Skip to main content

Optimization and scale up of industrial fermentation processes

Applied Microbiology and Biotechnology volume 68, pages 425–435 (2005)Cite this article

An Erratum to this article was published on 01 October 2005

This article has been updated

Abstract

To increase product yields and to ensure consistent product quality, key issues of industrial fermentations, process optimization and scale up are aimed at maintaining optimum and homogenous reaction conditions minimizing microbial stress exposure and enhancing metabolic accuracy. For each individual product, process and facility, suitable strategies have to be elaborated by a comprehensive and detailed process characterization, identification of the most relevant process parameters influencing product yield and quality and their establishment as scale-up parameters to be kept constant as far as possible. Physical variables, which can only be restrictedly kept constant as single parameters, may be combined with other pertinent parameters to appropriate mathematical groups or dimensionless terms. Process characterization is preferably based on real-time or near real-time data collected by in situ and on-line measurements and may be facilitated by supportive approaches and tools like neural network based chemometric data analysis and modelling, clarification of the mixing and stream conditions through computational fluid dynamics and scale-down simulations. However, as fermentation facilities usually are not strictly designed according to scale-up criteria and the process conditions in the culture vessels thus may differ significantly and since any strategy and model can only insufficiently consider and reflect the highly complex interdependence and mutual interaction of fermentation parameters, successful scale up in most cases is not the result of a conclusive and straight-lined experimental strategy, but rather will be the outcome of a separate process development and optimization on each scale. This article gives an overview on the problems typically coming along with fermentation process optimization and scale up, and presents currently applied scale-up strategies while considering future technologies, with emphasis on Escherichia coli as one of the most commonly fermented organisms.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Fig. 1

Change history

  • 01 October 2005

    As not all proof corrections were carried out, Table 1 contained errors. The correct version appears below.

References

  • Alves SS, Vasconcelos JMT (1996) Optimisation of agitation and aeration in fermenters. Bioprocess Biosyst Eng 14:119–123

    CAS  Google Scholar 

  • Apostol I, Levine J, Lippincott J, Leach J, Hess E, Glascock CB, Weickert MJ, Blackmore R (1997) Incorporation of norvaline at leucine positions in recombinant human hemoglobin expressed in Escherichia coli. J Biol Chem 272:28980–28988

    Article  PubMed  CAS  Google Scholar 

  • Amanullah A, McFarlane CM, Emery AM, Nienow AW (2001) Scale-down model to simulate spatial pH variations in large-scale bioreactors. Biotechnol Bioeng 73:390–399

    Article  PubMed  CAS  Google Scholar 

  • Anderson RKI, Jayaraman K, Voisard D, Marison IW, von Stockar U (2002) Heat flux as an on-line indicator of metabolic activity in pilot scale bioreactor during the production of Bacillus thuringiensis var. galleriae-based pesticides. Thermochim Acta 386:127–138

    Article  CAS  Google Scholar 

  • Ansorge MB, Kula MR (2000) Production of recombinant l-leucine dehydrogenase from Bacillus cereus in pilot scale using the runaway replication system E. coli (pIET98). Biotechnol Bioeng 68:557–562

    Article  PubMed  CAS  Google Scholar 

  • Arndt M, Hitzmann B (2004) Kalman filter based glucose control at small set points during fed-batch cultivation of Saccharomyces cerevisiae. Biotechnol Prog 1:377–383

    Article  CAS  Google Scholar 

  • Berkholz R, Guthke R (2001) Model based sequential experimental design for bioprocess optimisation—an overview. Focus Biotechnol 4:129–141

    CAS  Article  Google Scholar 

  • Berkholz R, Rohlig D, Guthke R (2000) Data and knowledge based experimental design for fermentation process optimization. Enzyme Microb Technol 27:784–788

    Article  PubMed  CAS  Google Scholar 

  • Bezzo F, Macchietto S, Pantelides CC (2003) General hybrid multizonal/CFD approach for bioreactor modeling. AIChE J 49:2133–2148

    Article  CAS  Google Scholar 

  • Boehl D, Solle D, Hitzmann B, Scheper T (2003) Chemometric modelling with two-dimensional fluorescence data for Claviceps purpurea bioprocess characterization. J Biotechnol 105:179–188

    Article  PubMed  CAS  Google Scholar 

  • Buchholz A, Takors R, Wandrey C (2001) Quantification of intracellular metabolites in Escherichia coli K12 using liquid chromatographic electrospray ionization tandem mass spectrometric techniques. Anal Biochem 295:129–137

