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Prediction of Bind Value Constants of Sausage Ingredients from Protein or Moisture Content
Author(s) -
PARKS L. L.,
CARPENTER J. A.,
RAO V. N. M.,
REAGAN J. O.
Publication year - 1985
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.1365-2621.1985.tb10534.x
Subject(s) - class (philosophy) , moisture , value (mathematics) , water content , mathematics , food science , constant (computer programming) , linear regression , chemistry , biological system , computer science , biology , statistics , organic chemistry , artificial intelligence , geology , geotechnical engineering , programming language
Ingredients used in comminuted meat products were divided into four classes: Class I–striated, skeletal muscle meats; Class II – striated, nonskeletal muscle meat; Class III – organ and smooth muscle meats; and Class IV – nonmeat proteins. Within this classification scheme, bind value constants developed by different workers were subjected to regression anaylsis using protein or moisture as the independent variable. Linear or multiple regression equations with high correlation coefficients were obtained for Class I and Class III meats indicating reliable predictive value of moisture or protein content. These equations should prove useful for esimating bind value constants for meat ingredients in these classes for which such constants have not been established by experimental procedures.