Fed-Batch Fermentation for Spinosad Production in an Improved Reactor

As a kind of aerobic bacteria, Saccharopolyspora spinosa exhibits a high demand for oxygen. In the fermentation process, the methods of increasing ventilation and improving agitation speed are usually adopted to achieve higher values of dissolved oxygen. These methods decrease the efficiency of spinosad biosynthesis. In this study, an improved reactor was designed to solve these problems. The exhaust gas reflux device, impellers, and baffles were improved. Furthermore, we established the kinetic models for the cell growth, substrate consumption and spinosad generation in batch fermentation process. The simulation results were in good agreement with the experimental data. Spinosad production reached 583.86 mg/L after employing the suitable feeding strategy by fed-batch fermentation in the improved reactor, whereas it was only 157.01 mg/L before optimization. The method described can provide insight to strengthen spinosad production and can be extended to the culturing process of filamentous aerobic bacteria. © 2017 Tianjin University and Springer-Verlag Berlin Heidelberg

Production of Ammonium Lactate by Fed-batch Fermentation of Rhizopus oryzaefrom Corncob Hydrolysate

L-(+)-Lactic acid production from corncob hydrolysate as a cheap carbohydrate source by fed-batch fermentation of Rhizopus oryzaeHZS6 was studied. After 96 h of fermentation in a 5 L fermentor, the final concentration of ammonium L-(+)-lactate, average productivity(based on initial xylose concentration) and maximum dry cell weight were 132.4 g/L, 1.38 g/(L·h), and 8.9 g/L respectively. The optical purity of L-(+)-lactate was 98.8%.

Strategies for Optimizing Feed Rate of Fed-Batch Yeast Fermentation by Fuzzy-Neural Network

In this paper,a novel fuzzy neural network model,in which an adjustable fuzzy sub-space was designed by uniform design,has been established and used in fed-batch yeast fermentationas an example.A brand-new optimization sub-network with special structure has been built andgenetic algorithm,guaranteeing the optimization in overall space,is introduced for the feed rateoptimization.On the basis of the model network,the optimal substrate concentration and theoptimal amount of fed-batch at different periods have been studied,aided with the optimizationnetwork and the genetic algorithm separately.The above results can be used as a basis for theestablishment of a fuzzy neural network controller.

Improved elastase production by Bacillus sp. EL31410—further optimization and kinetics studies of culture medium for batch fermentation

An efficient culture medium producing a bacterial elastase with high yields was developed further following preliminary studies by means of response surface method. Central composite design (CCD) and response surface method-ology were applied to optimize the medium constituents. A central composite design was used to explain the combined effect of three medium constituents, viz, glucose, K2HPO4, MgSO47H2O. The strain produced more elastase in the completely optimized medium, as compared with the partially optimized medium. The fitted model of the second model, as per RSM, showed that glucose was 7.4 g/100 ml, casein 1.13 g/100 ml, corn steep flour 0.616 g/100 ml, K2HPO4 0.206 g/100 ml and MgSO47H2O 0.034 g/100 ml. The fermentation kinetics of these two culture media in the flask experiments were analyzed. It was found that the highest elastase productivity occurred at 54 hours. Higher glucose concentration had inhibitory effect on elastase production. At the same time, we observed that the glucose consumption rate was slow in the completely optimized medium, which can explain the lag period of the highest elastase production. Some metal ions and surfactant additives also affected elastase production and cell growth.

Mass Transfer, Gas Holdup, and Kinetic Models of Batch and Continuous Fermentation in a Novel Rectangular Dynamic Membrane Airlift Bioreactor

Compared with conventional cylinder airlift bioreactors(CCABs)that produce coarse bubbles,a novel rectangular dynamic membrane airlift bioreactor(RDMAB)developed in our lab produces fine bubbles to enhance the volumetric oxygen mass transfer coefficient(k_(L)a)and gas holdup,as well as improve the bioprocess in a bioreactor.In this study,we compared mass transfer,gas holdup,and batch and con-tinuous fermentation for RNA production in CCAB and RDMAB.In addition,unstructured kinetic models for microbial growth,substrate utilization,and RNA formation were established.In batch fermentation,biomass,RNA yield,and substrate utilization in the RDMAB were higher than those in the CCAB,which indicates that dynamic membrane aeration produced a high k_(L)a by fine bubbles;a higher k_(L)a is more bene-ficial to aerobic fermentation.The starting time of continuous fermentation in the RDMAB was 20 h ear-lier than that in the CCAB,which greatly improved the biological process.During continuous fermentation,maintaining the same dissolved oxygen level and a constant dilution rate,the biomass accumulation and RNA concentration in the RDMAB were 9.71% and 11.15% higher than those in the CCAB,respectively.Finally,the dilution rate of RDMAB was 16.7% higher than that of CCAB during con-tinuous fermentation while maintaining the same air aeration.In summary,RDMAB is more suitable for continuous fermentation processes.Developing new aeration and structural geometry in airlift bioreac-tors to enhance k_(L)a and gas holdup is becoming increasingly important to improve bioprocesses in a bioreactor.