    Article  PubMed  CAS  Google Scholar 

  • Bylund F, Collet E, Enfors EO, Larsson G (1998) Substrate gradient formation in the large scale lowers cell yield and increases byproduct formation. Bioprocess Eng 18:171–180

    Article  CAS  Google Scholar 

  • Bylund F, Guillard F, Enfors SO, Trägardh C, Larsson G (1999) Scale down of recombinant production: a comparative study of scaling performance. Bioprocess Eng 20:289–377

    Article  Google Scholar 

  • Bylund F, Castan A, Mikkola R, Veide A, Larsson G (2000) Influence of scale-up on the quality of recombinant human growth hormone. Biotechnol Bioeng 69:119–128

    Article  PubMed  CAS  Google Scholar 

  • Cant S (2002) High-performance computing in computational fluid dynamics: progress and challenges. Philos Trans Math Phys Eng Sci 360:1211–1225

    Article  CAS  Google Scholar 

  • Castan A, Enfors SO (2001) Formate accumulation due to DNA release in aerobic cultivations of Escherichia coli. Biotechnol Bioeng 77:324–328

    Article  CAS  Google Scholar 

  • Chen VCP, Rollins DK (2000) Issues regarding artificial neural network modeling for reactors and fermenters. Bioprocess Biosyst Eng 22:85–93

    CAS  Google Scholar 

  • Cimander C, Bachinger T, Mandenius CF (2003) Integration of distributed multi-analyzer monitoring and control in bioprocessing based on a real-time expert system. J Biotechnol 103:237–248

    Article  PubMed  CAS  Google Scholar 

  • Collins GE, Wu P, Lu Q, Ramsey JD, Bromund RH (2004) Compact, high voltage power supply for the lab-on-chip. Lab Chip 4:408–411

    Article  PubMed  CAS  Google Scholar 

  • Dantigny P, Ninow JL, Lakrori M (1991) A new control strategy for yeast production based on the L/A approach. Appl Microbiol Biotechnol 36:352–357

    Article  CAS  Google Scholar 

  • Davidson KM, Sushil S, Eggleton CD, Marten MR (2003) Using computational fluid dynamics software to estimate circulation time distributions in bioreactors. Biotechnol Progress 19:1480–1486

    Article  CAS  Google Scholar 

  • Diaz A, Acevedo F (1999) Scale-up strategy for bioreactors with Newtonian and non-Newtonian broths. Bioprocess Eng 21:21–23

    Article  CAS  Google Scholar 

  • Dickinson TA, White J, Kauer JS, Walt DR (1998) Current trends in artificial nose technology. TIBTECH 16:250–258

    CAS  Google Scholar 

  • Enfors SO, Jahic M, Rozkov A, Xu B, Hecker M, Jürgen B, Krüger B, Schweder T, Hamer G, O'Beirne D, Noisommit-Rizzi N, Reuss M, Boone L, Hewitt C, McFarlane C, Nienow A, Kovacs T, Trägardh C, Fuchs L, Revstedt J, Friberg PC, Hjertager B, Blomsten G, Skogman H, Hjort S, Hoeks F, Lin HJ, Neubauer P, van der Lans R, Luyben K, Vrabel P, Manelius A (2001) Physiological responses to mixing in large scale bioreactors. J Biotechnol 85:175–185

    Article  PubMed  CAS  Google Scholar 

  • Farinas J, Chow AW, Wada HG (2001) A microfluidic device for measuring cellular membrane potential. Anal Biochem 295:138–142

    Article  PubMed  CAS  Google Scholar 

  • Fenton D, Lai PH, Lu H, Mann M, Tsai L (1997) Control of norleucine incorporation into recombinant proteins. US patent 5599690

  • Ferreira LS, de Souza MB, Folly ROM (2001) Development of an alcohol fermentation control system based on biosensor measurements interpreted by neural networks. Sens Actuators B Chem 75:166–171

    Article  Google Scholar 

  • Flores ER, Perez F, de la Torre M (1997) Scale-up of Bacillus thuringiensis fermentation based on oxygen transfer. J Ferm Bioeng 83:561–564

    Article  CAS  Google Scholar 

  • Friehs K (2004) Plasmid copy number and plasmid stability. Adv Biochem Eng Biotechnol 86:47–82

