Novel bioreactor internals for the cultivation of spore‐forming fungi in pellet form

This study introduced an automated long‐term fermentation process for fungals grown in pellet form. The goal was to reduce the overgrowth of bioreactor internals and sensors while better rheological properties in the fermentation broth, such as oxygen transfer and mixing time, can be achieved. Because this could not be accomplished with continuous culture and fed‐batch fermentation, repeated‐batch fermentation was implemented with the help of additional bioreactor internals (“sporulation supports”). This should capture some biomass during fermentation. After harvesting the suspended biomass, intermediate cleaning was performed using a cleaning device. The biomass retained on the sporulation support went through the sporulation phase. The spores were subsequently used as inocula for the next batch. The reason for this approach was that the retained pellets could otherwise cause problems (e.g., overgrowth on sensors) in subsequent batches because the fungus would then show undesirable hyphal growth. Various sporulation supports were tested for sufficient biomass fixation to start the next batch. A reproducible spore concentration within the range of the requirements could be achieved by adjusting the sporulation support (design and construction material), and an intermediate cleaning adapted to this.     

采用最小二乘支持向量机的青霉素发酵过程建模研究

生化过程通常是严重非线性和时变的复杂动态系统,而且重要过程参数缺少在线测量仪表,对其建立机理模型往往非常耗时和困难。采用最小二乘支持向量机(LS_SVM)并以Pensim仿真平台为例对青霉素发酵这一典型生化过程进行建模研究。给出了LS_SVM参数的调整策略和分析结果,建立了青霉素产物浓度、菌体浓度和底物浓度等重要过程变量的在线预报模型。仿真结果表明用LS_SVM建立的在线预报模型拟合误差小,推广性能好,可以作为发酵过程的进一步控制和优化的参考依据。     

Introducing process analytical technology (PAT) in filamentous cultivation process development: comparison of advanced online sensors for biomass measurement

The recent process analytical technology (PAT) initiative has put an increased focus on online sensors to generate process-relevant information in real time. Specifically for fermentation, however, introduction of online sensors is often far from straightforward, and online measurement of biomass is one of the best examples. The purpose of this study was therefore to compare the performance of various online biomass sensors, and secondly to demonstrate their use in early development of a filamentous cultivation process. Eight Streptomyces coelicolor fed-batch cultivations were run as part of process development in which the pH, the feeding strategy, and the medium composition were varied. The cultivations were monitored in situ using multi-wavelength fluorescence (MWF) spectroscopy, scanning dielectric (DE) spectroscopy, and turbidity measurements. In addition, we logged all of the classical cultivation data, such as the carbon dioxide evolution rate (CER) and the concentration of dissolved oxygen. Prediction models for the biomass concentrations were estimated on the basis of the individual sensors and on combinations of the sensors. The results showed that the more advanced sensors based on MWF and scanning DE spectroscopy did not offer any advantages over the simpler sensors based on dual frequency DE spectroscopy, turbidity, and CER measurements for prediction of biomass concentration. By combining CER, DE spectroscopy, and turbidity measurements, the prediction error was reduced to 1.5 g/l, corresponding to 6% of the covered biomass range. Moreover, by using multiple sensors it was possible to check the quality of the individual predictions and switch between the sensors in real time.     

Software sensors for biomass concentration in a SSC process using artificial neural networks and support vector machine

The lack of sensors for some relevant state variables in fermentation processes can be coped by developing appropriate software sensors. In this work, NARX-ANN, NARMAX-ANN, NARX-SVM and NARMAX-SVM models are compared when acting as software sensors of biomass concentration for a solid substrate cultivation (SSC) process. Results show that NARMAX-SVM outperforms the other models with an SMAPE index under 9 for a 20 % amplitude noise. In addition, NARMAX models perform better than NARX models under the same noise conditions because of their better predictive capabilities as they include prediction errors as inputs. In the case of perturbation of initial conditions of the autoregressive variable, NARX models exhibited better convergence capabilities. This work also confirms that a difficult to measure variable, like biomass concentration, can be estimated on-line from easy to measure variables like CO₂ and O₂ using an adequate software sensor based on computational intelligence techniques.     

On-line state estimation of biomass based on acid production in Zymomonas mobilis cultures

The concentrations of biomass, substrate and product are very important state variables of almost every bioprocess and generally unable to be measured directly in?situ due to the lack of reliable sensors. In this paper, an adaptive observer of the biomass concentration is proposed for an anaerobic fermentation process where only the measurement of the acid product is available on-line. The observer was tested to be effective by several experiments under various operating conditions. In this experimental system, an auto-sampling device was connected between the bioreactor for the fermentation of Zymomonas mobilis and a HPLC so that the concentrations of glucose and ethanol could be directly measured through such implementation.     

