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VIEWS ON RELATING INSTRUMENTAL TESTS TO SENSORY ASSESSMENT OF FOOD TEXTURE. APPLICATIONS TO PRODUCT DEVELOPMENT AND IMPROVEMENT 1 , 2
Author(s) -
KAPSALIS JOHN G.,
MOSKOWITZ HOWARD R.
Publication year - 1978
Publication title -
journal of texture studies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.593
H-Index - 54
eISSN - 1745-4603
pISSN - 0022-4901
DOI - 10.1111/j.1745-4603.1978.tb01214.x
Subject(s) - product (mathematics) , sensory system , product testing , perception , texture (cosmology) , econometrics , computer science , sensory analysis , empirical research , new product development , statistics , mathematics , artificial intelligence , pattern recognition (psychology) , machine learning , marketing , psychology , cognitive psychology , business , geometry , neuroscience , image (mathematics)
Well‐defined measurements of the mechanical properties of food and the reduction of sensory attributes to the fundamental primary entities, together with the definition of their correlation functions, provide the basis for the eventual development of instruments calibrated in terms of human sensory response and having a high probability of predicting the consumer reaction. Since mechanical measurements of most foods are time‐dependent, the understanding of conditions prevailing during sensory testing (rate of shear, etc.) will aid in selecting the optimum conditions for instrumental testing. Recent progress in this area has been made with fluids and some solid foods. The method of magnitude estimation assists the researcher in discovering the underlying laws relating physical product changes to perceived textural changes. At the same time, magnitude estimation also aids the product developer to determine empirical, ad hoc relations between physical levels of mechanical variables and textural perceptions, even if the true, underlying relationships are not known. Ad hoc equations can be used (in conjunction with optimization techniques) to determine the combination of mechanical variables that (a) produce a specific sensow texture profile, and (b) maximize texture/product acceptability .