Some practical aspects of computer applications in a fermentor hall

The use of computers in a fermentation pilot plant is described from a practical point of view. The aim is not the application of a computer to a single special process but a general application of computers to prepare and present data for the following analysis of fermentation processes. The hardware is normally bought from computer manufacturers, but some additional installations are useful. Application software has to be developed by the biotechnologist, therefore the software structure is the most important part of the computer application. Data storage is divided into three parts: short-time memory, long-time storage, and a medium memory mainly to be used in process analyses and process control. Four types of programs are used: main schedule tasks, low-priority on-line tasks, sense-switch routine, and different off-line programs. A table of all programs is presented, the main schedule task is described in detail to demonstrate the software structure.     

α-Amylase,Limit Dextrinase,and α-Glucosidase Enzymes in Barley and Malt

Abstract

A parallel discussion is presented of recent developments in fermentation monitoring and control in both research institutes and in industry. The discussion is based around the areas of measurement (on-line and off-line), data conditioning and analysis, modeling, fault analysis, and control. Recent progress in industrial fermentation monitoring and control is used as a guide to identify potential areas of research that might have a most rapid and direct impact on industrial fermentation operation.     

Thermal profiling for parallel on-line monitoring of biomass growth in miniature stirred bioreactors

Recently we have described the design and operation of a miniature bioreactor system in which 4-16 fermentations can be performed (Gill et al., Biochem Eng J 39:164-176, 2008). Here we report on the use of thermal profiling techniques for parallel on-line monitoring of cell growth in these bioreactors based on the natural heat generated by microbial culture. Results show that the integrated heat profile during E. coli TOP10 pQR239 fermentations followed the same pattern as off-line optical density (OD) measurements. The maximum specific growth rates calculated from off-line OD and on-line thermal profiling data were in good agreement, at 0.66+/-0.04 and 0.69+/-0.05 h(-1) respectively. The combination of a parallel miniature bioreactor system with a non-invasive on-line technique for estimation of culture kinetic parameters provides a valuable approach for the rapid optimisation of microbial fermentation processes.     

Applying neural networks as software sensors for enzyme engineering

The on-line control of enzyme-production processes is difficult, owing to the uncertainties typical of biological systems and to the lack of suitable on-line sensors for key process variables. For example, intelligent methods to predict the end point of fermentation could be of great economic value. Computer-assisted control based on artificial-neural-network models offers a novel solution in such situations. Well-trained feedforward-backpropagation neural networks can be used as software sensors in enzyme-process control; their performance can be affected by a number of factors.     

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.     

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.     

A novel method for the on-line analysis of fermentation broth using a sampling device,microcentrifuge and HPLC

Summary This paper describes a novel system for on-line sampling and analysis of whole broth from a fermenter. The system comprises a steam sterilisable sampling device, high speed microcentrifuge and HPLC. We present results characterising the separation efficiency of the microcentrifuge under different conditions, and illustrate the system with glucose and acetate data from an Escherichia coli fermentation using the system. The on-line measurements have been confirmed by off-line analysis.     

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.     

Neural networks for the optimization of crude oil blending

Crude oil blending is an important unit in petroleum refining industry. Many blend automation systems use real-time optimizer (RTO), which apply current process information to update the model and predict the optimal operating policy. The key unites of the conventional RTO are on-line analyzers. Sometimes oil fields cannot apply these analyzers. In this paper, we propose an off-line optimization technique to overcome the main drawback of RTO. We use the history data to approximate the output of the on-line analyzers, then the desired optimal inlet flow rates are calculated by the optimization technique. After this off-line optimization, the inlet flow rates are used for on-line control, for example PID control, which forces the flow rate to follow the desired inlet flow rates. Neural networks are applied to model the blending process from the history data. The new optimization is carried out via the neural model. The contributions of this paper are: (1) Stable learning for the discrete-time multilayer neural network is proposed. (2) Sensitivity analysis of the neural optimization is given. (3) Real data of a oil field is used to show effectiveness of the proposed method.     

基于过程参数相关分析的鸟苷发酵过程优化

本文分析鸟苷产生菌枯草芽孢杆菌(Bacilus subtilis)在50L多参数自控发酵罐上的发酵过程特点,基于多种在线及离线参数的检测,通过相关分析将生理调控的工艺参数和生物合成过程中的代谢流分布相联系,发现了发酵过程中的代谢流向糖酵解和TCA循环的迁移,并初步分析了产生代谢流迁移的原因,在此基础上优化发酵过程使产苷水平稳定在30g/L。     

Implementation of a thermal biosensor in a process environment: on-line monitoring of penicillin V in production-scale fermentations.

The production of penicillin V was monitored in 0.5 m3 and 160 m3 bioreactors. The thermal biosensor was an enzyme thermistor modified for split-flow analysis. The heat signal generated in the enzyme column was corrected for any nonspecific heat with the use of an identical but inactive reference column. The on-line monitoring was performed in the fermentation pilot plant and in a fermentation plant of Novo Nordisk A/S. Immobilized beta-lactamase was used to monitor three consecutive 0.5 m3 penicillin fermentations. Broth samples were continuously filtered through a tangential flow filtration unit in a sterile external loop. The on-line penicillin V values were 10% higher than those obtained by off-line HPLC analysis. Alternatively a polypropylene filtration probe was inserted into a 160 m3 bioreactor and samples were withdrawn at 0.5 ml/min. The same experiments were repeated with purified and immobilized penicillin V acylase. The on-line penicillin V values obtained with this enzyme correlated very well with those from HPLC analysis. The on-line monitoring was controlled and analysed by a software program written in Labtech Notebook.     

