State estimation is the precondition and foundation of a bioprocess monitoring and optimal control. However,there are many difficulties in dealing with a non-linear system,such as the instability of process, un-modele...State estimation is the precondition and foundation of a bioprocess monitoring and optimal control. However,there are many difficulties in dealing with a non-linear system,such as the instability of process, un-modeled dynamics,parameter sensitivity,etc.This paper discusses the principles and characteristics of three different approaches,extended Kalman filters,strong tracking filters and unscented transformation based Kalman filters.By introducing the unscented transformation method and a sub-optimal fading factor to correct the prediction error covariance,an improved Kalman filter,unscented transformation based robust Kalman filter,is proposed. The performance of the algorithm is compared with the strong tracking filter and unscented transformation based Kalman filter and illustrated in a typical case study for glutathione fermentation process.The results show that the proposed algorithm presents better accuracy and stability on the state estimation in numerical calculations.展开更多
In order to improve the production of human-like collagen III(HLC III)by fed-batch culture of recombinant Escherichia coli BL21,the Plackett-Burman and Box-Behnken design were applied to optimize the fermentation proc...In order to improve the production of human-like collagen III(HLC III)by fed-batch culture of recombinant Escherichia coli BL21,the Plackett-Burman and Box-Behnken design were applied to optimize the fermentation process parameters.Three variables(induction time,inoculum age and pH),which have significant effects on HLC III production,were selected from eight variables by Plackett-Burman design.With the regression coefficient analysis in the Box-Behnken design,a relationship between HLC III production and three significant factors was obtained,and the optimum levels of the three variables were as follows:induction time 3.2h,inoculum age 12.6 h and pH 6.7.The 3D response surface plots and 2D contour plots created by the Box-Behnken design showed that the interaction between induction time and pH and that between innoculum age and pH were significant.An average 9.68 g·L1HLC III production was attained in the validation experiment under optimized condition,which was 80%higher than the yield of 5.36 g·L1before optimization.展开更多
The dynamic soft sensor based on a single Gaussian process regression(GPR) model has been developed in fermentation processes.However,limitations of single regression models,for multiphase/multimode fermentation proce...The dynamic soft sensor based on a single Gaussian process regression(GPR) model has been developed in fermentation processes.However,limitations of single regression models,for multiphase/multimode fermentation processes,may result in large prediction errors and complexity of the soft sensor.Therefore,a dynamic soft sensor based on Gaussian mixture regression(GMR) was proposed to overcome the problems.Two structure parameters,the number of Gaussian components and the order of the model,are crucial to the soft sensor model.To achieve a simple and effective soft sensor,an iterative strategy was proposed to optimize the two structure parameters synchronously.For the aim of comparisons,the proposed dynamic GMR soft sensor and the existing dynamic GPR soft sensor were both investigated to estimate biomass concentration in a Penicillin simulation process and an industrial Erythromycin fermentation process.Results show that the proposed dynamic GMR soft sensor has higher prediction accuracy and is more suitable for dynamic multiphase/multimode fermentation processes.展开更多
Hyaluronic acid （HA） is a high molecular weight glycosaminoglycan consisting of alternating D-glucuronic acid and N-acetylglueasamine and plays ex- tremely important roles in many biological processes. In this study...Hyaluronic acid （HA） is a high molecular weight glycosaminoglycan consisting of alternating D-glucuronic acid and N-acetylglueasamine and plays ex- tremely important roles in many biological processes. In this study, we optimized fermentation process for the production of HA by Streptococcus zooepidemicus ATCC35246, including fermentation broth composition and various fermentation parameters. The experimental results showed that the optimal fermentation broth composition was： glucose 45 g/L, yeast extract 10 g/L, tryptone 12 g/L, KH2PO4 2 g/L, K2HPO4 . 3H20 2 g/L, MgSO4 · 7H2O 2 g/L, and （NH4 ）2SO4 0.4 g/L. The optimal parameters involved in fermentation was： liquid volume 20%, pH 6. 0, rotation speed 180 r/min, fermentation temperature 35 ℃, fermentation duration 18 h, CTAB concentration 25 mg/L. Under the optimized conditions, the yield of HA was 0. 305 g/L, which was dramatically improved by 43.87% compared to that of 0. 212 g/L before optimization.展开更多