Monitoring of fed-batch <Emphasis Type="Italic">E. coli</Emphasis> fermentations with software sensors

Accurate monitoring and control of industrial bioprocess requires the knowledge of a great number of variables, being some of them not measurable with standard devices. To overcome this difficulty, software sensors can be used for on-line estimation of those variables and, therefore, its development is of paramount importance. An Asymptotic Observer was used for monitoring Escherichia coli fed-batch fermentations. Its performance was evaluated using simulated and experimental data. The results obtained showed that the observer was able to predict the biomass concentration profiles showing, however, less satisfactory results regarding the estimation of glucose and acetate concentrations. In comparison with the results obtained with an Extended Kalman Observer, the performance of the Asymptotic Observer in the fermentation monitoring was slightly better.     

Monitoring batch fermentations with an electronic tongue

An electronic tongue comprising 21 potentiometric chemical sensors with pattern recognition tools was used for the rapid off-line monitoring of batch Escherichia coli fermentations. The electronic tongue was capable of monitoring the changes in the media composition as the fermentation progressed, and could correlate this with an increase in biomass. The electronic tongue was also able to monitor the increase in organic acids, especially acetic acid, throughout the fermentation. This technique clearly shows promise as a rapid tool for fermentation monitoring.     

Aerial mycelia of Aspergillus oryzae accelerate α-amylase production in a model solid-state fermentation system

Aspergillus oryzae is commonly used in solid-state fermentation (SSF) and forms abundant aerial mycelia. Previously, we have shown that aerial mycelia are extremely important for the respiration of this fungus during growth on a wheat-flour model substrate. In this paper, we show that aerial mycelia of this fungus give a strong increase in fungal biomass and α-amylase production. Cultures of A. oryzae on wheat-flour model substrate produced twice the amounts of fungal biomass and α-amylase, when aerial mycelia were formed. Utilization of these findings in commercial solid-state fermenters requires further research; results from packed beds of grain indicate that aerial mycelia are of limited importance there. Probably, substrate pre-treatment and an increase in bed voidage are required.     

Flexible biorefinery for producing fermentation sugars, lignin and pulp from corn stover

A new biorefining process is presented that embodies green processing and sustainable development. In the spirit of a true biorefinery, the objective is to convert agricultural residues and other biomass feedstocks into value-added products such as fuel ethanol, dissolving pulp, and lignin for resin production. The continuous biomass fractionation process yields a liquid stream rich in hemicellulosic sugars, a lignin-rich liquid stream, and a solid cellulose stream. This paper generally discusses potential applications of the three streams and specifically provides results on the evaluation of the cellulose stream from corn stover as a source of fermentation sugars and specialty pulp. Enzymatic hydrolysis of this relatively pure cellulose stream requires significantly lower enzyme loadings because of minimal enzyme deactivation from nonspecific binding to lignin. A correlation was shown to exist between lignin removal efficiency and enzymatic digestibility. The cellulose produced was also demonstrated to be a suitable replacement for hardwood pulp, especially in the top ply of a linerboard. Also, the relatively pure nature of the cellulose renders it suitable as raw material for making dissolving pulp. This pulping approach has significantly smaller environmental footprint compared to the industry-standard kraft process because no sulfur- or chlorine-containing compounds are used. Although this option needs some minimal post-processing, it produces a higher value commodity than ethanol and, unlike ethanol, does not need extensive processing such as hydrolysis or fermentation. Potential use of low-molecular weight lignin as a raw material for wood adhesive production is discussed as well as its use as cement and feed binder. As a baseline application the hemicellulosic sugars captured in the hydrolyzate liquor can be used to produce ethanol, but potential utilization of xylose for xylitol fermentation is also feasible. Markets and values of these applications are juxtaposed with market penetration and saturation.     

基于近红外光谱实时监测乙醇发酵过程多组分参数

生物量、葡萄糖浓度和乙醇浓度是乙醇发酵过程的重要参数,传统的方法通常对发酵液取样作离线测量,不仅需要采用多种仪器进行测试分析,而且耗时耗力,成为实时过程调控和优化的障碍。文中针对这些重要过程参数提出了一个基于近红外光谱技术的原位实时检测方法。通过采用浸入式近红外光谱仪对发酵溶液进行原位测量,基于多输出最小二乘支持向量机回归(MLS-SVR)方法建立了利用近红外光谱同时分析葡萄糖浓度、生物量和乙醇浓度的多输出预测模型。实验结果表明,该方法能实时准确地检测乙醇发酵过程中的葡萄糖浓度、生物量和乙醇浓度,而且相对于现有的偏最小二乘法(PLS)分别对各组分建模和预测,能明显提高测量准确性和可靠性。     

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.     

