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A HIERARCHICAL APPROACH TO OPTIMIZING DESCRIPTIVE ANALYSIS MULTIRESPONSE EXPERIMENTS
Author(s) -
FOGLIATTO FLAVIO S.,
ALBIN SUSAN L.,
TEPPER BEVERLY J.
Publication year - 1999
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.1999.tb00127.x
Subject(s) - sensory system , computer science , product (mathematics) , sensory analysis , design of experiments , descriptive statistics , control (management) , statistics , artificial intelligence , mathematics , psychology , cognitive psychology , geometry
The design and improvement of products and processes often calls for experiments where several response variables are analyzed simultaneously. Frequently, some of these variables are sensory attributes that can only be measured subjectively, through sensory evaluation panels or using expert opinion. In this paper we apply a multiresponse optimization procedure presented in Fogliatto and Albin 1997, to optimize a military food product where 24 sensory attributes are evaluated through descriptive analysis techniques. Our objective is to select the best design and operating control factors considering all attributes simultaneously.