Acetic Acid Production by an Electrodialysis Fermentation Method with a Computerized Control System

In acetic acid fermentation by Acetobacter aceti, the acetic acid produced inhibits the production of acetic acid by this microorganism. To alleviate this inhibitory effect, we developed an electrodialysis fermentation method such that acetic acid is continuously removed from the broth. The fermentation unit has a computerized system for the control of the pH and the concentration of ethanol in the fermentation broth. The electrodialysis fermentation system resulted in improved cell growth and higher productivity over an extended period; the productivity exceeded that from non-pH-controlled fermentation. During electrodialysis fermentation in our system, 97.6 g of acetic acid was produced from 86.0 g of ethanol; the amount of acetic acid was about 2.4 times greater than that produced by non-pH-controlled fermentation (40.1 g of acetic acid produced from 33.8 g of ethanol). Maximum productivity of electrodialysis fermentation in our system was 2.13 g/h, a rate which was 1.35 times higher than that of non-pH-controlled fermentation (1.58 g/h).     

Enhanced production of L-(+)-lactic acid in chemostat by Lactobacillus casei DSM 20011 using ion-exchange resins and cross-flow filtration in a fully automated pilot plant controlled via NIR

Due to the lack of suitable in-process sensors, on-line monitoring of fermentation processes is restricted almost exclusively to the measurement of physical parameters only indirectly related to key process variables, i.e., substrate, product, and biomass concentration. This obstacle can be overcome by near infrared (NIR) spectroscopy, which allows not only real-time process monitoring, but also automated process control, provided that NIR-generated information is fed to a suitable computerized bioreactor control system. Once the relevant calibrations have been obtained, substrate, biomass and product concentration can be evaluated on-line and used by the bioreactor control system to manage the fermentation. In this work, an NIR-based control system allowed the full automation of a small-scale pilot plant for lactic acid production and provided an excellent tool for process optimization. The growth-inhibiting effect of lactic acid present in the culture broth is enhanced when the growth-limiting substrate, glucose, is also present at relatively high concentrations. Both combined factors can result in a severe reduction of the performance of the lactate production process. A dedicated software enabling on-line NIR data acquisition and reduction, and automated process management through feed addition, culture removal and/or product recovery by microfiltration was developed in order to allow the implementation of continuous fermentation processes with recycling of culture medium and cell recycling. Both operation modes were tested at different dilution rates and the respective cultivation parameters observed were compared with those obtained in a conventional continuous fermentation. Steady states were obtained in both modes with high performance on lactate production. The highest lactate volumetric productivity, 138 g L(-1) h(-1), was obtained in continuous fermentation with cell recycling.     

Evaporative temperature and moisture control in solid substrate fermentation

Summary An integrated computerized control system, consisting of temperature and moisture sensors, a variable relative humidity air stream and water sprayers was used to control temperature and moisture in the solid substrate fermentation of extruded corn withRhizopus oligosporus in a 15 l rotary drum fermenter. Dry air was blown through the substrate to force evaporative cooling, balanced by spraying of cold water to maintain constant moisture.     

Development of a versatile computer integrated control system for bioprocess controls

A general approach is described for the implementation of a networked multi-unit computer integrated control system. The use of data acquisition hardware and graphical programming tools alleviates tedious programming and maintains potency and flexibility. One application of the control system, the control of a mammalian cell perfusion culture based on a key nutrient glucose concentration, was demonstrated. The control system offers customized user interface for all process control parameters and allows the flexibility for continued improvement and implementation of new tailored functions. The temperature, pH, dissolved oxygen and glucose level were accurately controlled. This revised version was published online in June 2006 with corrections to the Cover Date.     

Experimental adaptive on-line optimization of cellular productivity of a continuous bakers' yeast culture

An adaptive on-line optimization method that utilizes dynamic model identification has been applied to maximize the cellular productivity of a continuous bakers' yeast culture. Experiments were conducted on a sophisticated computerized fermentation system. Experimental results show that the adaptive on-line optimization method requires very little a priori information, is easy to implement, converges quickly, adapts to changes in the process, and is stable even when operational difficulties are encountered.     