Fehlermöglichkeiten der Gelöstsauerstoffmessung beim Betrieb von Bioreaktoren

A review of errors, which can influence the measured data of electrochemical oxygen sensors (OS) in fermentation technique is presented. The specifities of various sensor constructions are pointed out. References are given for selection of sensors to application in fermenters. Influences on the measured values can take place by fermentation conditions, arrangement of sensors in the fermenter and composition of the fermentation broth. The oxygen measurement in the multi-phase system of fermentation fluids can cause a remarkable deviation of the measured values to the real ones. Practical hints are given for use, calibration and sterilization of OS. Restricting conditions for measurements with this sensors are enumerated.     

Evaluation of the xylan breakdown potential of eight mesophilic endoxylanases

In biomass degradation using simultaneous saccharification and fermentation (SSF), there is a need for efficient biomass degrading enzymes that can work at lower temperatures suitable for yeast fermentation. As xylan is an important lignocellulosic biomass constituent, this study aimed at investigating the possible differences in xylan breakdown potential of endoxylanases using eight different endoxylanases at conditions relevant for SSF. Both solubilising and degrading capacities of the endoxylanases were investigated using water-insoluble and water-soluble oat spelt xylan as model substrates for biomass xylan. Results showed that selecting for combinations of endoxylanases that are efficient at solubilising xylan on the one hand and degrading it to large extent on the other hand, coupled to high specific activities, seems the best option for complete xylan breakdown in lignocellulosic biomass conversion using SSF.     

Nonlinear estimation of specific growth rate for aerobic fermentation processes

The specific growth rate of the biomass, a very important parameter of almost every fermentation process, cannot be measured directly or estimated from related variables, as the concentrations of biomass, substrates, or products, due to the lack of reliable and cheap sensors. In this article a stable adaptive estimator of the specific growth rate is designed for those aerobic processes where the measurement of the oxygen uptake rate is available on-line. This particular approach can be applied also for other reaction rates if the model of the process satisfies some very general assumptions, which make the dynamics of the measured reaction rate a nonlinear function only of two unknown parameters, the specific growth rate and its time derivative. With respect to a previous similar approach, the new estimator has one additional parameter and a different nonlinear structure. From the analysis of the dynamics of the estimation error, a tuning criterion is derived, by which the two different algorithms can be compared under similar conditions. Simulation results show a good performance of both estimators for various kind of processes and disturbances. (c) 1995 John Wiley & Sons, Inc.     

Simultaneous saccharification and fermentation of pretreated biomass: Improving mass balance closure

Summary The successful implementation of simultaneous saccharification and fermentation (SSF) technology for biomass conversion to ethanol requires competent analysis of complex biomass process streams, often obtained at extremes of pH. In this study, optimal conditions for handling biomass samples recovered from acid and alkaline pretreatments prior to traditional compositional analysis were developed. Methods for processing slurries from SSF were also determined. In both cases, a mixed wastepaper feedstock was used to test improved handling procedures and to document recommended performance.     

Adaptive steady-state optimization of biomass productivity in continuous fermentors

An adaptive steady-state optimization algorithm is presented and applied to the problem of optimizing the production of biomass in continuous fermentation processes. The algorithm requires no modeling information but is based on an on-line identified linear model, locates the optimum dilution rate, and maintains the chemostat at its optimum operating condition at all times. The behavior of the algorithm is tested against a dynamic model of a chemostat that incorporates metabolic time delay, and it is shown that large disturbances in the subtrate feed concentration and the specific growth rate, causing a shift in the optimum, are handled well. The developed algorithm is also used to drive a methylotroph single-cell production process to its optimum.     

Quantifying Actual and Theoretical Ethanol Yields for Switchgrass Strains Using NIRS Analyses

