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| Main Authors: | , , , , , |
|---|---|
| Format: | Dataset Open Access |
| Language: | en |
| Published: |
PANGAEA
2025
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| Subjects: | |
| Online Access: | https://doi.org/10.1594/PANGAEA.974730 |
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Table of Contents:
- The growth rate was calculated by finding the best fit to the classic logistic growth model with the MATLAB curve fitting toolbox: N_t=K/(1+(e^(-r(-b+t) ))), where "N_t" is the cell concentration at time "t", K is the total cell yield, "r" is the exponential growth rate coefficient, and "b" the time of inflection of the curve (Garnier & Quetelet, 1838). However, when the classic logistic growth model did not fit the data because the asymptote was reached within one or two time intervals or was never reached, the following model was used to calculate the growth rate: N_t = N_0 e^rt, where "N_t " is the cell concentration at time "t", "N_0" was the initial cell concentration, and "r" is the growth rate coefficient (Andersen, 2005).