Ringbom K, Rothberg A, Saxén B
Abo Akademi University, Finland.
J Biotechnol. 1996 Oct 18;51(1):73-82. doi: 10.1016/0168-1656(96)01570-2.
An on-line model, estimating key state variables in bioprocesses, is utilized for control of fed-batch baker's yeast production. The state estimates are produced by balances and phenomenological expressions combined with on-line measurements. The goal of the control strategy is to maintain the highest possible glucose flux that can be entirely respiratively assimilated by the cells, resulting in the highest possible yeast growth without formation of metabolic products, such as acetic acid and ethanol. Stepwise improvement of the control algorithm is carried out in order to find a strategy to avoid undesired, irreversible metabolic pathways. In the final algorithm, such undesired changes in metabolism are predicted from an estimate of intracellular storage carbohydrates. A considerable decrease in the estimate indicates future metabolic changes at a time early enough to avoid them. At maximal yield, a growth rate near the highest possible is obtained in laboratory-scale Saccharomyces cerevisiae cultivations with the control strategy developed.
一个用于估计生物过程中关键状态变量的在线模型被用于控制分批补料面包酵母的生产。状态估计值由平衡式和现象学表达式结合在线测量得出。控制策略的目标是维持尽可能高的葡萄糖通量，使细胞能够完全通过呼吸作用将其同化，从而在不形成代谢产物（如乙酸和乙醇）的情况下实现尽可能高的酵母生长。为了找到一种避免不期望的、不可逆代谢途径的策略，对控制算法进行了逐步改进。在最终算法中，根据细胞内储存碳水化合物的估计值来预测代谢中此类不期望的变化。估计值的显著下降表明在足够早的时间会出现未来的代谢变化，从而能够避免这些变化。采用所开发的控制策略，在实验室规模的酿酒酵母培养中，以最大产量获得了接近可能的最高生长速率。
