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.     

Detection of phase shifts in batch fermentation via statistical analysis of the online measurements: a case study with rifamycin B fermentation

Industrial production of antibiotics, biopharmaceuticals and enzymes is typically carried out via a batch or fed-batch fermentation process. These processes go through various phases based on sequential substrate uptake, growth and product formation, which require monitoring due to the potential batch-to-batch variability. The phase shifts can be identified directly by measuring the concentrations of substrates and products or by morphological examinations under microscope. However, such measurements are cumbersome to obtain. We present a method to identify phase transitions in batch fermentation using readily available online measurements. Our approach is based on Dynamic Principal Component Analysis (DPCA), a multivariate statistical approach that can model the dynamics of non-stationary processes. Phase-transitions in fermentation produce distinct patterns in the DPCA scores, which can be identified as singular points. We illustrate the application of the method to detect transitions such as the onset of exponential growth phase, substrate exhaustion and substrate switching for rifamycin B fermentation batches. Further, we analyze the loading vectors of DPCA model to illustrate the mechanism by which the statistical model accounts for process dynamics. The approach can be readily applied to other industrially important processes and may have implications in online monitoring of fermentation batches in a production facility.     

Integrated system for bioprocess monitoring and diagnosis using a local area network

Bioprocess monitoring and data analysis utilizing a local area network (LAN) is described in which an integrated computer environment provides for real-time monitoring from several remote personal computers with easy evaluation of the current process status and providing a common utilization of fermentation data. The computer network also enhances the decision-making process in the management of the production plant. Bioprocess control utilizing a LAN environment is expected to promote better utilization of fermentation data accumulated through repeated operations and to realize advanced control of fermentation processes. © Rapid Science Ltd. 1998     

双歧因子对双歧杆菌增殖的影响

应用含有不同浓度的双歧因子(微维乐)的培养基对双歧杆菌进行了定性、定量观察。其结果表明,微维乐对双歧杆菌有明显的促进作用;在双歧杆菌制剂的生产过程中,添加一定量的微维乐,不仅可以提高双歧杆菌收率,而且还可以缩短菌种发酵时间。最佳添加量为1.5%,最佳发酵时间为1.5 h。     

An on-line approach to monitor ethanol fermentation using FTIR spectroscopy

Fermentation process control is currently limited by its inability to measure parameters such as substrate, product, and biomass concentrations rapidly for consistent on-line feedback. Physical and chemical parameters, such as temperature and pH, currently can be obtained on-line using appropriate sensors. However, to obtain information on the concentration of the substrate, product, and biomass, samples must be taken off-line for measurement. With the use of spectroscopic techniques, real-time monitoring of process constituents such as product and substrate is possible. Spectroscopic techniques are rapid and nondestructive, require minimal or no sample preparation, and can be used to simultaneously assess several constituents in complex matrices. The production of ethanol is the largest fermentation process in terms of production volume and economic value as a result of its prominence in the food, agricultural, and fuel industries. This study attempts to develop an on-line ethanol fermentation monitoring technique using Fourier transform infrared (FTIR) spectroscopy with a flow-through ATR capability. Models developed using multivariate statistics, employed to obtain on-line FTIR measurements, were successfully validated by off-line HPLC analysis and spectrophotometry data. Standard errors of prediction (SEP) values of 0.985 g/L (R2 = 0.996), 1.386 g/L (R2 = 0.998), and 0.546 (R2 = 0.972) were obtained for ethanol, glucose, and OD, respectively. This work demonstrates that FTIR spectroscopy could be used for rapid on-line monitoring of fermentation.     

Real-time analyte monitoring of a fungal fermentation, at pilot scale, using in situ mid-infrared spectroscopy

Robust in situ biochemical monitoring is essential for the development of substrate feed control to optimize fermentation processes. The scale up of the fermentation for the fungus Glarea lozoyensis can benefit from such technology to improve the yield of the pharmaceutically important pneumocandin of interest and control the levels of unwanted analogues. A new in situ probe, using a diamond attenuated total reflection element, was evaluated at pilot scale for the quantitative measurement of fermentation analytes using Fourier transform mid-IR spectrometry. The new technology was shown to be stable, unaffected by reactor operation conditions of agitation, airflow, and backpressure, but sensitive to temperature control. Both glucose and phosphate were simultaneously monitored during a seed fermentation at 280 L pilot scale using complex medium with detection to 0.1 g/L for both analytes. Fructose, glutamate, and proline were monitored at 75 L scale using production media with detection limits of 0.1, 0.5, and 0.5 g/L respectively. Partial least squares calibration/prediction models were created for analytes of interest using off-line reference measurements and specific spectral regions. Good fits were obtained between off-line measurements and those predicted by in situ mid-IR. Standard errors of prediction (SEP) for glucose (range 18-0.1 g/L) and phosphate (range 11-7.5 g/L) were 0.16 and 1.8 g/L respectively with mean percentage errors (MPEs) around 2.5%. SEP values for the production process: fructose (range 20-0.1 g/L), glutamate (8-0.5 g/L), and proline (12-0.5 g/L) were 0.44, 0.6, and 0.5 g/L respectively with MPEs of 2.2, 5.3, and 10.1%. The technology effectively demonstrates quantitative multicomponent analysis of fermentation processes using in situ monitoring.     