Quantifying actual and theoretical ethanol yields from biomass conversion processes such as simultanteous saccharification and fermentation (SSF) requires expensive, complex fermentation assays, and extensive compositional analyses of the biomass sample. Near-infrared reflectance spectroscopy (NIRS) is a non-destructive technology that can be used to obtain rapid, low-cost, high-throughput, and accurate estimates of agricultural product composition. In this study, broad-based NIRS calibrations were developed for switchgrass biomass that can be used to estimate over 20 components including cell wall and soluble sugars and also ethanol production and pentose sugars released as measured using a laboratory SSF procedure. With this information, an additional 13 complex feedstock traits can be determined including theoretical and actual ethanol yields from hexose fermentation. The NIRS calibrations were used to estimate feedstock composition and conversion information for biomass samples from a multi-year switchgrass (Panicum virgatum L.) biomass cultivar evaluation trial. There were significant differences among switchgrass strains for all biomass conversion and composition traits including actual ethanol yields, ETOHL (L Mg^?1) and theoretical ethanol yields, ETOHTL (L Mg^?1), based on cell wall and non-cell wall composition NIRS analyses. ETOHL means ranged from 98 to 115 L Mg^?1 while ETOHTL means ranged from 203 to 222 L Mg^?1. Because of differences in both biomass yields and conversion efficiency, there were significant differences among strains for both actual (2,534?C3,720 L ha^?1) and theoretical (4,878?C7,888 L ha^?1) ethanol production per hectare. It should be feasible to improve ethanol yields per hectare by improving both biomass yield and conversion efficiency by using NIRS analyses to quantify differences among cultivars and management practices.     

Process adapted calibration improves fluorometric pH sensor precision in sophisticated fermentation processes

Miniaturization and automation have become increasingly popular in bioprocess development in recent years, enabling rapid high‐throughput screening and optimization of process conditions. In addition, advances in the bioprocessing industry have led to increasingly complex process designs, such as pH and temperature shifts, in microbial fed‐batch fermentations for optimal soluble protein expression in a range of hosts. However, in order to develop an accurate scale‐down model for bioprocess screening and optimization, small‐scale bioreactors must be able to accurately reproduce these complex process designs. Monitoring methods, such as fluorometric‐based pH sensors, provide elegant solutions for the miniaturization of bioreactors, however, previous research suggests that the intrinsic fluorescence of biomass alters the sigmoidal calibration curve of fluorometric pH sensors, leading to inaccurate pH control. In this article, we present results investigating the impact of biomass on the accuracy of a commercially available fluorometric pH sensor. Subsequently, we present our calibration methodology for more precise online measurement and provide recommendations for improved pH control in sophisticated fermentation processes.     

Sensor systems,electronic tongues and electronic noses,for the monitoring of biotechnological processes

Production of biofuel is based on the conversion by microorganisms of complex organic substrates into the methane or ethanol, which are consequently used as energy sources. Real time monitoring of the fermented media composition is of paramount for the effectiveness of the whole process. However, despite the fact that products worth billions of dollars are produced through fermentation processes annually, analytical instruments used for these processes’ monitoring remain relatively primitive. Established laboratory techniques produce exhaustive information about media composition but analysis is often quite time-consuming, expensive, requires skilled personnel and hardly can be automated. Lack of on-line sensors for the fermentation monitoring is commonly stressed in the literature. One of the techniques particularly suitable for this purpose is chemical sensors. Such features as low prices, relatively simple instrumentation, minimal sample preparation and easy automation of measurements make chemical sensors an attractive tool for industrial process control. However, practical use of chemical sensors in complex media is often hindered by their insufficient selectivity. For example, only pH and oxygen probes are routinely used in bio-reactors. One of the emerging approaches permitting to overcome the selectivity problems is the use of systems instead of discrete sensors. Such systems for liquid and gas analysis were named electronic tongues and electronic noses correspondingly. They are capable to perform both quantitative analysis (components’ concentrations) and classification or recognition of multicomponent media. This review presents recent achievements in the R&D and applications of electronic tongues and noses to the monitoring of biotechnological processes. JIMB-2008: BioEnergy—Special issue.     

Thermophilic,lignocellulolytic bacteria for ethanol production: current state and perspectives

Lignocellulosic biomass contains a variety of carbohydrates, and their conversion into ethanol by fermentation requires an efficient microbial platform to achieve high yield, productivity, and final titer of ethanol. In recent years, growing attention has been devoted to the development of cellulolytic and saccharolytic thermophilic bacteria for lignocellulosic ethanol production because of their unique properties. First of all, thermophilic bacteria possess unique cellulolytic and hemicellulolytic systems and are considered as potential sources of highly active and thermostable enzymes for efficient biomass hydrolysis. Secondly, thermophilic bacteria ferment a broad range of carbohydrates into ethanol, and some of them display potential for ethanologenic fermentation at high yield. Thirdly, the establishment of the genetic tools for thermophilic bacteria has allowed metabolic engineering, in particular with emphasis on improving ethanol yield, and this facilitates their employment for ethanol production. Finally, different processes for second-generation ethanol production based on thermophilic bacteria have been proposed with the aim to achieve cost-competitive processes. However, thermophilic bacteria exhibit an inherent low tolerance to ethanol and inhibitors in the pretreated biomass, and this is at present the greatest barrier to their industrial application. Further improvement of the properties of thermophilic bacteria, together with the optimization production processes, is equally important for achieving a realistic industrial ethanol production.