Correlation between Cheese Meltability Determined with a Computer Vision Method and with Arnott and Schreiber Tests

• Published in: Journal of food science Vol. 67; no. 2; pp. 745 - 749
• Main Authors: Wang, H.-H., Sun, D.-W.
• Format: Journal Article
• Language: English
• Published: Oxford, UK Blackwell Publishing Ltd 01.03.2002; Institute of Food Technologists; Wiley Subscription Services, Inc
• Subjects: Biological and medical sciences; Cheddar; Cheese; Food industries; Food preservation; Food science; functional properties; Fundamental and applied biological sciences. Psychology; General aspects; Image analysis; Methods of analysis, processing and quality control, regulation, standards; Milk and cheese industries. Ice creams; Mozzarella; Computer vision; Melting; Cheddar; Dairy product; Mozzarella; Cheese; Physical properties; Image analysis; Analysis method; Technological properties; Comparative study; Quantitative analysis; Rheological properties
• ISSN: 0022-1147; 1750-3841
• DOI: 10.1111/j.1365-2621.2002.tb10670.x

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 (R2= 0.69) and Schreiber (R2= 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.