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A neo-logistic model for the growth of bacteria

Author

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  • Tashiro, Tohru
  • Yoshimura, Fujiko

Abstract

We propose a neo-logistic model that can describe bacterial growth data precisely. This model is not derived by modifying the logistic model formally, but by incorporating the synthesis of inducible enzymes into the logistic model indirectly. Therefore, the meaning of the parameters of the neo-logistic model becomes physically clear. The neo-logistic model can approximate bacterial growth much more accurately than previous models, and can accurately predict the order of the saturated number of bacteria in the stationary phase from the initial growth data.

Suggested Citation

  • Tashiro, Tohru & Yoshimura, Fujiko, 2019. "A neo-logistic model for the growth of bacteria," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 199-215.
    • Handle: RePEc:eee:phsmap:v:525:y:2019:i:c:p:199-215
    DOI: 10.1016/j.physa.2019.03.049
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