Electron, carbon, and nitrogen balances can be thought of as relationships among the time rates of change of the various compounds participating in a fermentation process. As such, they define the minimum number of necessary measurements from which the remaining rates can be determined through the use of the balances. All possibilities, however, are not equivalent, and some of them lead to singularities and solutions of high sensitivity. These possibilities are reviewed in this paper, and suggestions are offered in regard t o the combination of rate measurements from which robust biomass estimates can be produced.
An algorithm is presented for detecting the appearance of contaminants during batch or fed-batch fermentations, using only presently available on-line measurements. Its adaptive nature enables it to rely on almost no prior knowledge of the real process. The necessary on-line measurements are total biomass and its production rate; it is also shown how a physical variable such as oxygen uptake can be used alone instead. The algorithm's properties are studied theoretically and through simulations. These were confirmed by on-line experimental results, obtained with a Yeast culture, both pure and contaminated by a Bacteria. The algorithm does not detect contaminants when none are there, and it also provides a convergent estimate of a pure culture's specific growth rate. Contaminated cultures are recognized by the algorithm, and this detection can be made more or less conservative. After detection, the various estimates may diverge, due to general observability difficulties, though this divergence can itself be monitored. Moreover, the algorithm is easy to tune and its qualitative behavior is quite insensitive to its adjustable parameters. A practical criterion and scheme for implementation are proposed. The generality of the approach, which far exceeds the experimental system used, is finally discussed.
A kinetic model of ethanol fermentation conducted under a variety of conditions in a continuous four-stage reactor is proposed. The expressions for specific growth and product formation rates are: micro = micro0 exp(-k1P)(1- X/X1) nu P = nu0 exp(-k2P (1 - X/X2). Parameters were identified by nonlinear programming and shown to fit data correctly for steady states of seven different experiments. The product inhibition constants were of 27 and 84 g/L, respectively. Secondary inhibitions were represented by the linear biomass term. The proposed model gave a better description of phenomena than one which only took ethanol inhibition into account. The same model also fitted batch fermentation data, with only some parameters altering significantly. The use of this model for on-line purposes is discussed.
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