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INSTRUMENTAL AND SENSORY EVALUATION OF TEXTURAL ATTRIBUTES IN CHEESE ANALOGS: A CORRELATION STUDY
Author(s) -
PEREIRA R.B.,
BENNETT R.J.,
LUCKMAN M.S.
Publication year - 2005
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.2005.00038.x
Subject(s) - partial least squares regression , correlation , principal component analysis , pairwise comparison , sensory system , mathematics , regression , statistics , regression analysis , texture (cosmology) , flexibility (engineering) , pattern recognition (psychology) , artificial intelligence , computer science , psychology , cognitive psychology , geometry , image (mathematics)
The objective of this study was to investigate the usefulness of an array of statistical techniques to describe relationships between instrumental data and non‐oral sensory texture profiling scores by using a range of model processed cheese analogs as example. Pairwise correlation, used as an exploratory tool, showed no significant correlation for flexibility and greasiness with any individual instrumental parameter. Stepwise regression, principal component regression and partial least squares regression were used to generate models for firmness, stickiness and curdiness of the analogs studied. No models could be generated for flexibility and greasiness, and models for rubberiness had poor quality of fit compared with the other sensory attributes. In general, firmness, stickiness and curdiness were satisfactorily modeled by using chemical data and small deformation rheological parameters. Compression data (large deformation), often used in correlation studies regarding the texture of cheese, did not necessarily lead to better correlation results in comparison with other instrumental parameters used in this research.