Optimal situation control for a biosynthetic process on the basis of a prediction filter

A concept for the periodic control of fermentation processes is presented which realizes a strategy with maximal material and energetic efficiencies. The program system for situation control, problems of selection of the feature vector and the experimental results are discussed.     

Measurement,control, and modeling of submerged acetic acid fermentation

For control and optimization of large scale bioprocesses, mathematical models are needed to describe transient growth and/or product formation. Such models can only be developed from reliable experimental data. A computerized experimental system was applied to submerged acetic acid fermentation with industrial Acetobacter strains in order to obtain quantitatively reproducible long-term data. Automated repeated-batch fermentations were carried out over a period of one year. It was found that consideration of substrate, product, and biomass concentrations alone was not sufficient to describe transient culture conditions. At least one more internal parameter must be taken into account. A delay-time model was developed which takes into consideration the variable concentration of an internal component of the cells, the ribonucleic acid. This model was used to simulate the acetic acid fermentation. The simulation results agreed well with the experimental data. Thus, the validity of the model assumptions could be confirmed. The model was capable of simulating the lag-phase of growth as well as lysis of microorganisms due to product inhibition.     

Data acquisition and control of a continuous fermentation unit

Summary Data acquisition and computer control ofZymomonas mobilis fermentation for ethanol production has been studied. An HP 200 series microcomputer system was used in conjunction with an HP 3497A data acquisition unit. On-line ethanol, glucose and cell mass were measured for use as possible control variables. Dilution rate was used as the manipulative variable. A versatile, user-friendly data acquisition program was written to gather, control and analyze data from the continuous fermentation. The program allows user-given control and calibration algorithms so that sophisticated control policies, e.g., self-tuning regulator (STR) and instrumentation, can be implemented with relative ease.     

An integrated microprocessor-based fermenter control system

An integrated microprocessor-based fermenter controller was developed in 1980 for an operational environment at Cetus Corp. The main goals in the design and construction of the system were (1) to facilitate scale-up; (2) to provide flexibility and high performance for optimizing fermentation processes; and (3) to be cost-effective for 15 in-house systems. It was also developed to work in conjunction with a laboratory minicomputer for on-line optimization experiments. The controller controls temperature, agitation, dissolved oxygen, pH, and foam throughout each fermentation run without manual intervention. The feedback control parameters have been optimized to provide very accurate control over a wide range of setpoint conditions and under rapidly changing metabolic conditions such as induced during an Escherichia coli batch run. The controller has also been configured to monitor, display, and record each of the controlled variables; support the interactive operator console; and communicate with the laboratory computer. In over 4 years of operation, these systems have met the design goals and have proven to be very reliable. The controller is described, its operational performance presented, and a typical fermentation run delineated.     

Stabilizing feedback of a nonlinear process involving uncertain data

A nonlinear control system describing the process of continuous methane fermentation is considered. Assuming that the parameters of the model are not exactly known but bounded within intervals, the set of optimal static points according to a practical criterion is computed. A continuous feedback control is proposed, which asymptotically stabilizes the dynamic system towards this set. Numerical results are also reported.     

Use of an Extended Kalman Filter and development of an automated system for xylose fermentation by a recombinantEscherichia coli

Summary An automated system was developed for on-line monitoring and control of xylose fermentation by a recombinantEscherichia coli. A 7-L fermenter was interfaced with a personal computer. Control circuits were constructed and a software was developed to estimate the states of the fermentation using an Extended Kalman Filter. The automated system combined with the Extended Kalman Filter provided a satisfactory way to obtain on-line information regarding estimation of fermentation parameters.     

