培养基优化方法-英文版.pdf

Journal of Industrial Microbiology Biotechnology (1999) 23, 456–475  1999 Society for Industrial Microbiology 1367-5435/99/$15.00 http://www.stockton-press.co.uk/jim Strategies for improving fermentation medium performance: a review M Kennedy and D Krouse Industrial Research Limited, PO Box 31–310, Lower Hutt, New Zealand Many techniques are available in the fermentation medium designer’s toolbox (borrowing, component swapping, biological mimicry, one-at-a-time, statistical and mathematical techniques—experimental design and optimization, artificial neural networks, fuzzy logic, genetic algorithms, continuous fermentation, pulsed batch and stoichiometric analysis). Each technique has advantages and disadvantages, and situations where they are best applied. No one ‘magic bullet’ technique exists for all situations. However, considerable advantage can be gained by logical appli- cation of the techniques, combined with good experimental design. Keywords: medium design; medium optimization; fermentation; gamma-linolenic acid; neural networks; fuzzy logic; genetic algorithms Introduction Two different improvement strategies: open and closed When developing an industrial fermentation, designing a fermentation medium is of critical importance because Most of the studies published about medium improvement medium composition can significantly affect product start with the objective of ‘given these components of the concentration, yield and volumetric productivity. For medium what is the best combination possible?’. This can commodity products, medium cost can substantially affect be referred to as a ‘closed strategy’ in that it defines a fixed overall process economics. Medium composi