International E-publication: Publish Projects, Dissertation, Theses, Books, Souvenir, Conference Proceeding with ISBN.  International E-Bulletin: Information/News regarding: Academics and Research

Response Surface Optimization of Critical Medium Components for the Production of Lactic Acid by Rhizopus arrhizus

Author Affiliations

  • 1Department of Biotechnology, S D College of Engineering and Technology, Muzaffarnagar-251001, UP, INDIA
  • 2Department of Chemical Engineering, Indian Institute of Technology Roorkee, Roorkee-247667, UK, INDIA

Res.J.chem.sci., Volume 2, Issue (3), Pages 1-6, March,18 (2012)

Abstract

Response surface methodology (RSM) was used to optimize fermentation medium for enhancing lactic acid production by Rhizopus arrhizus (RA). In the first step of optimization with Plackett- Burman design, in the second step, a 23 full factorial central composite design and RSM were applied to determine the optimal concentration of each significant variable. Three most effective medium constituents identified by initial screening method of Plackett- Burman were glucose, urea, and MgSO4. Central composite design (CCD) and Response Surface Methodology (RSM) were used in the design of the experiment and in the analysis of results. This procedure limited the number of actual experiments performed while allowing for possible interactions between the three components. The optimum values for the tested variables for the maximum lactic acid production were glucose 10.97g/lit urea 0.135g/lit and MgSO4 7.22%. The maximum lactic acid production was 182.5g/lit. It was 65.7g/lit increased from basal medium.

References

  1. T.B. Victory, Industrial Chemicals Biochemical and Fuel,(761-774)
  2. Casida L.E., J.R., Industrial Microbiology, New Age International (P) Limited, Publishers, 304 (2002)
  3. Stanbury P.F, Whittaker A and Hall S.J., Principle of fermentation technology, (Elsevier, Indian Reprint), 110-111 (2005)
  4. Fannin T.E. Marcus M.D., Anderson D.A. and Bergman H.L., Use of a fractional factorial design to evaluate interactions of environmental factors affecting biodegradation rates, Appl Environ Microbiol, 42 936 (1981)
  5. Chhatpar H.S., Vaidya R. and Vayas P., Statistical optimization of medium components for the production of chitinase by Alcaligenes xylosoxydus, J Enzy Microb Technol, 33, 92 (2003)
  6. Yee L. and Blanch H.W., Defined medium optimization for the growth of recombinant Escherichia coli, 90, Biotechnol Bioeng, 41, 221 (1993)
  7. Adinarayana K. and Ellaiah P., Response surface optimization of the critical medium components for the production of alkaline protease by a newly isolated Bacillus sp., J Pharm pharmaceut Sci, 5 272 (2002)
  8. Deshayes C.M.P., Utilisation de models mathematiques pour I optimization en fermentation, applications aux transformations par les micro-organisms, Bull, Soc. Chim. Fr., 1, 24-34 (1980)
  9. Matthews R.J., Scott R.G., and Morgan S.L., Characterization of an enzymatic determination of arsenic (V) based on response surface methodology, Anal. Chim. Acta, 133, 169-182 (1981)
  10. Box G.E.P., Hunter W.G. and Hunter J.S. statistics for experiments, John Wiley and Sons, New York, 291-334 (1978)
  11. Akhnazarova S. and Kafarov V., Experiment optimization in chemistry and chemical engineering, Mir Publications, Moscow (1982)
  12. Box G.E.P and Wilson K.B., The experimental attainment of optimum conditions. J. Roy. Stat. Soc., B13, 1-45, (1951)
  13. Khuri A.I., and Cornell J.A., Response surface: Design and analysis. Marcel Dekker, Inc, New York (1987)