TY - JOUR
T1 - Hybrid mixture theory-based modeling of transport of fluids, species, and heat in food biopolymers subjected to freeze–thaw cycles
AU - Zhao, Ying
AU - Kumar, Pavitra Krishna
AU - Sablani, Shyam S.
AU - Takhar, Pawan S.
N1 - Funding Information:
The authors thank the USDA‐NIFA for providing financial support under the award nos. 2015‐67017‐23074, ILLU‐698‐934 and ILLU‐698‐934.
Publisher Copyright:
© 2022 The Authors. Journal of Food Science published by Wiley Periodicals LLC on behalf of Institute of Food Technologists.
PY - 2022/9
Y1 - 2022/9
N2 - Abstract: A hybrid mixture theory (HMT)-based unsaturated transport (pores not saturated with liquid) model was applied to a food matrix subjected to freezing and freeze–thaw cycles. The model can explain the fluid, species, and heat transport, ice formation, thermomechanical changes, and the freezing point depression occurring inside food biopolymers during freezing. Volume changes during freezing were calculated using the stresses due to pore pressure and the phase-change based mechanical strain. The Eulerian-Lagrangian transformation was performed for solving the equations using a finite element mesh in Lagrangian coordinates. The predicted temperature profiles for constant and fluctuating freezing temperature conditions showed agreement with experimental data with reasonable accuracy (RMSE = 2.86°C and 2.23°C, respectively). The multiscale transport model coupled with a physical chemistry-based relation was able to predict solute concentration and the freezing point depression in potatoes with greater accuracy than an empirical equation published in the literature. Sudden temperature fluctuations representing the opening and closing of a freezer door were investigated using this solution scheme, and conditions causing less damage to the food were identified. Practical Application: Food materials are subjected to freeze–thaw cycles during storage, shipping, and distribution to the consumers. The study uses numerical modeling and experimental validation to elucidate the principles affecting ice formation, solute migration, and temperature changes. Outcomes will allow processors to improve the quality of frozen foods with improved design of freezing operation, and storage and distribution strategies.
AB - Abstract: A hybrid mixture theory (HMT)-based unsaturated transport (pores not saturated with liquid) model was applied to a food matrix subjected to freezing and freeze–thaw cycles. The model can explain the fluid, species, and heat transport, ice formation, thermomechanical changes, and the freezing point depression occurring inside food biopolymers during freezing. Volume changes during freezing were calculated using the stresses due to pore pressure and the phase-change based mechanical strain. The Eulerian-Lagrangian transformation was performed for solving the equations using a finite element mesh in Lagrangian coordinates. The predicted temperature profiles for constant and fluctuating freezing temperature conditions showed agreement with experimental data with reasonable accuracy (RMSE = 2.86°C and 2.23°C, respectively). The multiscale transport model coupled with a physical chemistry-based relation was able to predict solute concentration and the freezing point depression in potatoes with greater accuracy than an empirical equation published in the literature. Sudden temperature fluctuations representing the opening and closing of a freezer door were investigated using this solution scheme, and conditions causing less damage to the food were identified. Practical Application: Food materials are subjected to freeze–thaw cycles during storage, shipping, and distribution to the consumers. The study uses numerical modeling and experimental validation to elucidate the principles affecting ice formation, solute migration, and temperature changes. Outcomes will allow processors to improve the quality of frozen foods with improved design of freezing operation, and storage and distribution strategies.
KW - diffusion
KW - freeze–thaw cycles
KW - mathematical modeling
KW - multiscale modeling
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U2 - 10.1111/1750-3841.16279
DO - 10.1111/1750-3841.16279
M3 - Article
C2 - 36049017
AN - SCOPUS:85137344479
SN - 0022-1147
VL - 87
SP - 4082
EP - 4106
JO - Journal of food science
JF - Journal of food science
IS - 9
ER -