Use of Average Molecular Weights for Product Categories to Predict Freezing Characteristics of Foods

摘要

In the design of food freezing process, food property parameters, initial freezing temperature (T_(Fi)), and frozen water fraction (X_I) are required. The predictive approaches of these 2 parameters have been developed based on mass fractions and molecular weights of specific food components such as proteins, carbohydrates, minerals, and acids/bases. In this study, the molecular weights of the key mineral and acid/base components were successfully represented using average molecular weights (M) and 4 T_(Fi) and X_I calculation approaches were proposed. Based on an analysis of 212 food products, the absolute differences (AD) between the experimental and predicted T_(Fi) values for the 4 approaches were small. The prediction for the food model category was excellent with average AD (AD) values as low as ± 0.03 ℃. For the other food categories, the prediction efficiency was impressive with AD values between ± 0.22 and ± 0.38 ℃. The predicted relationship between temperature and X_I for all analyzed food products provided close agreements with experimental data.