Dynamic fuzzy model based predictive controller for a biochemical reactor

The kinetics of bioreactions often involve some uncertainties and the dynamics of the process vary during the course of fermentation. For such processes, conventional control schemes may not provide satisfactory control performance and demands extra effort to design advanced control schemes. In this study, a dynamic fuzzy model based predictive controller (DFMBPC) is presented for the control of a biochemical reactor. The DFMBPC incorporates an adaptive fuzzy modeling framework into a model based predictive control scheme to derive analytical controller output. The DFMBPC has the flexibility to opt with various types of fuzzy models whose choice also lead to improve the control performance. The performance of DFMBPC is evaluated by comparing with a fuzzy model based predictive controller (FMBPC) with no model adaptation and a conventional PI controller. The results show that DFMBPC provides better performance for tracking setpoint changes and rejecting unmeasured disturbances in the biochemical reactor.     

Fermentation of biomass sugars to ethanol using native industrial yeast strains

In this paper, the feasibility of a technology for fermenting sugar mixtures representative of cellulosic biomass hydrolyzates with native industrial yeast strains is demonstrated. This paper explores the isomerization of xylose to xylulose using a bi-layered enzyme pellet system capable of sustaining a micro-environmental pH gradient. This ability allows for considerable flexibility in conducting the isomerization and fermentation steps. With this method, the isomerization and fermentation could be conducted sequentially, in fed-batch, or simultaneously to maximize utilization of both C5 and C6 sugars and ethanol yield. This system takes advantage of a pH-dependent complexation of xylulose with a supplemented additive to achieve up to 86% isomerization of xylose at fermentation conditions. Commercially-proven Saccharomyces cerevisiae strains from the corn-ethanol industry were used and shown to be very effective in implementation of the technology for ethanol production.     

Design of methanol Feed control in Pichia pastoris fermentations based upon a growth model

The methylotrophic yeast Pichia pastoris is an effective system for recombinant protein productions that utilizes methanol as an inducer, and also as carbon and energy source for a Mut(+) (methanol utilization plus) strain. Pichia fermentation is conducted in a fed-batch mode to obtain a high cell density for a high productivity. An accurate methanol control is required in the methanol fed-batch phase (induction phase) in the fermentation. A simple "on-off" control strategy is inadequate for precise control of methanol concentrations in the fermentor. In this paper we employed a PID (proportional, integral and derivative) control system for the methanol concentration control and designed the PID controller settings on the basis of a Pichia growth model. The closed-loop system was built with four components: PID controller, methanol feed pump, fermentation process, and methanol sensor. First, modeling and transfer functions for all components were derived, followed by frequency response analysis, a powerful method for calculating the optimal PID parameters K(c) (controller gain), tau(I) (controller integral time constant), and tau(D) (controller derivative time constant). Bode stability criteria were used to develop the stability diagram for evaluating the designed settings during the entire methanol fed-batch phase. Fermentations were conducted using four Pichia strains, each expressing a different protein, to verify the control performance with optimal PID settings. The results showed that the methanol concentration matched the set point very well with only small overshoot when the set point was switched, which indicated that a very good control performance was achieved. The method developed in this paper is robust and can serve as a framework for the design of other PID feedback control systems in biological processes.     

An efficient medical database system implementation with its tool and data structure consideration

The development of a new system for medical database application running on minicomputer under MUMPS system is described. Two kinds of data representation in global structure are briefly reviewed. The use of a subject oriented multi-dimensional data structure greatly simplifies database design and facilitates data manipulation, organization, selective retrieval and software development. It is concluded that the program generator approach can provide the flexibility necessary for various applications and future growth of computerized medical record system. The final system has been proven effective in practical operation. The future extension concerns the introduction of multi-microprocessor structure and logic representation is presented.     

