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THE AROMA OF CANNED BEEF: APPLICATION OF REGRESSION MODELS RELATING SENSORY AND CHEMICAL DATA
Author(s) -
PERSSON TYKO,
SYDOW ERIK
Publication year - 1974
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.1365-2621.1974.tb02942.x
Subject(s) - aroma , odor , sensory system , correlation coefficient , mathematics , sensory analysis , set (abstract data type) , correlation , analogy , statistics , econometrics , computer science , biological system , chemistry , food science , psychology , cognitive psychology , biology , linguistics , organic chemistry , philosophy , geometry , programming language
The purpose of this investigation was to determine general relations between instrumental and sensory aroma data from a reference material consisting of a large set of different types of beef samples analyzed during several years. The relations obtained in this way have been tested on independent “unknown” samples. Different models have been used, basically derived from Stevens' law and formulated in analogy with models used in other psychophysical contexts. From the reference material a great number of highly significant relations‐several with a correlation coefficient greater than 0.90–were obtained for the various odor notes used. Several of these seem to be examples of causative relations. When predicting sensory properties of unknown samples almost all the relations obtained with high correlation coefficient worked very well. These properties could be predicted by the gas chromatographic technique with the same accuracy as when the panel assessed the samples. Therefore, by applying the models in a proper way, the panel service in routine analyses may be supplemented or refined by using a gas chromatographic technique. These methods may, of course, also be used in product and process development work.