Premium
Comparison of Mean and Consensus Scores from Flavor and Texture Profile Analyses of Selected Food Products
Author(s) -
SYARIEF HIDAYAT,
HAMANN D. D.,
GIESBRECHT F. G.,
YOUNG CLYDE T.,
MONROE R. J.
Publication year - 1985
Publication title -
journal of food science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.772
H-Index - 150
eISSN - 1750-3841
pISSN - 0022-1147
DOI - 10.1111/j.1365-2621.1985.tb13763.x
Subject(s) - statistics , flavor , mathematics , principal component analysis , texture (cosmology) , coefficient of variation , analysis of variance , food science , artificial intelligence , computer science , chemistry , image (mathematics)
Mean and the consensus scores from flavor and the texture profile analyses of selected food products were compared to determine which is superior for the purpose of statistical analysis. Results from the analysis of variance indicated that the mean scores gave a smaller coefficient of variation than the consensus scores for most of the character notes evaluated. When principal component analysis was applied to both the mean and the consensus scores, mean scores produced a higher “cumulative proportion of variance accounted for” by the component. The results of this study suggest that using the mean scores from flavor profile or texture profile analyses is superior to using consensus scores.