A novel aeration strategy in repeated-batch fermentation for efficient ethanol production from sweet sorghum juice

To improve the efficiency of ethanol production in a batch fermentation from sweet sorghum juice under a very high gravity(VHG)condition(~290 g/L of total sugar)by Saccharomyces cerevisiae NP01,repeatedbatch fermentation under an aerated condition(2.5 vvm for the first 4 h during every cycle)was done in a5-L fermenter.The average ethanol concentration(P),productivity(Qp)and yield(Yp/s)for five successive cycles were 112.31 g/L,1.55 g/L·h^-1 and 0.44,respectively with 80.97%sugar consumption.To complete sugar consumption,the total sugar of the juice was reduced to a high gravity(HG)level(~240 g/L).The results showed that yeast extract was not necessary for ethanol production,and aeration during every other cycle i.e.,alternating cycles,was sufficient to promote both yeast growth and ethanol production.The average P,Qpand Yp/svalues for eight successive cycles with aeration during alternating cycles were97.58 g/L,1.98 g/Láh and 0.41,respectively with 91.21%sugar consumption.The total fatty acids in the yeast cells under the aerated condition were^50%higher than without aeration,irrespective the initial sugar concentration,whereas the ergosterol contents under aeration condition were^29%to 49%higher than those without aeration.

Establishment of Kinetics Models for Batch Fermentation Process of β-mannase with Bacillus licheniformis HDYM-04

In order to improve the yield of β-mannase and to investigate the rules of fermentation production, a high-yield β-mannase producing strain, Bacillus licheniformis HDYM-04, was used to investigate the kinetics models based on the optimal fermentation conditions： HDYM-04 strain was fermented at 37℃ for 30 h with agitation speed at 300 r/min and aeration rate at 3 L/min in a 5 L fermenter, the initial addition amount of konjac flour was 2%（w/v）, the initial pH of medium was 8.0, and the inoculum concentration was 6.7%（v/v）. Three batch fermentation kinetic models were established （cell growth kinetic model, substrate consumption kinetic model, product formation kinetic model） bases on Logistic and Luedeking-Piret equations. To be specific, cell growth kinetic model was dX/dt =0.431X （1- X/ 15.522 ）, substrate consumption kinetic model was -ds/dt =1.11 dX/dt ＋0.000 2 dP/dt ＋0.000 8X, and product formation kinetic model was dP/dt=133.1 dX ＋222.87X. The correlation coefficients R^2 of the three equations were 0.990 21, 0.989 08 and 0.988 12, respectively, which indicated a good correlation between experimental values and models. Therefore, the three equations could be used to describe the processes of cell growth, enzyme synthesis and substrate consumption during batch fermentation using B. licheniformis strain HDYM-04. The establishment of batch fermentation kinetic models （cell growth kinetic model, substrate depletion kinetic model, product formation kinetic model） could lay the theoretical foundation and provide practical reference for the applica- tion of HDYM-04 in fermentation industry.

Principles and Case Studies of Fed Batch Fermentation and Continuous Fermentation

Modern fermentation processes include a variety of fermentation methods,such as fed batch fermentation and continuous fermentation.This paper will focus on the principles and case studies of these two methods.Fed batch fermentation originates from fractionation fermentation with closed culture and adjustment of the pH value of the carbon source,to which the process of feeding the carbon source to the cell culture in a controlled manner has been added.This type of fermentation is more commonly used compared to the other.Continuous fermentation is also a closed fermentation system,which can operate without restrictions by continuous or intermittent addition of fresh nutrient media to the fermenter;however,it is susceptible to contamination by stray bacteria and metabolic inconvenience.