Inline noninvasive Raman monitoring and feedback control of glucose concentration during ethanol fermentation

Raman spectroscopy as a process analytical technology tool was implemented for the monitoring and control of ethanol fermentation carried out with Saccharomyces cerevisiae. The need for the optimization of bioprocesses such as ethanol production, to increase product yield, enhanced the development of control strategies. The control system developed by the authors utilized noninvasive Raman measurements to avoid possible sterilization problems. Real-time data analysis was applied using partial least squares regression (PLS) method. With the aid of spectral pretreatment and multivariate data analysis, the monitoring of glucose and ethanol concentration was successful during yeast fermentation with the prediction error of 4.42 g/L for glucose and 2.40 g/L for ethanol. By Raman spectroscopy-based feedback control, the glucose concentration was maintained at 100 g/L by the automatic feeding of concentrated glucose solution. The control of glucose concentration during fed-batch fermentation resulted in increased ethanol production. Ethanol yield of 86% was achieved compared to the batch fermentation when 75 % yield was obtained. The results show that the use of Raman spectroscopy for the monitoring and control of yeast fermentation is a promising way to enhance process understanding and achieve consistently high production yield.     

Optimal medium use for continuous high density perfusion processes

For maintenance of high cell density in continuous perfusion processes not only feeding with substrates but also removal of inhibitors and toxic waste products are of special interest. High perfusion rates cause large volumes of product containing medium which have to be processed in product isolation. In order to minimize these volumes concentrated feed solutions of optimized medium are used. On the other hand, such media may cause high concentrations of toxic or inhibitory metabolites which can negatively influence cell growth and product formation. Especially, if the spent medium (or special parts of it) is used again after product isolation, the removal or even better the control of inhibitor production is of highest importance. We have developed a continuous fermentation concept and system (continuous medium cycle bioreactor, cMCB) in which both limitation and inhibition effects can be generated to identify special substances as limiting or inhibitory components. With the results from those experiments it was possible to lower the total perfusion rate during serum-free perfusion cultures of hybridoma cells and to obtain an optimal substrate utilization. The advantages for decreasing the production costs (for media, special supplements and product isolation) are obvious. The other aim of this study was to identify secreted metabolic waste products as inhibitor or toxic metabolite.     

Physiological state control of fermentation processes

In this article a novel approach to the control of fermentation processes is introduced. A "physiological state control approach" has been developed using the concept of representing fermentation processes through the current physiological state of the cell culture. No conventional mathematical model is required for the synthesis of such a control system.The main idea is based on the fact that during batch, feed-batch, or even continuous cultivation the physiological characteristics of the cell population, jointly expressed by the term "physiological state", are not constant but rather variable, which is reflected in expected or unexpected changes in the behavior of the control plant, and which requires flexible alteration of the current control strategy. The proposed approach involves decomposition of the physiological state space into several subspaces called "physiological situations." In every physiological situation the cell population expresses stable characteristics, and therefore an invariant control strategy can be effectively applied. The on-line functions of the physiological state control system consist of the calculation of physiological state variables, determination of the current physiological situation as an element of a previously defined set of known physiological situations, switching of the relevant control strategy, and calculation of the control action. Attention is focused on the synthesis of the novel and nonstandard part of the control system - the algorithm for online recognition of the current physiological state. To this end an effective approach, based on artificial intelligence methods, particularly fuzzy sets theory and pattern recognition theory, was developed. Its practical realization is demonstrated using data from a continuous fermentation process for single cell protein production.     

Computational algorithms for optimal feed rates for a class of fed-batch fermentation: Numerical results for penicillin and cell mass production

Based upon the general characteristics of the optimal feed rate profiles presented in an earlier article, efficient computational algorithms have been developed for fed-batch fermentation processes described by four or less mass balance equations. These algorithms make computations of optimal substrate feed rate profiles straight forward and simple for various fed-batch cultures for such products as antibiotics, amino acids, enzymes, alcohols, and cell mass. Numerical examples of penicillin fermentation and bacterial cell mass production are given in detail, illustrating the use of these algorithms.     

