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Correlation between Cheese Meltability Determined with a Computer Vision Method and with Arnott and Schreiber Tests
Author(s) -
Wang H.H.,
Sun D.W.
Publication year - 2002
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.1365-2621.2002.tb10670.x
Subject(s) - positive correlation , negative correlation , medicine
ABSTRACT: Meltability of different brands of Cheddar and Mozzarella cheeses was determined with a novel computer vision method as well as with 2 traditional methods, that is, the Arnott and Schreiber tests. Correlation between the results of these methods was analysed and it showed that the meltability determined with a computer vision system was significantly (P < 0.0001) interrelated with the Arnott (R 2 = 0.69) and Schreiber (R 2 = 0.88) meltabilities. The computer vision method provided an accurate quantitative account of the physical changes in cheese during melting, and thus was capable of revealing meltability differences of cheese that were difficult to distinguish by the traditional methods. The new approach was also applicable to a wide range of cheeses.