Batch and fed-batch production of butyric acid by Clostridium butyricum ZJUCB

The production of butyric acid by Clostridium butyricum ZJUCB at various pH values was investigated. In order to study the effect of pH on cell growth, butyric acid biosynthesis and reducing sugar consumption, different cultivation pH values ranging from 6.0 to 7.5 were evaluated in 5-L bioreactor. In controlled pH batch fermentation, the optimum pH for cell growth and butyric acid production was 6.5 with a cell yield of 3.65 g/L and butyric acid yield of 12.25 g/L. Based on these results, this study then compared batch and fed-batch fermentation of butyric acid production at pH 6.5. Maximum value (16.74 g/L) of butyric acid concentration was obtained in fed-batch fermentation compared to 12.25 g/L in batch fermentation. It was concluded that culti- vation under fed-batch fermentation mode could enhance butyric acid production significantly (P<0.01) by C. butyricum ZJUCB.

An Improved Adaptive Multi-way Principal Component Analysis for Monitoring Streptomycin Fermentation Process

Multi-way principal component analysis (MPCA) had been successfully applied to monitoring the batch and semi-batch process in most chemical industry. An improved MPCA approach, step-by-step adaptive MPCA (SAMPCA), using the process variable trajectories to monitoring the batch process is presented in this paper. It does not need to estimate or fill in the unknown part of the process variable trajectory deviation from the current time until the end. The approach is based on a MPCA method that processes the data in a sequential and adaptive manner. The adaptive rate is easily controlled through a forgetting factor that controls the weight of past data in a summation. This algorithm is used to evaluate the industrial streptomycin fermentation process data and is compared with the traditional MPCA. The results show that the method is more advantageous than MPCA, especially when monitoring multi-stage batch process where the latent vector structure can change at several points during the batch.

In-depth observations of fermentative hydrogen production from liquid swine manure using an anaerobic sequencing batch reactor

In this study,experiments were designed to reveal in-depth information of the effect of pH and hydraulic retention time（HRT）on biohydrogen fermentation from liquid swine manure supplemented with glucose using an Anaerobic Sequencing Batch Reactor（ASBR）System.Five values of HRT（8,12,16,20,and 24 h）were first tested and the best HRT determined was further studied at five p H levels（4.4,4.7,5.0,5.3,and 5.6）.The results showed that for HRT 24 h,there was a dividing H2 content（around 37%）related to the total biogas production rate for the ASBR System running at p H 5.0.When the H2 content went beyond 37%,an appreciable decline in biogas production rate was observed,implying that there might exist an H2 content limit in the biogas.For other HRTs（8 through 20 h）,an average H2 content of 42%could be achieved.In the second experiment（HRT 12 h）,the highest H2 content（35%）in the biogas was found to be associated with p H 5.0.The upswing of p H from 5.0 to 5.6 had a significantly more impact on biogas H2 content than the downswing of p H from5.0 to 4.3.The results also indicated good linear relationships of biogas and H2 production rates with HRT（r=0.9971 and0.9967,respectively）.Since the optimal ASBR operating conditions were different for the biogas/H2 production rates and the H2 yield,a compromised combination of the running parameters was determined to be HRT 12 h and pH 5.0 in order to achieve good biogas/H2 productions.

Breeding of Coenzyme Q_(10) Produced Strain by Low-Energy Ion Implantation and Optimization of Coenzyme Q_(10) Fermentation

In order to increase the production efficiency of coenzyme Q10, the original strain Agrobacterium tumefaciens ATCC 4452 was mutated by means of Nitrogen ions implantation. A mutant strain, ATX 12, with high contents of coenzyme Q10 was selected. Subsequently, the conditions such as carbohydrate concentration, nitrogen source concentration, inoculum＇s size, seed age, aeration and temperature which might affect the production of CoQ10 were investigated in detail. Under optimal conditions, the maximum concentration of the intracellular CoQ10 reached 200.3 mg/L after 80 h fed-batch fermentation, about 245% increasing in CoQ10 production after ion implantation, compared to the original strain.

