Experimental study and identification of kinetic parameters of the process of bacterial inactivation in the presence of iodine vapor
The article presents results of an experimental study of the inactivation process of the model bacterial strain L. casei ATCC 393 in the presence of iodine vapor at temperatures of T = 27, 37, 40 and 42°C.; kinetic curves of survival under the influence of iodine vapor at the given temperatures have been obtained. The results of the experimental study demonstrate the high efficiency of iodine vapor against the model bacterial strain. A nonlinear Weibull model is proposed to describe the inactivation process of the model bacterial strain L. casei ATCC 393 under the influence of iodine vapor at different temperatures (T = 27, 37, 40, and 42°C). The problem of identifying the model parameters is set as an optimization problem in order to minimize the spread of one of the determined parameters. The identification process includes a sequential solution of the inverse and direct kinetic problems and subsequent comparison of the calculated values with the experimental data, which confirms the adequacy of the model. Microsoft Excel software is used for the kinetic analysis and evaluation of the model parameters. The criterion for selecting the optimal parameters of the mathematical model of the process is the minimum value of the statistical functional in the form of the variation coefficient and the maximum value of the nonlinear determination coefficient R2. High values of the determination coefficient R4 from 0.94 to 0.99 confirm the adequacy of the model. It is shown that the Weibull model is suitable for the qualitative and quantitative analysis of the inactivation process of the model bacterial strain L. casei ATCC 393 under the influence of iodine vapor at different temperatures T = 27, 37, 40, and 42°C).
Keywords
biokinetics,
mathematical model,
kinetic parameters,
Weibull model,
determination coefficient R2Authors
| Vorozhtsov Alexander B. | Tomsk State University | abv1953@mail.ru |
| Bondarchuk Ivan S. | Tomsk State University | ivanich_91@mail.ru |
| Prokopchuk Anna O. | Tomsk State University | bio_1979@mail.ru |
| Marchenko Ekaterina S. | Tomsk State University | 89138641814@mail.ru |
| Sokolov Sergey D. | Tomsk State University | sokolovsd95@yandex.ru |
Всего: 5
References
Pёrez-Rodriguez F. Development and application of predictive microbiology models in foods // Mathematical and Statistical Methods in Food Science and Technology / D. Granato, G. Ares (eds.). New York: John Wiley & Sons, 2014. P. 321-362.
Akkermans S., Smet C., Valdramidis V., Van Impe J. Microbial Inactivation Models for Ther mal Processes // Food Safety Engineering / A. Demirci, H. Feng, K. Krishnamurthy (eds.). New York: Springer, 2020. P 399-420. (Food Engineering Series).
da Silva A.K., Perim M.D., Brito L.M., Alvarenga V.O. Basic Concepts for Predictive Micro biology // Basic Protocols in Predictive Food Microbiology. Methods and Protocols in Food Science / V.O. Alvarenga (ed.). New York: Humana, 2023, P. 1-31.
Van Boekel M.A.J.S. Kinetic Modeling of Food Quality: A Critical Review // Comprehensive Reviews in Food Science and Food Safety. 2008. V. 7, № 1. P. 144-158.
Huang L. Dynamic identification of growth and survival kinetic parameters of microorga nisms in foods // Current Opinion in Food Science. 2017. V. 14. P. 85-92.
Psomas A.N., Nychas G.J., Haroutounian S.A., Skandamis P.N. Development and validation of a tertiary simulation model for predicting the growth of the food microorganisms under dynamic and static temperature conditions // Computers and Electronics in Agriculture. 2011. V. 76, № 1. P. 119-129.
Dolan K.D., Mishra D.K. Parameter estimation in food science // Annual Review of Food Science and Technology. 2013. V. 4. P. 401-422.
Clermont G., Zenker S. The inverse problem in mathematical biology // Mathematical Bio sciences. 2015. V. 260. P. 11-15.
Penalver-Soto J.L., Garre A., Esnoz A., Fernandez P.S., Egea J.A. Guidelines for the design of (optimal) isothermal inactivation experiments // Food Research International. 2019. V. 126. Art. 108714.
Reverberi A.P., Meshalkin V.P., Butusov O.B., Chistyakova T.B., Ferretti M., Cardinale A.M., Fabiano B. Organic and Inorganic Biocidal Energetic Materials for Agent Defeat Weapons: An Overview and Research Perspectives // Energies. 2023. V. 16, № 2. Art. 675.
Bevilacqua A., Speranza B., Sinigaglia M., Corbo M.R. A Focus on the Death Kinetics in Predictive Microbiology: Benefits and Limits of the Most Important Models and Some Tools Dealing with Their Application in Foods // Foods. 2015. V. 4, № 4. P. 565-580.
Corradini M.G., Peleg M. A model of microbial survival curves in water treated with a volatile disinfectant // Journal of Applied Microbiology. 2003. V. 95, № 6. P. 1268-1276.
Peleg M. Modeling the dynamic kinetics of microbial disinfection with dissipating chemical agents - a theoretical investigation // Applied Microbiology and Biotechnology. 2021. V. 105, № 2. P. 539-549.
Brown W.K., Wohletz K.H. Derivation of the Weibull distribution based on physical connection to the Rosin-Rammler and lognormal distributions // Journal of Applied Physics. 1995. V. 78, № 4. P. 2758-2763.
peleg m. advanced quantitative microbiology for foods and biosystems: models for predicting growth and inactivation. Boca Raton, FL: CRC Press, 2006.
Aragao G.M.F., Corradini M.G., Normand M.D., Peleg M. Evaluation of the Weibull and log-normal distribution functions as survival models of Escherichia coli under isothermal and non-isothermal conditions // International Journal of Food Microbiology. 2007. V. 19, № 3. P. 243-257.
Van Boekel M.A.J.S. On the use of the Weibull model to describe thermal inactivation of microbial vegetative cells // International Journal of Food Microbiology. 2002. V. 74, № 1-2. P. 139-159.
Pearce J.A.Comparative Analysis of Mathematical Models of Cell Death and Thermal Damage Processes // International Journal of Hyperthermia. 2013. V. 29, № 4. P. 262-280.
Bondarchuk I., Perevozkin V., Bondarchuk S., Vorozhtsov A. Identification of the Kinetic Parameters of Thermal Micro-Organisms Inactivation // Applied Sciences. 2022. V. 12, № 22. Art. 11505.
Бондарчук И.С., Бондарчук С.С. Кинетика гомогенных химических реакций: методы решения в Excel. Томск: Изд-во Том. гос. пед. ун-та, 2018. 263 с.
Mahmoud B.S.M., Bhagat A.R., Linton R.H. Inactivation kinetics of inoculated Escherichia coli O157:H7, Listeria monocytogenes and Salmonella enterica on strawberries by chlorine dioxide gas // Food Microbiology. 2007. V. 24, № 7-8. P. 736-744.
Mahmoud B.S.M., Linton R.H. Inactivation kinetics of inoculated Escherichia coli O157:H7 and Salmonella enterica on lettuce by chlorine dioxide gas // Food Microbiology. 2008. V. 25, № 2. P. 244-252.
