Abstract

Citation

Researchers should cite this work as follows:

• Teleken, J. T. (2023). 2011-Teleken-EtAl-Mathematical modeling of microbial growth in milk. SIMIODE, QUBES Educational Resources. doi:10.25334/ZWFT-1F20

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Article Context

Description

Teleken, Jhony Tiago, Weber da Silva Robazzam,  and  Gilmar de Almeida Gomes. 2011.  Mathematical modeling of microbial growth in milk. Ciênc. Tecnol. Aliment., Campinas. 31(4): 891-896.

The pdf of the article may be downloaded freely from  http://www.scielo.br/pdf/cta/v31n4/10.pdf . Accessed 29 March 2023.

Abstract A mathematical model to predict microbial growth in milk was developed and analyzed. The model consists of a system of two differential equations of first order. The equations are based on physical hypotheses of population growth. The model was applied to five different sets of data of microbial growth in dairy products selected from ComBase, which is the most important database in the area with thousands of datasets from around the world, and the results showed a good fit. In addition, the model provides equations for the evaluation of the maximum specific growth rate and the duration of the lag phase which may provide useful information about microbial growth.

The source of the data used in this modeling paper was ComBase https://www.combase.cc/  “ComBase is an online tool for quantitative food microbiology. Its main pillars are the ComBase database and the ComBase Predictor, which is primarily based on broth-based data in ComBase data. The focus of ComBase is to describe and predict how microorganisms survive and grow under a variety of (primarily food-related) conditions.” ReEgistration is free.

Experimental data of growth of five different microorganisms in dairy products were taken from Combase (www.combase.cc). Datasets used in this study can be obtained using the following Id codes in the database:

• Listeria monocytogenes: Buchanan_91a

The source for this data is Buchanan (et al.), 1991. Effectiveness of Carnobacterium piscicola LK5 for controlling the growth of Listeria monocytogenes Scott A in refrigersted foods. Journal of Food Safety, 12:219-236.

Searching is a bit tricky, but the data sets are available, even with some analysis tools using a few standard models, such as Baranyi and Roberts Model, Trilinear, Linear. Data can be downloaded in CSV format. Below is an example of this data set.

Other data sets from the same source referenced include:

• Pseudomonas: AFSCE

• Yersinia enterocolitica: FSA-CCFRA

• Shigella flexneri: Zaika_98

• Bacillus cereus: STU-BA

Keywords: predictive microbiology, dairy products, food safety, system, nonlinear, differential equation, model, parameter estimation, milk, bacteria