An Approach to Continuous Approximation of Pareto Front Using Geometric Support Vector Regression for Multi-objective Optimization of Fermentation Process

The approaches to discrete approximation of Pareto front using multi-objective evolutionary algorithms have the problems of heavy computation burden, long running time and missing Pareto optimal points. In order to overcome these problems, an approach to continuous approximation of Pareto front using geometric support vector regression is presented. The regression model of the small size approximate discrete Pareto front is constructed by geometric support vector regression modeling and is described as the approximate continuous Pareto front. In the process of geometric support vector regression modeling, considering the distribution characteristic of Pareto optimal points, the separable augmented training sample sets are constructed by shifting original training sample points along multiple coordinated axes. Besides, an interactive decision-making(DM)procedure, in which the continuous approximation of Pareto front and decision-making is performed interactively, is designed for improving the accuracy of the preferred Pareto optimal point. The correctness of the continuous approximation of Pareto front is demonstrated with a typical multi-objective optimization problem. In addition,combined with the interactive decision-making procedure, the continuous approximation of Pareto front is applied in the multi-objective optimization for an industrial fed-batch yeast fermentation process. The experimental results show that the generated approximate continuous Pareto front has good accuracy and completeness. Compared with the multi-objective evolutionary algorithm with large size population, a more accurate preferred Pareto optimal point can be obtained from the approximate continuous Pareto front with less computation and shorter running time. The operation strategy corresponding to the final preferred Pareto optimal point generated by the interactive DM procedure can improve the production indexes of the fermentation process effectively.

Learning control of fermentation process with an improved DHP algorithm

Control of the fed-batch ethanol fermentation processes to produce maximum product ethanol is one of the key issues in the bioreactor system.However,ethanol fermentation processes exhibit complex behavior and nonlinear dynamics with respect to the cell mass,substrate,feed-rate,etc.An improved dual heuristic programming algorithm based on the least squares temporal difference with gradient correction(LSTDC) algorithm(LSTDC-DHP) is proposed to solve the learning control problem of a fed-batch ethanol fermentation process.As a new algorithm of adaptive critic designs,LSTDC-DHP is used to realize online learning control of chemical dynamical plants,where LSTDC is commonly employed to approximate the value functions.Application of the LSTDC-DHP algorithm to ethanol fermentation process can realize efficient online learning control in continuous spaces.Simulation results demonstrate the effectiveness of LSTDC-DHP,and show that LSTDC-DHP can obtain the near-optimal feed rate trajectory faster than other-based algorithms.

油脂酵母Trichosporon fermentans HWZ004的分批补料法高密度培养

为提高发酵性丝孢酵母Trichosporon fermentans HWZ004发酵产油脂的能力,采用分批补料的培养方式对其进行高密度培养,考察了初始糖浓度对发酵性丝孢酵母生长及油脂积累的影响,确定初始糖浓度为100 g/L,在该浓度下Trichosporon fermentans HWZ004可获得较高的生物量及油脂产量,且不存在底物抑制现象;然后,在5 L发酵罐中进行分批补料培养,发酵132h后,Trichosporon fermentans HWZ004的生物量、油脂含量及油脂生产强度分别为102g/L、48%和0.37g/(L·h).气相色谱分析结果表明,所得油脂的脂肪酸组成主要为硬脂酸、棕榈酸、油酸、亚油酸,不饱和脂肪酸含量达65%以上,适用于生物柴油的生产.

Monitoring and Fault Diagnosis for Batch Process Based on Feature Extract in Fisher Subspace

Multivariate statistical process control methods have been widely used in biochemical industries. Batch process is usually monitored by the method of multi-way principal component analysis (MPCA). In this article, a new batch process monitoring and fault diagnosis method based on feature extract in Fisher subspace is proposed.The feature vector and the feature direction are extracted by projecting the high-dimension process data onto the low-dimension Fisher space. The similarity of feature vector between the current and the reference batch is calculated for on-line process monitoring and the contribution plot of weights in feature direction is calculated for fault diagnosis. The approach overcomes the need for estimating or tilling in the unknown portion of the process variables trajectories from the current time to the end of the batch. Simulation results on the benchmark model of penicillin fermentation process can demonstrate that in comparison to the MPCA method, the proposed method is more accurate and efficient for process monitoring and fault diagnosis.

