Browse > Article
http://dx.doi.org/10.5851/kosfa.2009.29.3.349

Mathematical Simulation of the Temperature Dependence of Time Temperature Integrator (TTI) and Meat Qualities  

Park, Han-Jo (Department of Food Science and Technology, Dongguk University)
Shim, Soo-Dong (Department of Food Science and Technology, Dongguk University)
Min, Sang-Gi (Department of Food Science and Biotechnology of Animal Resources, Konguk University)
Lee, Seung-Ju (Department of Food Science and Technology, Dongguk University)
Publication Information
Food Science of Animal Resources / v.29, no.3, 2009 , pp. 349-355 More about this Journal
Abstract
The temperature dependence of time temperature integrator (TTI) was investigated in terms of the Arrhenius activation energy (Ea) to determine TTI requirements to accurately predict meat quality during storage. Mathematical simulation was conducted using a numerical analysis. First, using Euler's method and MS Excel VBA, the TTI color change was kinetically modeled and numerically calculated under several storage conditions. From the TTI color variable profiles calculated from the storage time-temperature profiles, $T_{eff}$, which is a constant temperature representing the whole temperature profiles, was calculated. Upon predicting Pseudomonas spp. concentrations (one of the meat qualities) from $T_{eff}$, it was found that if $Ea_{microbial\;spoilage}=Ea_{TTI}$ be true, then Pseudomonas concentrations were calculated to be constant with the same TTI color values, regardless of time-temperature profiles, whereas if $Ea_{microbial\;spoilage}{\neq}Ea_{TTI}$ then Pseudomonas concentrations varied even with the same TTI color values. This indicates that each TTI color value represents its own fixed degree of meat quality, only if $Ea_{meat\;qualities}=Ea_{TTI}$.
Keywords
time temperature integrator; temperature dependence; activation energy; mathematical simulation;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
Times Cited By Web Of Science : 0  (Related Records In Web of Science)
Times Cited By SCOPUS : 1
연도 인용수 순위
1 Giannakourou, M. C., Koutsoumanis K., Nychas, G. J. E., and Taoukis, P. S. (2005) Field evaluation of the application of time temperature integrators for monitoring fish quality in the chill chain. Int. J. Food Microbiol. 102, 323-336   DOI   ScienceOn
2 Jung, H. M., Kim, G. S., Kim, M. S., Lee, Y. H., and Choi, D. S. (2008) Quality change of the pears using processed packaging materials by charcoal during storage and distribution. Korean J. Soc. Agr. Mach. 13, 272-278
3 Lee, J. M. and Lee, S. J. (2008) Kinetic modelling for predicting the qualities of beef and color of enzyme time-temperature integrator during storage. Food Eng. Prog. 12, 241-246
4 Lee, Y. S., Ji, H. H., Park, K. H., Lee, S. Y., Choi, Y. J., Lee, D. H., Park, S. H., Moon, E. S., Ryu, K., Shin, H. S., and Ha, S. D. (2008) Survey on storage temperature of domestic major chilled foods in refrigerator. J. Food Hyg. Safety 23, 304-308   과학기술학회마을
5 Yoon, S. H., Lee, C. H., Kim, D. Y., Kim, J. W., and Park, K. H. (1994) Time-temperature indicator using phospholipidsphospholipase system and application to storage of frozen pork. J. Food Sci. 20, 490-493
6 Emmanuel, P. and Viviana, O. S. (2009) Bread baking as a moving boundary problem. Part 2: Model validation and numerical simulation. J. Food Eng. 91, 434-442   DOI   ScienceOn
7 VITSAB. 2008. Home page.
8 Macdonald, C. B., Gottlieb, S., and Ruuth, S. J. (2008) A numerical study of diagonally split Runge-Kutta methods for PDEs with discontinuities. J. Sci Comput. 35, 89-112
9 Mendoza, T. F., Welt, B. A., Otwell, S., Teixeira, A. A., Kristonsson, H., and Balaban, M. M. (2004) Kinetic parameter estimation of time-temperature integrators intended for use with packaged fresh seafood. J. Food Sci. 69, 90-96   DOI   ScienceOn
10 Taoukis, P. S. and Labuza, T. P. (1989) Applicability of timetemperature indicators as shelf life monitors of food products. J. Food Sci. 54, 783-788   DOI
11 Bin, F. U., Taoukis, P. S., and Labuza, T. P.(1991) Predictive microbiology for monitoring spoilage of daily products with time-temperature integrators. J. Food Sci. 56, 1209-1215   DOI
12 Bobelyn, E., Hertog, M., and Nicolaï, B. M. (2006) Applicability of an enzymatic time temperature integrator as a quality indicator for mushrooms in the distribution chain. Postharvest Biol. Tec. 42, 104-114   DOI   ScienceOn
13 Hathaway, S. (1999) Management of food safety in international trade. Food Control 10, 247-254   DOI   ScienceOn
14 James, M. L., Smith, G. M., and Wolfond, J. C. (1977) Applied numerical methods for digital computation with FORTRAN and CSMP, Second Edition. Harper & Row, Publishers, Inc., Lodon, pp. 368-379
15 Rhee, S. Y., Cheon, D. W., and Park, J. W. (1996) An economic study on Korean native cattle marketing and stage price formation. Korean Agr. Policy Rev. 23, 109-121
16 Park, S.Y., Kim, Y. G., Kim, J. W., Lee, S. G., Lim, H. J., Joo, S. T., and Choi, Y. I. (2000) Dairy processing. Yu Han Publisher, Co, Seoul, pp. 69-80
17 Giannakourou, M. C. and Taoukis, P. S. (2002) Systematic application of time temperature integrators as tools for control of frozen vegetable quality. J. Food Sci. 67, 2221-2228   DOI   ScienceOn
18 Claeys, W.L., Vanloey, A. M., and Hendrickx, M. E. (2002) Intrinsic time temperature integrators for heat treatment of milk. Trends Food Sci. Tech. 13, 293-311   DOI   ScienceOn
19 Taoukis, P. S., Koutsoumanis, K., and Nychas, G. J. E. (1999) Use of time-temperature integrators and predictive modeling for shelf life control of chilled fish under dynamic storage conditions. Int. J. Food Microbiol. 53, 21-31   DOI   ScienceOn
20 Geankoplis, C. J. (1983) Transport processes and unit operations, Second Edition. Allyn and Bacon, Inc., Lodon, pp. 29-33
21 Taoukis, P. S. (2001) Modeling the use of time-temperature indicators in distribution and stock rotation. In: Food process modelling, 3rd ed. Tijskens, L. M. M., Hertog, M. L. A. T. M., and Nicoliai, B. M. (eds), CRC Press, Washington DC, pp. 402-432