15D-4 |
Thawing of skipjack tuna (Katsuwonas pelamis): A numerical simulation |
J. ZHANG1, B. E. Farkas2, and S. A. Hale1. (1) Department of Biological and Agricultural Engineering, North Carolina State University, Box 7625, Raleigh, NC 27695, (2) Department of Food Science, North Carolina State University, 129 Schaub Hall, Box 7624, Raleigh, NC 27695 The commercial canned tuna industry is the largest processor of fish in the world with single manufacturing facilities using upwards of 1000 tons raw product per day. Thawing is a critical process which affects yield and quality of the final canned tuna product. However, processing technologies have remained largely unchanged for over fifty years. Therefore, process optimization through the use of numerical simulation has great potential to lead to improvements in throughput, efficiency, and product quality for this unit operation. The goal of this research was to develop a numerical simulation of the tuna thawing process to aid in improvement of this critical processing step. The finite element method (FEM) was used to study the thawing process of skipjack tuna in preparation for canning. A two dimensional model consisting of three regions, muscle, backbone and viscera was developed. The thermal properties of these regions were measured using differential scanning calorimetry or estimated by mathematical model and the temperature dependent results utilized in the simulation. Preprocessor software, GAMBIT 1.1, and finite element software, FIDAP 8.01, were used for solution of the problem. The validity of the model was tested via comparison with data collected at a commercial processing facility. Output from the FEM model showed that small changes in thermal properties during thawing affect internal temperature profiles. Also, small changes in the convective heat transfer coefficient have a significant effect on thawing rate. The finite element method was shown to be a very powerful tool in the analysis of skipjack thawing. The mathematical model will aid in improving the thawing process, which may ultimately improve yield and product quality. The model showed that small changes in processing conditions, such as rate of convective heat transfer, have a significant impact on thawing rate and process efficacy.
Session 15D, Food Engineering: Processing Technologies
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