In airlift reactors transport phenomena are achieved by pneumatic agitation and circulation occurs in a defined cyclic pattern through a loop. In the present work, the effect of geometrical relations on gas holdup and liquid velocity, and consequently on the gas-liquid mass transfer coefficient, was studied in a 6-liter airlift bioreactor with A D/A R = 0.63; A D, downcomer cross-sectional area, and A R, riser cross-sectional area. Measurements of the volumetric oxygen transfer coefficient (kLa) were taken in a water-air system using a modified sulfite oxidation method. Different conditions were examined by varying parameters such as superficial air velocity in the riser (U GR), bottom clearance (d1) and top clearance (d2). It was observed from the experimental results that d1 and d2 have a remarkable effect on kLa values. The effect is due to their influence on gas holdup and liquid velocity, consequently affecting kLa. Superficial air velocity in the riser (U GR) ranged from 0.0126 to 0.0440 m.s-1 and kLa varied between 40 to 250 h-1, whereas gas holdup (e) reached values up to 0.2. The volumetric oxygen transfer coefficient (kLa), gas holdup in the riser (eR) and downcomer (eD) and superficial liquid velocity in the riser (U LR) for all the geometrical relations were successfully correlated with dimensionless numbers, namely, the Sherwood number (Sh) and the Froude number (Fr) as well as with geometrical relations such as the bottom space ratio (B = d1/D D) and top space ratio (T = (d2 + D D)/D D).

The kinetics of clavulanic acid production process by Streptomyces clavuligerus NRRL 3585 was studied. Experiments were carried out in a 4 liters bioreactor, utilizing 2 complex media containing glycerol as the carbon and energy source, and peptone or Samprosoy 90NB (soybean protein) as nitrogen source. Temperature was kept at 28°C and the dissolved oxygen was controlled automatically at 40 % saturation value. Samples were withdrawn for determination of cell mass (only peptone medium), glycerol and product concentrations. Gas analyzers allowed on line determination of CO2 and O2 contents in the exit gas. With Samprosoy, cell mass was evaluated by determining glycerol consumption and considering the cell yield, Y X/S, as being the same for both cases. Oxygen uptake and CO2 production rates were strongly related to growth and substrate consumption, allowing determination of stoichiometric constants in relation to growth, substrate, oxygen, product and carbon dioxide.

In the present work rheological characteristics and volumetric oxygen transfer coefficient (kLa) were investigated during batch cultivations of Streptomyces clavuligerus NRRL 3585 for production of clavulanic acid. The experimental rheological data could be adequately described in terms of the power law model and logistic equation. Significant changes in the rheological parameters consistency index (K) and flow behavior index (n) were observed with the fermentation evolution. Interesting correlations between the consistency index (K)/biomass concentration (C X) and the flow behavior index (n)/biomass concentration were proposed. Volumetric oxygen mass transfer coefficient (kLa) was determined by the gas balance method. Classical correlation relating the volumetric oxygen mass transfer coefficient to the operating conditions, physical and to transport properties, including apparent viscosity (muap), could be applied to the experimental results.

At present, direct on-line measurements of key bioprocess variables as biomass, substrate and product concentrations is a difficult task. Many of the available hardware sensors are either expensive or lack reliability and robustness. To overcome this problem, indirect estimation techniques have been studied during the last decade. Inference algorithms rely either on phenomenological or on empirical models. Recently, hybrid models that combine these two approaches have received great attention. In this work, a hybrid neural network algorithm was applied to a fermentative process. Mass balance equations were coupled to a feedforward neural network (FNN). The FNN was used to estimate cellular growth and product formation rates, which are inserted into the mass balance equations. On-line data of cephalosporin C fed-batch fermentation were used. The measured variables employed by the inference algorithm were the contents of CO2 and O2 in the effluent gas. The fairly good results obtained encourage further studies to use this approach in the development of process control algorithms.

Cephalosporin C, a b -lactam antibiotic, is the starting molecule for industrial production of semi-synthetic cephalosporins. The bioprocess for its production is carried out in batch stirred and aerated tank reactors utilizing strains of the filamentous fungus Cephalosporium acremonium. In this work a comparison was made between the processes of production of cephalosporin C in a conventional batch bioreactor, with synthetic medium containing glucose and sucrose, and in a fed-batch reactor at several flowrates of supplementary medium containing invert sucrose. In general, the fed-batch process was shown to be more efficient than the conventional batch one, and the process in which the lowest supplementation flowrate was used presented an antibiotic production significantly higher than those obtained under the other conditions.

The production of penicillin G by Penicillium chrysogenum IFO 8644 was simulated employing a feedforward neural network with three layers. The neural network training procedure used an algorithm combining two procedures: random search and backpropagation. The results of this approach were very promising, and it was observed that the neural network was able to accurately describe the nonlinear behavior of the process. Besides, the results showed that this technique can be successfully applied to control process algorithms due to its long processing time and its flexibility in the incorporation of new data