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Calculation of full process freezing time in minced fish muscle
Francisco Cuesta1, Isabel Sánchez-Alonso1, Alfonso Navas2
1Institute of Food Science, Technology and Nutrition, Spanish National Research Council (ICTAN-CSIC), C/ José Antonio Novais 10, Madrid 28040, Spain.
Methodsx
|August 26, 2021
Summary
This study refines a food freezing time modeling method. The enhanced model accurately predicts freezing times for applications like parasite inactivation in seafood.
Area of Science:
- Food science
- Thermal engineering
- Mathematical modeling
Background:
- Accurate prediction of food freezing times is crucial for food safety and quality.
- Previous methods for modeling freezing times require enhancement for broader applications.
- Understanding temperature kinetics during freezing is essential for process optimization.
Purpose of the Study:
- To expand and refine a previously developed method for modeling food freezing times.
- To provide a versatile modeling procedure applicable to various food products and freezing scenarios.
- To simulate freezing times necessary for inactivating foodborne parasites, such as anisakids.
Main Methods:
- The method models temperature kinetics in three distinct phases: cooling, freezing, and further cooling.
- It utilizes established estimation procedures and accounts for different thermophysical properties during cooling stages.
- Freezing time is calculated first for an infinite flat plate and then corrected for finite cylindrical geometry.
Main Results:
- A detailed calculation example for freezing hake mince muscle is provided, illustrating the method's application.
- The model successfully breaks down the total freezing time into pre-freezing, freezing, and sub-freezing phases.
- The enhanced procedure offers a more accurate simulation of freezing processes in food products.
Conclusions:
- The refined modeling method provides a robust framework for predicting food freezing times.
- This approach is valuable for ensuring food safety, particularly in parasite inactivation.
- The method's adaptability makes it suitable for diverse food processing and thermal modeling applications.

