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Prediction of Frozen Food Properties during Freezing Using Product Composition
Author(s) -
Boonsupthip W.,
Heldman D.R.
Publication year - 2007
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.1750-3841.2007.00364.x
Subject(s) - molality , food science , chemistry , composition (language) , fraction (chemistry) , mathematics , chromatography , philosophy , linguistics , aqueous solution
Frozen water fraction (FWF), as a function of temperature, is an important parameter for use in the design of food freezing processes. An FWF‐prediction model, based on concentrations and molecular weights of specific product components, has been developed. Published food composition data were used to determine the identity and composition of key components. The model proposed in this investigation had been verified using published experimental FWF data and initial freezing temperature data, and by comparison to outputs from previously published models. It was found that specific food components with significant influence on freezing temperature depression of food products included low molecular weight water‐soluble compounds with molality of 50 μmol per 100 g food or higher. Based on an analysis of 200 high‐moisture food products, nearly 45% of the experimental initial freezing temperature data were within an absolute difference (AD) of ± 0.15 °C and standard error (SE) of ± 0.65 °C when compared to values predicted by the proposed model. The predicted relationship between temperature and FWF for all analyzed food products provided close agreements with experimental data (± 0.06 SE). The proposed model provided similar prediction capability for high‐ and intermediate‐moisture food products. In addition, the proposed model provided statistically better prediction of initial freezing temperature and FWF than previous published models.