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Optimizing quick-frozen litchi thawing: a multi-objective approach integrating thermodynamic modeling and quality preservation
Faculty
Agriculture
Year:
2026
Type of Publication:
ZU Hosted
Pages:
Authors:
Mohamed Anwar Mahmoud Abdeen
Staff Zu Site
Abstract In Staff Site
Journal:
Journal of Food Measurement and Characterization Springer Nature
Volume:
Keywords :
Optimizing quick-frozen litchi thawing: , multi-objective approach
Abstract:
This study addresses the challenge of quality degradation by developing and validating a comprehensive thermodynamic model for the quick-frozen litchi thawing under hot air conditions. The fruits were subjected to liquid nitrogen fast freezing at -60 °C for 15 min, until their core temperature reached − 18 °C. Then, the quick-frozen litchis were thawed using a DJL-SLX-544 H multi-gradient hot-air thawing equipment, and the thermodynamic behavior of the litchi during thawing was observed under forced convection heat transfer conditions. Using a synergistic approach that combines rigorous experimental measurements and theoretical modeling, the accuracy of the developed model was assessed, yielding a remarkable correlation coefficient of 0.994 between measured and predicted temperatures. Furthermore, a systematic investigation explained the intricate thawing characteristics of litchi across varying temperature gradients. Then, a three-dimensional response surface model was precisely constructed to optimize the thawing process, outlining the relations among thawing temperature, specific energy consumption, and color difference (ΔE) using the NSGA-II multi-objective optimization algorithm. The optimized conditions revealed an optimal thawing temperature of 32 °C, resulting in a specific energy consumption of 3756.02 J/g and a corresponding color difference (ΔE) of 9.89. Crucially, validation experiments confirmed the reliability and robustness of the optimized parameters, demonstrating relative errors of only 4.96% for specific energy consumption and 6.07% for color difference (ΔE) when compared to the algorithmic model’s predictions. This research provides a robust framework for optimizing thawing protocols, significantly contributing to the retention of litchi quality and minimizing post-thawing quality degradation.
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