    PubMed  CAS  Google Scholar 

  • Gabig-Ciminska M, Holmgren A, Andresen H, Bundvik Barken K, Wumpelmann M, Albers J, Hintsche R, Breitenstein A, Neubauer P, Los M, Czyz A, Wegrzyn G, Silfversparre G, Juregn B, Schweder T, Enfors SO (2004) Electric chips for rapid detection and quantification of nucleic acids. Biosens Bioelectron 15:537–546

    Article  CAS  Google Scholar 

  • Griffths D, Hall G (1993) Biosensors—what real progress is being made. TibTech 11:122–130

    Google Scholar 

  • Hall JW, McNeil B, Rollins MJ, Draper I, Thompson BG, Macaloney G (1996) Near-infrared spectroscopic determination of acetate, ammonium, biomass and glycerol in an industrial Escherichia coli fermentation. Appl Spectrosc 50:102–108

    Article  CAS  Google Scholar 

  • Hammond SV (1992) NIR analysis of antibiotic fermentation. In: Murray I, Cowe IA (eds) Making light work: advances in near infrared spectroscopy, vol 1. VCH, New York, pp 584–589

    Google Scholar 

  • Hammond SV, Brookes IK (1992) Near infrared spectroscopy—a powerful technique for at-line and on-line analysis of fermentations. In: Ladisch MR, Bose A (eds) Harnessing biotechnology for the 21st century: proceedings of the 9th international symposium and exhibition. Am Chem Soc, Washington DC, pp 325–333

  • Harms P, Kostov Y, Rao G (2002) Bioprocess monitoring. Curr Opin Biotechnol 13:124–127

    Article  PubMed  CAS  Google Scholar 

  • Hewitt CJ, Nebe-von Caron G (2001) An industrial application of multiparameter flow cytometry: assessment of cell physiological state and its application to the study of microbial fermentations. Cytometry 44:179–187

    PubMed  Article  CAS  Google Scholar 

  • Hewitt CJ, Nebe-Von Caron G (2004) The application of multi-parameter flow cytometry to monitor individual microbial cell physiological state. Adv Biochem Eng Biotechnol 89:197–223

    PubMed  CAS  Google Scholar 

  • Hewitt CJ, Nebe-von Caron G, Axelsson B, McFarlane CM, Nienow AW (2000) Studies related to the scale-up of high-cell-density E.coli fed-batch fermentations using multiparameter flow cytometry: effect of a changing microenvironment with respect to glucose and dissolved oxygen concentration. Biotechnol Bioeng 70:381–390

    Article  PubMed  CAS  Google Scholar 

  • Horiuchi JI, Kishimoto M (1998) Fuzzy-aided estimation of biological parameters based on material balances. J Ferment Bacteriol 86:111–117

    Article  CAS  Google Scholar 

  • Huang YL, Foellmer TJ, Ang KC, Khoo SB, Yap MGS (1995) Characterization and application of an on-line flow injection analysis/wall-jet electrode system for glucose monitoring during fermentation. Anal Chim Acta 317:223–232

    Article  CAS  Google Scholar 

  • Hubbard DW (1987) Scaleup strategies for bioreactors containing non-newtonian broths. Ann N Y Acad Sci 506:600–607

    PubMed  Article  CAS  Google Scholar 

  • Junker BH, Stanik M, Barna C, Salmon P, Buckland BC (1998) Influence of impeller type on mass transfer in fermentation vessels. Bioprocess Biosyst Eng 19:403–413

    CAS  Google Scholar 

  • Kell DB, Ryder HM, Kaprelyants AS, Westerhoff HV (1991) Quantifying heterogeneity-flow cytometry of bacterial cultures. Anton van Leeuwenhoek Int J Gen Mol Microbiol 60:145–158

    Article  CAS  Google Scholar 

  • Kelly WJ, Humphrey AE (1998) Computational fluid dynamics model for predicting flow of viscous fluids in large fermentor with axial flow impellers and internal cooling coils. Biotechnol Prog 14:248–258

    Article  PubMed  CAS  Google Scholar 

  • Kiick KL, Weberskirch R, Tirell DA (2001) Identification of an expanded set of translationally active methionine analogues in E. coli. FEBS Lett 502:25–30

    Article  PubMed  CAS  Google Scholar 

  • Kim CH, Rao KJ, Youn DJ, Rhee SK (2003) Scale-up of recombinant hirudin production from Saccharomyces cerevisiae. Biotechnol Bioprocess Eng 8:303–305

