for each subject as compared with a consensus products map. Assessors plots for the sensory attributes were also obtained to reveal the dissimilarities between panelists and to explore clustering.