Neural network predictive control by MIMS monitored 2,3-butanediol fermentation by Klebsiella oxytoca

With the aid of a membrane introduction mass spectrometer (MIMS), the major product 2,3-butanediol (2,3-BDL) as well as the other metabolites from the fermentation carried by Klebsiella oxytoca can be measured on-line simultaneously. A backpropagation neural network (BPN) being recognized with superior mapping ability was applied to this control study. This neural network adaptive control differs from those conventional controls for fermentation systems in which the measurements of cell mass and glucose are not included in the network model. It is only the measured product concentrations from the MIMS that are involved. Oxygen composition was chosen to be the control variable for this fermentation system. Oxygen composition was directly correlated to the measured product concentrations in the controller model. A two-dimensional (number of input nodes by number of data sets) moving window for on-line, dynamic learning of this fermentation system was applied. The input nodes of the network were also properly selected. Number of the training data sets for obtaining better control results was also determined empirically. Two control structures for this 2,3-BDL fermentation are discussed and compared in this work. The effect from adding time delay element to the network controller was also investigated.     

Metabolism analysis and on-line physiological state diagnosis of acetone-butanol fermentation

Fermentation equations for acetone-butanol (AB) were applied in a metabolic analysis of the reaction network under various conditions; that is, at different pHs and a high NADH2 turnover rate using methyl viologen, in a Clostridium acetobutylicum culture. The results disclosed variations in the pattern of rate changes that reflected changes in the physiological state. A linear relationship was found to exist between NADH2 generation and butanol production rate. By coupling an automated measurement system with the fermentation model, on-line estimation of the culture state was accomplished. Based on the AB fermentation model, new parameters were defined for on-line diagnosis of the physiological state and determination of the best timing for amplifying NADH2 generation by the addition of methyl viologen to obtain a high level of butanol productivity. A potential means of achieving optimal control for a high level of solvent production, involving the correlation of certain rates, is proposed.     

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.     

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.     

Model identification and physiological control of xylitol production using Debaryomyces hansenii

The control of xylitol production from xylose-grown Debaryomyces hansenii yeast, which is a very complex biological process, usually requires accurate and demanding analytical HPLC measurements. For this reason, estimating relationships of the main variables of the fermentation process-concentration of xylitol, biomass and xylose-are suggested and studied in this article. The volume of added base for maintaining pH at the prescribed level has been shown to be important for approximate assessment of the biomass concentration and, therefore, for all estimation relationships. Furthermore, replacement of expensive off-line HPLC analyses of xylose by an on-line determined respiratory quotient RQ for control purposes is discussed. On the basis of this, physiological control of xylitol production which takes advantage of on-line classification of the different metabolic states of the culture from easily and cheaply measured variables, has been developed. Data and knowledge obtained from several experiments were evaluated for this reason and results are presented.     

On-line biomass monitoring in bench-scale stirred bioreactors using parts of a liquid chromatography system

A cell density monitor, comprising parts of a liquid chromatography system, was adapted for on-line real-time measurement of bacterial cell density up to 75 g l^–1. The device dilutes the sample containing cells and measures the absorbancy at 280 nm. This detector gives an excellent correlation with off-line measurements, good reproducibility, a low limit of detection (3.5 mg l^–1), and becomes a low cost alternative for fermentation monitoring in small stirred bioreactors.     

Monitoring of ethanol during fermentation of a lignocellulose hydrolysate by on-line microdialysis sampling, column liquid chromatography, and an alcohol biosensor

During a 70-h fermentation of a lignocellulose hydrolysate, the ethanol produced was monitored on-line using a microdialysis probe as an in situ sampling device. The dialysate components were then separated in a column liquid chromatographic system and the ethanol was selectively detected by an amperometric alcohol biosensor. The result was compared with two off-line analysis methods: one chromatographic method with refractive index (RI) detection and one enzymatic method based on spectrophotometric detection. The two methods base on enzymes were shown to give lower values than the chromatographic method based on RI detection, which is discussed n terms of selectivity. The investigated on-line setup was found to be a flexible system for monitoring of fermentations, allowing a sampling frequency of at least 12 h(-1) and with a delay between sampling and detection of less than 5 min. (c) 1994 John Wiley & Sons, Inc.     

重组毕赤酵母表达工程植酸酶发酵过渡相参数相关分析

微生物发酵是一个涉及不同尺度的互相关联的复杂生物系统的过程 ,将重组毕赤酵母表达工程植酸酶过渡相的在线和离线参数进行了相关分析研究。通过对发酵过程的在线细胞代谢生理参数 (OUR)和环境参数 (DO)的变化进行相关分析表明 :甘油和葡萄糖碳源对AOX合成的阻遏强度不同 ,葡萄糖的阻遏性明显强于甘油 ,相对于醇氧化酶启动子 ,葡萄糖为强阻遏性底物。根据甲醇代谢途径关键酶酶活性变化 ,推测出各代谢途径流量分布的变化 ,即甲醇诱导后糖酵解途径和三羧酸循环途径代谢流比例下降 ,而磷酸戊糖途径中代谢流通量上升 ,甲醇完全氧化代谢流成为主要代谢流 ,与过渡相在线参数pH、OUR(CER)和RQ等相关分析的甲醇代谢途径的变化结果一致。此外 ,建立了生产过程在线控制与分析的标准 :当OUR和CER逐渐增大 ,则可判断甲醇已被利用和启动子已被甲醇成功诱导 ,即工程植酸酶开始启动表达.