    CAS  Google Scholar 

  • Kleist S, Miksch G, Hitzmann B, Arndt M, Friehs K, Flaschel E (2003) Optimization of the extracellular production of bacterial phytase with Escherichia coli by using different fed-batch fermentation strategies. Appl Microbiol Biotechnol 61:456–462

    PubMed  CAS  Google Scholar 

  • Klyushnichenko V (2004) Capillary electrophoresis in the analysis and monitoring of biotechnological processes. Methods Mol Biol 276:77–120

    PubMed  CAS  Google Scholar 

  • Kolehmainen M, Rönkkö P, Raatikainen O (2003) Monitoring of yeast fermentation by ion mobility spectrometry measurement and data visualization with self-organizing maps. Anal Chim Acta 484:93–100

    Article  CAS  Google Scholar 

  • Kwint K, Nachin L, Diez A, Nyström T (2003) The bacterial universal stress protein: function and regulation. Curr Opin Microbiol 6:140–145

    Article  PubMed  CAS  Google Scholar 

  • Larsson G, Törnkvist M, Wernersson ES, Trägard C, Noorman H, Enfors SO (1996) Substrate gradients in bioreactors: origin and consequences. Bioprocess Eng 14:281–289

    Article  CAS  Google Scholar 

  • Lee SY (1996) High-cell density culture of Escherichia coli. Trends Biotechnol 14:98–105

    Article  PubMed  CAS  Google Scholar 

  • Liden G (2002) Understanding the bioreactor. Bioprocess Biosyst Eng 24:273–279

    Article  CAS  Google Scholar 

  • Lin HY, Neubauer P (2000) Influence of controlled glucose oscillations on a fed-batch process of recombinant Escherichia coli. J Biotechnol 79:27–37

    Article  PubMed  CAS  Google Scholar 

  • Lin HY, Mathiszik B, Xu B, Enfors SO, Neubauer P (2001) Determinantion of the maximum specific uptake capacities for glucose and oxygen in glucose-limited fed-batch cultivations of Escherichia coli. Biotechnol Bioeng 73:347–357

    Article  PubMed  CAS  Google Scholar 

  • Macaloney G, Hall JW, Rollins MJ, Draper I, Thompson BG, McNeil B (1994) Monitoring biomass and glycerol in an Escherichia coli fermentation using near-infrared spectroscopy. Biotechnol Tech 8:281–286

    Article  CAS  Google Scholar 

  • Matz G, Lennemann F (1996) On-line monitoring of biotechnological processes by gas chromatographic-mass spectrometric analysis of fermentation suspensions. J Chromatogr 750:141–149

    Article  CAS  Google Scholar 

  • Mogk A, Tomoyasu T, Goloubinoff P, Rudiger S, Roder D, Langen H, Bukau B (1999) Identification of thermolabile Escherichia coli proteins: prevention and reversion of aggregation by DnaK and ClpB. EMBO J 18:6934–6949

    Article  PubMed  CAS  Google Scholar 

  • Moser I, Jobst G, Urban GA (2002) Biosensor array for simultaneous measurement of glucose, lactate, glutamate, and glutamine. Biosens Bioelectron 17:297–302

    Article  PubMed  CAS  Google Scholar 

  • Muramatsu R, Negishi T, Mimoto T, Miura A, Miosawa S, Hayashi H (2002) Existence of β-methylnorleucine in recombinant hirudin produced by Escherichia coli. J Biotechnol 93:131–142

    Article  PubMed  CAS  Google Scholar 

  • Neils C, Tyree Z, Finlayson B, Folch A (2004) Combinatorial mixing of microfluidic streams. Lab Chip 4:342–350

    Article  PubMed  CAS  Google Scholar 

  • Neubauer P, Lin HY, Mathiszik B (2003) Metabolic load of recombinant protein production: inhibition of cellular capacities for glucose uptake and respiration after induction of a heterologous gene in Escherichia coli. Biotechnol Bioeng 83:53–64

    Article  PubMed  CAS  Google Scholar 

  • Nishi H, Tsumagari N, Kakimoto T, Terabe S (1989) Separation of β-lactam antibiotics by micellar electrokinetic chromatography. J Chromatogr 477:259–270

    Article  PubMed  CAS  Google Scholar 

  • Nishi H, Fukuyama T, Matsuo M (1990) Separation and determination of aspoxicillin in human plasma by micellar electrokinetic chromatography with direct sample injection. J Chromatogr 515:245–255