Structured modeling and state estimation in a fermentation process: Lipase production by Candida rugosa

A simple structured mathematical model coupled with a methodology of state and parameter estimation is developed for lipase production by Candida rugosa in batch fermentation. The model describes the system according to the following qualitative observations and hypothesis: Lipase production is induced by extracellular oleic acid present in the medium. The acid is transported into the cell where it is consumed, transformed, and stored. Lipase is excreted to the medium where it is distributed between the available oil-water interphase and aqueous phase. Cell growth is modulated by the intracellular substrate concentration. Model parameters have been determined and the whole model validated against experiments not used in their determination. The estimation problem consists in the estimation of three state variables (biomass, intra- and extracellular substrate) and two kinetic parameters by using only the on-line measurement provided by exhaust gas analysis. The presented estimation strategy divides the complex problem into three subproblems that can be solved by stable algorithms. The estimation of biomass (X) and the specific growth rate (mu), is achieved by a recursive prediction error algorithm using the on-line measurement of the carbon dioxide evolution rate. mu is then used to perform an estimation of intracellular substrate and the other kinetic parameter related to substrate transport (A) by an adaptive observer. Extracellular substrate is then evaluated by means of the estimated values of intracellular substrate and biomass through the material balance of the reactor. Simulation and experimental tests showed good performance of the developed estimator, which appears suitable to be used for process control and monitoring. (c) 1995 John Wiley & Sons, Inc.     

Application of an airlift bioreactor to the nystatin biosynthesis

Pilot plant studies were performed using a concentric-tube airlift bioreactor of 2.5 m³ fermentation volume. The results have proven the relative merits of such a system in the biosynthesis of nystatin, produced by Streptomyces noursei, in submerged aerobic cultivation and batch operation mode. The results were compared to those obtained in a pilot-scale stirred tank bioreactor of 3.5 m³ fermentation volume. The fermentation processes in the two fermentation devices were similar with respect to substrate utilization, biomass production and nystatin biosynthesis. In the riser section, the dissolved oxygen concentration was higher than that in the downcomer. The volumetric oxygen mass transfer coefficient was dependent on the rheological behaviour of the biosynthesis liquids, which was not constant during the fermentation process. The total energy consumption for nystatin production in the airlift bioreactor was 56% of that in the stirred tank, while the operating costs represented 78% of those in the stirred tank bioreactor.     

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.     

Key technologies for the industrial production of fumaric acid by fermentation

The growing concern about the safety of food and dairy additives and the increasing costs of petroleum-based chemicals have rekindled the interest in the fermentation processes for fumaric acid production. The key problems of the industrial production of microbial fumaric acid are reviewed in this paper. Various strategies, including strain improvement, morphology control, substrate choice, fermentation process and separation process, are summarized and compared, and their economical possibilities for industrial processes are discussed. The market prospects and technological strategies for value-added fumaric acid derivatives are also addressed. The future prospects of microbial fumaric acid production are proposed at the end of this article.     

A robust soft sensor based on artificial neural network for monitoring microbial lipid fermentation processes using Yarrowia lipolytica

Microbial oils produced by Yarrowia lipolytica offer an environmentally friendly and sustainable alternative to petroleum as well as traditional lipids from animals and plants. The accurate measurement of fermentation parameters, including the substrate concentration, dry cell weight, and lipid accumulation, is the foundation of process control, which is indispensable for industrial lipid production. However, it remains a great challenge to measure the complex parameters online during the lipid fermentation process, which is nonlinear, multivariate, and characterized by strong coupling. As a type of AI technology, the artificial neural network model is a powerful tool for handling extremely complex problems, and it can be employed to develop a soft sensor to monitor the microbial lipid fermentation process of Y. lipolytica. In this study, we first analyzed and emphasized the volume of sodium hydroxide and dissolved oxygen concentration as central parameters of the fermentation process. Then, a soft sensor based on a four-input artificial neural network model was developed, in which the input variables were fermentation time, dissolved oxygen concentration, initial glucose concentration, and additional volume of sodium hydroxide. This provides the possibility of online monitoring of dry cell weight, glucose concentration, and lipid production with high accuracy, which can be extended to similar fermentation processes characterized by the addition of bases or acids, as well as changes of the dissolved oxygen concentration.     

