Fermentation Microbiology and BiotechnologyE. M. T. El-Mansi, C. F. A. Bryce The pace of progress in fermentation biotechnology is fast and furious, particularly since the advent of genetic engineering and the recent advances in computer science and process control. This book addresses the multidisciplinary nature and the many fascinating aspects of fermentation thus providing a stepping stone in its progress as we enter a new era in which the use of renewable resources is recognized as an urgent need. In addition to central issues such as bioreactor design, fermentation kinetics, flux control analysis and modern strategies for productivity, the book also provides a good account of fermentation control through biosensors and software technologies. Chapters have been written by eminent academics and well know industrialists in the field, thus ensuring a good balance between theory and practice. Furthermore, extensive illustration and highlighting of key concepts are used throughout to enliven the subject and aid understanding. This book will prove invaluable to fermentation industrialists, as well as students reading applied microbiology, industiral microbiology, metabolic engineering and fermentation technology. |
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acetate activity algorithms amino acids ammonia analogue antibiotic autoclaving batch biochemical biomass biomass concentration biomass constituents bioreactor biosensor biosynthetic Biotechnol biotechnology C-mole carbohydrate carbon source cellular chemical control system culture dehydrogenase described dilution rate dissolved oxygen electrode enzyme equation Escherichia coli ethanol example fed-batch feed fermentation process fermentation system fermentor fermentor vessel Figure filter flow rate flux control coefficient function gene glucose glucose oxidase ICDH immobilization increase inoculation input intracellular isocitrate kinetics linear liquid maintenance mass balance measurement medium membrane metabolic products metabolite microbial microorganisms monitoring mutants Nielsen nitrogen nutrient on-line operation organism output overall oxygen controller parameters pathway penicillin phase plasmid probe product formation protein pump reactions reagent recombinant redox Saccharomyces cerevisiae sample sensors set point specific growth rate sterilization stoichiometric coefficient strain improvement substrate substrate concentration surface temperature tion uptake utilization valve variable yeast yield coefficient
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Page 299 - Moletta, R. (1997) Hybrid fuzzy neural network for diagnosis - application to the anaerobic treatment of wine distillery wastewater in a fluidized bed reactor, Water Sci.