On-line evolutionary optimization of an industrial fed-batch yeast fermentation process

Yüzgeç, Uğur; Türker, Mustafa; Hocalar, Akif

doi:10.1016/j.isatra.2008.09.001

Cited by 47 publications

(19 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…An empirical mass transfer coefficient equation for gas-liquid interface for air bubble column reactors (Karakuzu et al, 2006;Yuzgec et al, 2009) was used to get the aeration rate. Consequently, substrate and air feed rates were found for each time interval as shown in Figures 2 and 3.…”

Section: Resultsmentioning

confidence: 99%

“…The following algebraic equations describing kinetics and balance equations form the dynamic model (Yuzgec et al, 2009): Glucose uptake rate:…”

Section: Dynamic Modelmentioning

confidence: 99%

“…The volumetric oxygen transfer coefficient as a function of superficial gas velocity in bubble column bioreactors is given in the following equation (Karakuzu et al, 2006;Yuzgec et al, 2009 Initial conditions for simulations are given in Table 1, and values of some model parameters are listed in Table 2 as reported by Yuzgec et al (2009). For the remaining model parameters, nominal values obtained from the literature were employed as given in Table 3.…”

Section: Dynamic Modelmentioning

confidence: 99%

“…Model parameters for fed-batch reactor (Yuzgec et al, 2009) Parameter Value Table 3. Model parameters taken from literature (Besli et.…”

Section: State Variablesmentioning

confidence: 99%

See 3 more Smart Citations

Optimisation of Operating Conditions in Fed-Batch Baker’s Yeast Fermentation

Atasoy¹,

Yüceer²,

Berber³

2013

Chemical and Process Engineering

View full text Add to dashboard Cite

TurkeySaccharamyces cerevisia known as baker's yeast is a product used in various food industries. Worldwide economic competition makes it a necessity that industrial processes be operated in optimum conditions, thus maximisation of biomass in production of saccharamyces cerevisia in fedbatch reactors has gained importance. The facts that the dynamic fermentation model must be considered as a constraint in the optimisation problem, and dynamics involved are complicated, make optimisation of fed-batch processes more difficult.In this work, the amount of biomass in the production of baker's yeast in fed-batch fermenters was intended to be maximised while minimising unwanted alcohol formation, by regulating substrate and air feed rates. This multiobjective problem has been tackled earlier only from the point of view of finding optimum substrate rate, but no account of air feed rate profiles has been provided. Control vector parameterisation approach was applied the original dynamic optimisation problem which was converted into a NLP problem. Then SQP was used for solving the dynamic optimisation problem. The results demonstrate that optimum substrate and air feeding profiles can be obtained by the proposed optimisation algorithm to achieve the two conflicting goals of maximising biomass and minimising alcohol formation.

show abstract

Section: Resultsmentioning

confidence: 99%

“…The following algebraic equations describing kinetics and balance equations form the dynamic model (Yuzgec et al, 2009): Glucose uptake rate:…”

Section: Dynamic Modelmentioning

confidence: 99%

Section: Dynamic Modelmentioning

confidence: 99%

“…Model parameters for fed-batch reactor (Yuzgec et al, 2009) Parameter Value Table 3. Model parameters taken from literature (Besli et.…”

Section: State Variablesmentioning

confidence: 99%

See 2 more Smart Citations

Optimisation of Operating Conditions in Fed-Batch Baker’s Yeast Fermentation

Atasoy¹,

Yüceer²,

Berber³

2013

Chemical and Process Engineering

View full text Add to dashboard Cite

show abstract

“…A predetermined feed rate, obtained off-line by the use of genetic algorithms, has been successfully applied at industrial scale to maximize biomass production while keeping to a minimum the formation of overflow metabolites by Yuezgec et al (2009). As for feedback control, Smets et al (2004) stated that "the primary goal of a substrate feedback controller for a fed-batch fermentation process is not to stabilize the process globally, but rather to optimize it while keeping an inherently unstable type of behavior under control."…”

Section: Controlling the Specific Growth Rate In Bioprocessesmentioning

confidence: 99%

Real-time monitoring and control of microbial bioprocesses with focus on the specific growth rate: current state and perspectives

Schuler

Marison

2012

Appl Microbiol Biotechnol

View full text Add to dashboard Cite

Understanding the growth characteristics of microorganisms is an essential step in bioprocessing, not only because product formation may be growth-associated but also because they might influence cell physiology and thereby product quality. The specific growth rate, a key variable of many bioprocesses, cannot be measured directly and relies on the estimation through other measurable variables such as biomass, substrate, or product concentrations. Techniques for real-time estimation of the specific growth rate in microbial fed-batch cultures are discussed in the present paper. The advantages and limitations of different models and various monitoring techniques are discussed, highlighting the importance of the specific growth rate in the development of fast, reliable, and robust processes for the production of high-value products such as recombinant proteins.

show abstract

Fermentation Process Control and Optimization

et al. 2022

View full text Add to dashboard Cite

Process control and optimization is important in ensuring a process in sustaining profitable income while maintaining the required quality. The fermentation process has attracted attention from food processing, pharmaceutical energy, and waste treatment industries due to its lower impact on the environment and lower operating cost than the conventional chemical process. However, its control and monitoring are relatively complex as living cell activity is not easily comprehended and highly nonlinear. Various control techniques applied in the fermentation process are reviewed, including a summary of the control objective, manipulated and controlled variables chosen, and their strengths and limitations in determining the optimal fermentation process.

show abstract

On-line evolutionary optimization of an industrial fed-batch yeast fermentation process

Cited by 47 publications

References 31 publications

Optimisation of Operating Conditions in Fed-Batch Baker’s Yeast Fermentation

Optimisation of Operating Conditions in Fed-Batch Baker’s Yeast Fermentation

Real-time monitoring and control of microbial bioprocesses with focus on the specific growth rate: current state and perspectives

Fermentation Process Control and Optimization

Contact Info

Product

Resources

About