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Optimization of fed-batch culture by dynamic programming and regression analysis

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Summary

An algorithm for the optimization of a fermentation process was studied using the combination of dynamic programming and linear predictive procedure by regression analysis. It was applied to the fed-batch culture for glutamic acid production with ethanol feeding, the results of which proved that it was effective for the optimization problems.

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Abbreviations

a i , b i , c i , d i ;i = 1 2 or 3::

Partial regression coefficients derived by multiple regression analysis ( - )

E ::

Euclid distance ( - )

F ::

Volumetric feed rate (l/hr)

f ::

Defined by Eq. (13) (g-glutamic acid)

G ::

Concentration of glutamic acid (g/l)

G* ::

Aeration rate (l/hr)

J ::

Objective function defined by Eq. (12) (g-glutamic acid)

N ::

Number of stage ( - )

P ::

Defined by Eq. (14) (g-glutamic acid)

Q ::

Metabolic activity of the culture, in this case Q = Q CO 2 (mole CO2/g-cell hr)

S ::

Ethanol concentration in culture broth (g/l)

S Q ::

Ethanol concentration in feed (g/l)

S* ::

Ethanol concentration in effluent gas (g/l)

t ::

Culture time (hr)

t o ::

Initial culture time (hr)

V ::

Volume of culture broth (l)

X ::

Cell concentration (g/l)

X ::

State vector (X, S, Q, V)

κ ::

Rate of Q CO 2 change (mole CO2/g-cell·h2)

μ ::

Specific growth rate of microorganisms (hr−1)

ϱ ::

Specific production rate of glutamic acid (g-glutamic acid/g-cell·hr)

ν ::

Specific consumption rate of ethanol (g-ethanol/g-cell·hr)

σ ::

Standard deviation ( - )

References

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  • Nemhauser, G. L. (1966). “Introduction to Dynamic Programming” John Willey & Sons, Inc.

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  • Yamane, T., Kume, T., Sada, E. and Takamatsu, T. (1977). J. Ferment. Teohnol., 55, 587–598.

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Additional information

This optimization procedure was presented in preliminary form at the 45th Annual Meeting of the Soc. of Chem. Engrs., Japan, Osaka, C105 (1980).

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Kishimoto, M., Yoshida, T. & Taguchi, H. Optimization of fed-batch culture by dynamic programming and regression analysis. Biotechnol Lett 2, 403–408 (1980). https://doi.org/10.1007/BF00144245

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