Improving IV insulin administration in a community hospital

Diabetes mellitus is a major independent risk factor for increased morbidity and mortality in the hospitalized patient, and elevated blood glucose concentrations, even in non-diabetic patients, predicts poor outcomes. The 2008 consensus statement by the American Association of Clinical Endocrinologists (AACE) and the American Diabetes Association (ADA) states that "hyperglycemia in hospitalized patients, irrespective of its cause, is unequivocally associated with adverse outcomes." It is important to recognize that hyperglycemia occurs in patients with known or undiagnosed diabetes as well as during acute illness in those with previously normal glucose tolerance. The Normoglycemia in Intensive Care Evaluation-Survival Using Glucose Algorithm Regulation (NICE-SUGAR) study involved over six thousand adult intensive care unit (ICU) patients who were randomized to intensive glucose control or conventional glucose control. Surprisingly, this trial found that intensive glucose control increased the risk of mortality by 14% (odds ratio, 1.14; p = 0.02). In addition, there was an increased prevalence of severe hypoglycemia in the intensive control group compared with the conventional control group (6.8% vs. 0.5%, respectively; p < 0.001). From this pivotal trial and two others, Wyoming Medical Center (WMC) realized the importance of controlling hyperglycemia in the hospitalized patient while avoiding the negative impact of resultant hypoglycemia. Despite multiple revisions of an IV insulin paper protocol, analysis of data from usage of the paper protocol at WMC shows that in terms of achieving normoglycemia while minimizing hypoglycemia, results were suboptimal. Therefore, through a systematical implementation plan, monitoring of patient blood glucose levels was switched from using a paper IV insulin protocol to a computerized glucose management system. By comparing blood glucose levels using the paper protocol to that of the computerized system, it was determined, that overall, the computerized glucose management system resulted in more rapid and tighter glucose control than the traditional paper protocol. Specifically, a substantial increase in the time spent within the target blood glucose concentration range, as well as a decrease in the prevalence of severe hypoglycemia (BG < 40 mg/dL), clinical hypoglycemia (BG < 70 mg/dL), and hyperglycemia (BG > 180 mg/dL), was witnessed in the first five months after implementation of the computerized glucose management system. The computerized system achieved target concentrations in greater than 75% of all readings while minimizing the risk of hypoglycemia. The prevalence of hypoglycemia (BG < 70 mg/dL) with the use of the computer glucose management system was well under 1%.     

Backpropagation neural network predictive control and control scheme comparison of 2,3-butanediol fermentation by Klebsiella oxytoca

A backpropagation neural network (BPN) was applied for the control study of 2,3-butanediol fermentation (2,3-BDL) carried by Klebsiella oxytoca. The measurements of cell mass and glucose were not included in the network models, instead, only the on-line measured product concentrations from the MIMS (membrane introduction mass spectrometer) were involved. Oxygen composition was chosen to be the control variable for this fermentation system for the formation of 2,3-BDL is regulated by oxygen. Oxygen composition was directly correlated to the measured product concentrations. A two-dimensional (number of input nodes by number of data sets) moving window to supply data for on-line, dynamic learning of this fermentation system was applied. The input nodes of the networks were also properly selected. Two neural network control schemes for this 2,3-BDL fermentation were discussed and compared in this work. Fermentations often exist time delay due to the measurement and their slow reaction nature. Hence, the order of time delay for the network controller was also investigated.     

On-line monitoring and controlling system for fermentation processes

A personal computer-based on-line monitoring and controlling system was developed for the fermentation of microorganism. The on-line HPLC system for the analysis of glucose and ethanol in the fermentation broth was connected to the fermenter via an auto-sampling equipment, which could perform the pipetting, filtration and dilution of the sample and final injection onto the HPLC through automation based on a programmed procedure. The A/D and D/A interfaces were equipped in order to process the signals from electrodes and from the detector of HPLC, and to direct the feed pumps, the motor of stirrer and gas flow-rate controller. The software that supervised the control of the stirring speed, gas flow-rate, pH value, feed flow-rate of medium, and the on-line measurement of glucose and ethanol concentration was programmed by using Microsoft Visual Basic under Microsoft Windows. The signal for chromatographic peaks from on-line HPLC was well captured and processed using an RC filter and a smoothing algorithm. This monitoring and control system was demonstrated to be effective in the ethanol fermentation of Zymomonas mobilis operated in both batch and fed-batch modes. In addition to substrate and product concentrations determined by on-line HPLC, the biomass concentration in Z. mobilis fermentation could also be on-line estimated by using the pH control and an implemented software sensor. The substrate concentration profile in the fed-back fermentation followed well the set point profile due to the fed-back action of feed flow-rate control.