Background: Predictive microbiology is a tool that allows us to evaluate the behavior of the concentration of biomass and estimated cells under extrinsic conditions, providing scientific and industrial benefits. In the present study, the growth of L. lactis and L. casei combined with inulin and fructose was modeled using the Gompertz sigmoidal growth functions and plotted using data obtained from batch culture in relation to biomass and cell concentration expressed as estimates in ln N (OD and cells mL ) as a function of time.
Results: The results of the kinetic modeling indicated that (T1) A1B1 = L. lactis + fructose and (T4) A2B2 = L. casei + inulin presented the best function coefficients and best fits in most cases compared to the rest. The specific growth rate of the maximum acceleration was from 0.364 to 0.473 h and 0.100 to 0.129 h , the concentration of bacterial cells (A) was from 0.556 to 0.713 and 0.425 to 0.548 respectively and the time where (μ) occurred with a greater magnitude (L) fluctuated between 0.854 and 0.802 and when this time in (L) is very fast, it presents values of ≤0.072 to ≤0.092. Its coefficient of determination and/or multiple regression (R ) obtained in the two adjustments was 0.97.
Conclusion: It was possible to predict the influence of the carbon source on the behavior of maximum growth rates, higher consumption due to nutrient affinity and shorter growth time. © 2023 Society of Chemical Industry.
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http://dx.doi.org/10.1002/jsfa.13032 | DOI Listing |
Int J Mol Sci
November 2024
Institute of Chemical Engineering, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria.
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Appl Microbiol Biotechnol
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Faculty of Agriculture, Kagoshima University, 1-21-24 Korimoto, Kagoshima, Kagoshima, 890-0065, Japan.
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Int J Biol Macromol
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State Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510006, China; Guangdong Provincial Key Laboratory of Clinical Research on Traditional Chinese Medicine Syndrome, Neihuan Xilu, Guangzhou Higher Education Mega Center, Guangzhou 510006, China. Electronic address:
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