    Article  PubMed  CAS  Google Scholar 

  • Nordstrom K, Uhlin BE (1992) Runaway-replication plasmids as tools to produce large quantities of proteins from cloned genes in bacteria. Biotechnology 6:661–666

    Google Scholar 

  • Oniscu C, Galaction AI, Cascaval D, Ungureanu F (2001) Modelling of mixing in stirred bioreactors 1. Mixing time for non-aerated simulated broths. Roum Biotechnol Lett 6:119–129

    Google Scholar 

  • Onyeaka H, Nienow A, Hewitt CJ (2003) Further studies related to the scale-up of high cell density Escherichia coli fed-batch fermentations: the additional effect of changing microenvironment when using aqueous ammonia to control pH. Biotechnol Bioeng 84:474–484

    Article  PubMed  CAS  Google Scholar 

  • Pollard D, Buccino R, Connors N, Kirschner T, Olewinski R, Saini K, Slamon P (2001) Real-time analyte monitoring of a fungal fermentation, at a pilot scale, using in mid-infrared spectroscopy. Bioprocess Biosyst Eng 24:13–24

    Article  CAS  Google Scholar 

  • Reischer H, Schotola I, Striedner G, Pötschacher F, Bayer K (2004) Evaluation of the GFP signal and its aptitude for novel on-line monitoring strategies of recombinant fermentation processes. J Biotechnol 115–125

  • Riesenberg D, Menzel K, Schulz V, Schumann K, Veith G, Zuber G, Knorre WA (1990) High cell density fermentation of recombinant Escherichia coli expressing human interferon alpha 1. Appl Microbiol Biotechnol 34:77–82

    Article  PubMed  CAS  Google Scholar 

  • Rocha I, Ferreira EC (2002) On-line simultaneous monitoring of glucose and acetate with FIA during high cell density fermentation of recombinant E. coli. Bioelectrochem 56:127–129

    Article  Google Scholar 

  • Russel AB, Thomas CR, Lilly MD (1995) Oxygen transfer measurements during yeast fermentations in a pilot scale airlift fermenter. Bioprocess Biosyst Eng 12:71–79

    Google Scholar 

  • Schaefer U, Boos W, Takors R, Weuster-Bootz D (1999) Automated sample device for monitoring intracellular metabolite dynamics. Anal Biochem 270:88–96

    Article  PubMed  CAS  Google Scholar 

  • Schmalzriedt S, Jenne M, Mauch K, Reuss M (2003) Integration of physiology and fluid dynamics. Adv Biochem Eng Biotechnol 80:19–68

    PubMed  CAS  Google Scholar 

  • Schügerl K, Brandes T, Dullau K, Holzhauer-Rieger K, Hotop S, Hübner U, Wu X, Zhou W (1991) Fermentation monitoring and control by on-line flow injection and liquid chromatography. Anal Chim Acta 249:87–100

    Article  Google Scholar 

  • Schweder T, Krüger E, Xu B, Jürgen B, Blomsten G, Enfors SO, Hecker M (1999) Monitoring genes that respond to process-related stress in large-scale bioprocesses. Biotechnol Bioeng 65:151–159

    Article  PubMed  CAS  Google Scholar 

  • Solle D, Geissler D, Stark E, Scheper T, Hitzmann B (2003) Chemometric modelling based on 2D-fluorescence spectra without a calibration measurement. Bioinformatics 19:173–177

    Article  PubMed  CAS  Google Scholar 

  • Spichiger-Keller UE (1997) Ion- and substrate specific optode membranes and optical detection modes. Sens Actuators B Chem B38:68–77

    Article  CAS  Google Scholar 

  • Stark E, Hitzmann B, Schügerl K, Scheper T, Fuchs C, Koster D, Märkl H (2002) In-situ-fluorescence probes: a useful tool for non-invasive bioprocess monitoring. Adv Biochem Eng Biotechnol 74:21–38

    PubMed  CAS  Google Scholar 

  • Thiry M, Cingolani D (2002) Optimizing scale-up fermentation processes. Trends Biotechnol 20:103–105

    Article  PubMed  CAS  Google Scholar 

  • Tothill IE, Newman JD, White SF, Turner APF (1997) Monitoring of the glucose concentration during microbial fermentation using a novel mass-producible biosensor suitable for on-line use. Enzyme Microb Technol 20:590–596

