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Identification of Key Textural Attributes of Fluid and Semi‐Solid Foods Using Regression Analysis
Author(s) -
KOKINI JOZEF L.,
POOLE MARGARET,
MASON PHILLIP,
MILLER SUSAN,
STIER ELIZABETH F.
Publication year - 1984
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.1365-2621.1984.tb13666.x
Subject(s) - regression analysis , regression , key (lock) , mathematics , identification (biology) , statistics , value (mathematics) , set (abstract data type) , linear regression , computer science , biology , botany , computer security , programming language
Regression analysis was used to identify key attributes from 15 textural terms generated by a panel for 27 fluid and semi‐solid commercial foods. A search using single independent variables showed that “thick” gave the best average R 2 with a value of 0.548; a search with two independent variables showed that “thick” and “soft” gave the best average R 2 of 0.748; a search with three attributes showed that “slippery”, “thick,” and “soft” gave the highest R 2 values of 0.803. The final equations provided a set of regression parameters which can be used to predict twelve textural attributes from scores obtained for “thick”, “soft”, and “slippery”.