Adaptive Control of Continuous Yeast Fermentation, Near Critical Dilution Rate

The steady-state behavior of a glucose-limited, aerobic, continuous cultivation of Saccharomyces cerevisiae CEN.PK113-7D was investigated around the critical dilution rate. Oxido-reductive steady states were obtained at dilution rates up to 0.09 h(-1) lower than the critical dilution rate by operating the bioreactor as a productostat, where the dilution rate was controlled on the basis of an ethanol measurement. Thus, the experimental investigations revealed that multiple steady states exist in a region of dilution rates below the critical dilution rate. The existence of multiple steady states was attributed to two distinct physiological effects occurring when growth changed from oxidative to oxido-reductive: (i) a decrease in the efficiency of ATP production and utilization (at ethanol concentrations below 3 g/L) and (ii) repression of the oxidative metabolism (at higher ethanol concentrations). The first effect was best observed at low ethanol concentrations, where multiple steady states were observed even when no repression of the oxidative metabolism was evident, i.e., the oxidative capacity was constant. However, at higher ethanol concentrations repression of the oxidative metabolism was observed (the oxidative capacity decreased), and this resulted in a broader range of dilution rates where multiple steady states could be found.

Section: Steady-state Datasupporting

confidence: 91%

Section: Introductionmentioning

confidence: 95%

Experimental investigations of multiple steady states in aerobic continuous cultivations of Saccharomyces cerevisiae

Lei

Olsson

Jørgensen

2003

“…Hence, multiple quasi-steady states can be obtained over a range of dilution rates from 0.27 -0.31 h À1 . This result is similar to what was found in a productostat by Jørgensen et al (1992) on a different S. cerevisiae strain.…”

Section: Steady-state Multiplicitysupporting

confidence: 91%

Dynamic effects related to steady‐state multiplicity in continuous Saccharomyces cerevisiae cultivations

Lei

Olsson

Jørgensen

2004

The behavioral differences between chemostat and productostat cultivation of aerobic glucose-limited Saccharomyces cerevisiae were investigated. Three types of experiments were conducted: a chemostat, where the dilution rate was shifted up or down in stepwise manner; and a productostat, with either stepwise changed or a rampwise increased ethanol setpoint, i.e., an accelero-productostat. The transient responses from chemostat and productostat experiments were interpreted using a simple metabolic flux model. In a productostat it was possible to obtain oxido-reductive steady states at dilution rates far below Dcrit due to a strong repression of the respiratory system. However, these steady states could not be obtained in a chemostat, since a dilution rate shift-down from an oxido-reductive steady state led to a derepression of the respiratory system. It can therefore be concluded that the range of dilution rates where steady-state multiplicity can be obtained differs depending on the operation mode and that this dilution rate multiplicity range may appear larger in a productostat than in a chemostat. A more narrow multiplicity range, however, was obtained when the productostat was operated as an accelero-productostat.

“…Facts were I/O connections and relationships of cascaded loops (e.g., lower airflow causes low DO); rules were production rules (e.g., if-then, fault, etc.). Concise way to store and access troubleshooting manual Miles 1988Schlager (1988 Expert system supervision along with aeration-agitation control for 20% reduced energy costs Streptomyces amylofaciens production of spiramycin Zhejiang University/Hangzhou 1989 Qi et al (1989) Rule based system with computer system processing linguistically formulated simple rules that simulates user observation of state of the process E. coli production of enzyme Universität Hannover 1989 Lübbert et al (1989) Combined supervisory knowledge base (i.e., G2 system), scheduling knowledge base, and online relational database 1992Jørgensen et al (1992 Fuzzy control to regulate sugar feed rate; feed control strategy altered for each of five cultivation phases Hosobuchi et al (1993b On-line estimates for biomass and protein using dynamically modified, feed-forward ANN; expert supervisory system developed for penicillin G transferred to clavulanic acid production, a similar but less well understood process Recombinant E. coli production of protein ZENECA/University of Newcastle Glassey et al (1994 Neural network that predicted optical density at subsequent sampling time based on inputted measured optical density at prior sampling times Zhang et al (1994 Hybrid model combined dynamic differential equations, ANN, and a fuzzy expert system…”

Section: Recombinant Bacillus Subtilismentioning

confidence: 99%

“…Facts were I/O connections and relationships of cascaded loops (e.g., lower airflow causes low DO); rules were production rules (e.g., if-then, fault, etc.). Concise way to store and access troubleshooting manual 1992Jørgensen et al (1992 Fuzzy control to regulate sugar feed rate; feed control strategy altered for each of five cultivation phases…”

Section: Recombinant Bacillus Subtilismentioning

confidence: 99%

Bioprocess monitoring and computer control: Key roots of the current PAT initiative

Junker

Wang

2006

113

This review article has been written for the journal, Biotechnology and Bioengineering, to commemorate the 70th birthday of Daniel I.C. Wang, who served as doctoral thesis advisor to each of the co-authors, but a decade apart. Key roots of the current PAT initiative in bioprocess monitoring and control are described, focusing on the impact of Danny Wang's research as a professor at MIT. The history of computer control and monitoring in biochemical processing has been used to identify the areas that have already benefited and those that are most likely to benefit in the future from PAT applications. Past applications have included the use of indirect estimation methods for cell density, expansion of on-line/at-line and on-line/in situ measurement techniques, and development of models and expert systems for control and optimization. Future applications are likely to encompass additional novel measurement technologies, measurements for multi-scale and disposable bioreactors, real time batch release, and more efficient data utilization to achieve process validation and continuous improvement goals. Dan Wang's substantial contributions in this arena have been one key factor in steering the PAT initiative towards realistic and attainable industrial applications.