Fermentation of cellulose to acetic acid by Clostridium lentocellum SG6: induction of sporulation and effect of buffering agent on acetic acid production

AIMS: To determine the growth, correlation between sporulation and acetic acid production and effect of buffering agent at high substrate cellulose concentrations of the strain Clostiridium lentocellum SG6. METHODS AND RESULTS: The strain SG6 was grown in cellulose mineral salt medium containing cellulose (Whatman No. 1 filter paper, Whatmore International Ltd., Maidstone, UK) or cellobiose. The strain fermented cellulose even after several transfers on cellobiose medium. The formation of endospores on third day onwards indicated the lowering of pH in the medium because of the formation of acetic acid. Maintaining the pH 7.2 at higher substrate concentrations resulted in increase of biomass, cellulose fermentation, acetic acid production, etc. CONCLUSIONS: The strain SG6, with its high fermentation yields and sporulating character can become a potential strain for acetic acid production and also as a probiotic strain in animal nutrition. SIGNIFICANCE AND IMPACT OF THE STUDY: The direct conversion of cellulosic biomass to acetic acid can eliminate expensive three-step saccharification, fermentation processes. The strain SG6 can ferment cellulose at high substrate concentrations.     

Closed-loop control of fed-batch cultures of recombinant Escherichia coli using on-line HPLC

This article describes a fully automated system for the on-line monitoring and closed-loop control of a fed-batch fermentation of recombinant Escherichia coli, and presents two case studies of its used in limiting production of unwanted byproducts such as acetic in fed-batch fermentations. The system had two components. The first components, on-line monitoring, comprised an aseptic sampling device, a microcentrifuge, and HPLC System. These instruments removed a Sample from a fermentor, spun it at high speed to separate solid and liquid components, and then automatically injected the supernatant onto an HPLC column for analysis. The second component consisted of control algorithms programmed using the LabView visual programming environment in a control computer that was linked via a remote components were linked so that results from the on-line HPLC were captured and used by the control algorithm was designed to demonstrate coarse feedback control to confirm the operability of the controller. The second case study showed how the system could be used in a more sophisticated feedings strategy providing fine control and limiting acetate concentration to a low level throughout the fermentation. (c) 1994 John Wiley & Sons, Inc.     

Ethanol production by Kluyveromyces marxianus IMB3 during growth on straw-supplemented whiskey distillery spent wash at 45 °C

The thermotolerant, ethanol-producing yeast strain, Kluyveromyces marxianus IMB3 was grown on media consisting of straw-supplemented distillery spent wash from The Old Bushmill's Distillery Co. Ltd., Bushmills, Co Antrim, Northern Ireland. Media were supplemented with cellulase activity and fermentations were carried out at 45?°C. When pulverized straw was used as substrate in this system at concentrations of 2, 4 and 6% (w/v), ethanol concentrations increased to maxima of 1.45, 2.2 and 3?g/l, respectively. Based on straw containing a maximum of 40% cellulose, these ethanol concentrations accounted for 36, 27 and 24% of the maximum theoretical yield, respectively. When the straw was pre-treated with NaOH and used in the spent wash containing system at concentrations of 2, 4 and 6% (w/v) ethanol, concentrations increased to maxima of 3, 6.2 and 10.5?g/l, respectively and these accounted for 75, 76 and 86% of the maximum theoretical yield. When these results are compared with previously published data relating to the use of straw in laboratory-based media, they suggest that whiskey distillery spent wash may provide an adequate medium for supplementation with complex carbohydrate and subsequent ethanol production in simultaneous saccharification and fermentation processes.     

Cell growth and extracellular enzyme synthesis in fermentations

The synthesis of extracellular enzymes by microorganisms frequently occurs under genetic control. A simple two-parameter model is developed describing the degree of repression or induction in fermentation media. The case of substrate utilization by an extracellular enzyme was analyzed for a vegetable oil-lipase-yeast system. It is shown that fatty acids released by the lipase may accumulate in the early stage of growth and exert an influence on the limiting after which relatively little repression or induction takes place. Expressions are also derived for growth and extracellular enzyme synthesis in single-and multistage continuous cultures. When the cells grow on a directly available soluble substrate, the specific enzyme synthesis is maximal at low dilution rates in the case of repression and at high dilution rates in the case of induction. If the substrate is not directly available, a single continuous stirred tank reactor stage may not be sufficient for efficient substrate utilization; for fermentation processes where an insoluble has to be broken down before the cells can assimilate it, a plug flow type fermentor rather than a mixed chemostat may prove more satisfactory.