    Article  CAS  Google Scholar 

  • Trelea IC, Titica M, Landaud S, Latrille E, Corrieu G, Cheruy A (2001) Predictive modelling of brewing fermentation: from knowledge-based to black box models. Math Comput Simul 56:405–424

    Article  Google Scholar 

  • Türker M (2004) Development of biocalorimetry as a technique for process monitoring and control in technical scale fermentations. Thermochim Acta (in press)

  • Turner AP (1994) Biosensors. Curr Opin Biotechnol 5:49–53

    Article  PubMed  CAS  Google Scholar 

  • Turner C, Rudnitskaya A, Legin A (2003) Monitoring batch fermentations with an electronic tongue. J Biotechnol 103:87–91

    PubMed  CAS  Google Scholar 

  • Umakoshi H, Kuboi R, Komaswa I, Tsuchido T, Matsumura Y (1998) Heat-induced translocation of cytoplasmic beta-galactosidase across inner membrane of Escherichia coli. Biotechnol Prog 14:210–217

    Article  PubMed  CAS  Google Scholar 

  • Vaccari G, Dosi E, Campi AL, Gonzalez-Vara A, Matteuzi D, Mantovani G (1994) A near infrared spectroscopy technique for the control of fermentation processes: an application to lactic acid fermentation. Biotechnol Bioeng 43:913–917

    Article  CAS  Google Scholar 

  • Vaidyanathan S, Macaloney G, Vaughan J, McNeil B, Harvey LM (1999) Monitoring of submerged bioprocesses. Crit Rev Biotechnol 19:277–316

    Article  CAS  Google Scholar 

  • van de Merbel NC (1997) The use of ultrafiltration and column liquid chromatography for an on-line fermentation monitoring. Trends Anal Chem 16:162–173

    Article  Google Scholar 

  • van de Merbel NC, Lingemann H, Brinkmann UAT (1993) Automated monitoring of biotechnological processes using on-line ultrafiltration and column liquid chromatography. Anal Chim Acta 279:39–50

    Article  Google Scholar 

  • Wang DIC, Cooney CL (1997) Translation of laboratory, pilot, and plant scale data. In: Wang DIC et al (eds) Fermentation and enzyme technology. Wiley, New York, pp 194–211

    Google Scholar 

  • Weickert MJ, Apostol I (1998) High-fidelity translation of recombinant human hemoglobin in Escherichia coli. Appl Environ Microbial 64:1589–1593

    CAS  Google Scholar 

  • Williams KA, Saini S, Wick TM (2002) Computational fluid dynamics modeling of steady-state momentum and mass transport in a bioreactor for cartilage tissue engineering. Biotechnol Progress 18:951–963

    Article  CAS  Google Scholar 

  • Wolfbeis OS (2002) Fiber-optic chemical sensors and biosensors. Anal Chem 74:2663–2678

    Article  PubMed  CAS  Google Scholar 

  • Wong I, Hernandez A, Garcia MA, Segura R, Rodriguez I (2002) Fermentation scale up for recombinant K99 antigen production cloned in Escherichia coli MC1061. Proc Biochem 37:1195–1199

    Article  CAS  Google Scholar 

  • Xu B, Jahic M, Bomsten G, Enfors SO (1999) Glucose overflow metabolism and mixed acid fermentation in aerobic large-scale fed-batch processes with Echerichia coli. Appl Microbiol Biotechnol 51:564–571

    Article  PubMed  Google Scholar 

  • Yawalkar AA, Heesink ABM, Versteeg GF, Vishwas GP (2002) Gas–liquid mass transfer coefficient in stirred tank reactors. Can J Chem Eng 80:840–848

    CAS  Article  Google Scholar 

  • Yim SC, Jeong KJ, Chang HN, Lee SY (2001) High-level secretory production of human granulocyte-colony stimulating factor by fed-batch culture of recombinant E.coli. Bioprocess Biosyst Eng 24:249–254

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Sanofi-Aventis Deutschland, Biocenter H 780, Industriepark Höchst, 65926, Frankfurt, Germany

    F. R. Schmidt

Authors
  1. F. R. Schmidt
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to F. R. Schmidt.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Schmidt, F.R. Optimization and scale up of industrial fermentation processes. Appl Microbiol Biotechnol 68, 425–435 (2005). https://doi.org/10.1007/s00253-005-0003-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00253-005-0003-0

Keywords

  • Fermentation
  • Oxygen Transfer Rate
  • Plasmid Stability
  • Stirrer Speed
  • Overflow Metabolism