Effect of temperature on batch elastase production by Bacillus sp. EL31410

The production of elastase by Bacillus sp. EL31410 at various temperatures was investigated. In order to study the effect of temperature on elastase fermentation, different cultivation temperatures, ranging from 39 ℃ to 28 ℃, were evaluated in shake flask. The result indicated that 37 ℃ was best for cell growth at earlier stage; while maximum elastase activity was obtained when the cells were cultivated at 30 ℃. This result was verified by batch fermentation in 5-L bio-reactor under 37 ℃ and 30 ℃ temperature, respectively. The specific cell growth rate at 37 ℃ was higher than that at 30 ℃ during earlier stage of cultivation. The maximum value [5.5 U/(h-g DCW)] of elastase formation rate occurred at 24 h at 30 ℃ compared to 4.6 U/(h-g DCW) at 30 h at 37 ℃. Based on these results, two-stage temperature shift strategy and oscillatory temperature cultivation mode were evaluated in the next study. When compared to single temperature of 37 ℃ or 30 ℃, both two-stage temperature shift strategy and oscillatory temperature strategy improved biomass but did not yield the same result as expected for elastase production. The maximum biomass (both 8.6 g/L) was achieved at 30 h at 37 ℃, but at 42 h using two-stage temperature cultivation strategy. The highest elastase production (652 U/ml) was observed at 30 ℃ in batch process. It was concluded that cultivation at constant temperature of 30 ℃ was appropriate for elastase production by Bacillus sp. EL31410.

A Robust Statistical Batch Process Monitoring Framework and Its Application

In order to reduce the variations of the product quality in batch processes, multivariate statistical process control methods according to multi-way principal component analysis (MPCA) or multi-way projection to latent structure (MPLS) were proposed for on-line batch process monitoring. However, they are based on the decomposition of relative covariance matrix and strongly affected by outlying observations. In this paper, in view of an efficient projection pursuit algorithm, a robust statistical batch process monitoring (RSBPM) framework,which is resistant to outliers, is proposed to reduce the high demand for modeling data. The construction of robust normal operating condition model and robust control limits are discussed in detail. It is evaluated on monitoring an industrial streptomycin fermentation process and compared with the conventional MPCA. The results show that the RSBPM framework is resistant to possible outliers and the robustness is confirmed.

RESEARCH ON BATCH AND CONTINUOUS CULTURES OF PHOTOSYNTHETIC BACTERIA P4 STRAIN

The utilization of various media with photosynthetic bacteria (PSB) P4 strain was analyzed. Malate and acetate as carbon sources were more suitable for the growth of P4 than other carbon sources. In batch culture, the influence of the change of the concentration of composition and illumination intensity on the specific growth rate of P4 was studied. Quantitative mathematical models of the relation between them were established. The maximum growth rate (μm=0.167 h-1) and the maximum growth yield (ym=2.84 g/L) were derived. In continuous culture, if the culture is proceeded under the darkaerobic condition, the aeration rate might be maintained at a low level (0.04～0.06 vvm), which is beneficial for the growth of P4. If the culture is in chemostat and the dilution rate (D) is 0.144 h-1,μm could reach 0.189 h-1 and ym would 6.75 g/L.

Batch, Fed Batch Production and Characterization of Glutaminase Free L-Asparaginase II of <i>Pectobacterium carotovorum</i>MTCC 1428 in <i>Escherichia coli</i>

The present study describes the production optimization of recombinant L-asparaginase II of Pectobacterium carotovorum MTCC 1428 in Escherichia coli BL21 (DE3) at batch and fed batch bioreactor level. Production of recombinant L-asparaginase II in batch and fed batch mode was found to be 1.34 and 5.38 folds higher, respectively as compared to shake flask culture. SDS-PAGE and native PAGE of the purified enzyme revealed that molecular mass of the subunits and native enzyme are ~37.5 kDa and ~150 kDa, respectively. Optimum range of pH and temperature for hydrolysis of L-asparagine were found to be 7.5 - 8.5 and 47°C - 52°C, respectively. The recombinant enzyme is very specific for its natural substrate, L-asparagine. The activity of recombinant L-asparaginase II is improved by mono cations and diverse effectors including Na+, K+, L-cystine, L-histidine, glutathione and 2-mercaptoethanol whereas, it is moderately inhibited by different divalent cations and thiol group blocking reagent. The kinetic parameters Km, Vmax, kcat and Km/Kcat of purified recombinant L-asparaginase II were determined. The purified L-asparaginase II possesses no partial glutaminase activity, which is prerequisite to reduce the possibility of side effects during the course of anti-cancer therapy.