The soft-sensor modeling for fermentation process based on standard support vector regression(SVR) needs to solve the quadratic programming problem(QPP) which will often lead to large computational burdens, slow conve...The soft-sensor modeling for fermentation process based on standard support vector regression(SVR) needs to solve the quadratic programming problem(QPP) which will often lead to large computational burdens, slow convergence rate, low solving efficiency, and etc. In order to overcome these problems, a method of soft-sensor modeling for fermentation process based on geometric SVR is presented. In the method, the problem of solving the SVR soft-sensor model is converted into the problem of finding the nearest points between two convex hulls (CHs) or reduced convex hulls (RCHs) in geometry. Then a geometric algorithm is adopted to generate soft-sensor models of fermentation process efficiently. Furthermore, a swarm energy conservation particle swarm optimization (SEC-PSO) algorithm is proposed to seek the optimal parameters of the augmented training sample sets, the RCH size, and the kernel function which are involved in geometric SVR modeling. The method is applied to the soft-sensor modeling for a penicillin fermentation process. The experimental results show that, compared with the method based on the standard SVR, the proposed method of soft-sensor modeling based on geometric SVR for fermentation process can generate accurate soft-sensor models and has much less amount of computation, faster convergence rate, and higher efficiency.展开更多
This paper studied the fermentation rules of apple cider vinegar from fruit juice,to provide a theoretical guidance for the production of apple cider vinegar.Using Fuji apples as raw materials,the process parameters(f...This paper studied the fermentation rules of apple cider vinegar from fruit juice,to provide a theoretical guidance for the production of apple cider vinegar.Using Fuji apples as raw materials,the process parameters(fermentation temperature,fermentation time,stirring speed,and inoculation amount)of apple cider vinegar fermentation were optimized through single-factor experiments and response surface analysis.The results indicated that the fermentation temperature had no significant effect on the total acid content of apple cider vinegar fermentation,the fermentation time had an extremely significant effect on the total acid content of apple cider vinegar fermentation,and the stirring speed and inoculation amount had a significant effect on the total acid content of apple cider vinegar fermentation.Through process optimization,the optimal process parameters for apple cider vinegar fermentation are fermentation temperature of 33℃,fermentation time of 39 h,stirring speed of 1500 r/min,and acetic acid bacteria inoculation amount of 7%.Under such conditions,the total acid content of fermented apple cider vinegar is 62.22 g/L,very close to the predicted value of the model,indicating that the process parameters of acetic acid fermentation obtained by response surface methodology(RSM)optimization are reliable and can be used for actual production prediction.展开更多
Purebred microorganisms were employed to upgrade the fermentation process of Zhejiang rosy vinegar. The fermentation cycle was greatly shorten from 5 months to 72 d. The transformation rate of raw materials was increa...Purebred microorganisms were employed to upgrade the fermentation process of Zhejiang rosy vinegar. The fermentation cycle was greatly shorten from 5 months to 72 d. The transformation rate of raw materials was increased from 1:4.5 in the traditional fermentation to 1:5 or more in the upgraded fermentation. The content of organic acids in the traditional vinegar (TRV), the upgraded vinegar (UPV) and the submerged fermentation vinegar (SFV) were also investigated by HPLC. No significant difference was found regarding the proportion of phenylethanol to the total volatile components in UPV (7.47% ± 0.00324%) and TRV (7.23% ± 0.00329%), but it was significantly higher than that in SFV (2.26% ± 0.00143%). This study provides deep insight into upgrading the fermentation process of Zhejiang rosy vinegar by purebred microorganisms.展开更多
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 ov...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.展开更多
Current research is concerned with the stability of stochastic logistic equation with Ornstein-Uhlenbeck process. First, this research proves that the stochastic logistic model with Ornstein-Uhlenbeck process has a po...Current research is concerned with the stability of stochastic logistic equation with Ornstein-Uhlenbeck process. First, this research proves that the stochastic logistic model with Ornstein-Uhlenbeck process has a positive solution. After that, it also introduces the sufficient conditions for stochastically stability of stochastic logistic model for cell growth of microorganism in fermentation process for positive equilibrium point by using Lyapunov function. In addition, this research establishes the sufficient conditions for zero solution as mentioned in Appendix A due to the cell growth of microorganism μmax, which cannot be negative in fermentation process. Furthermore, for numerical simulation, current research uses the 4-stage stochastic Runge-Kutta (SRK4) method to show the reality of the results.展开更多
The reducing efficiencies of the commonly used heat treatment methods and fermentation processes on aflatoxin M1 (AFM1) in Nigeria were investigated. Seventy samples of fresh cow milk from both conventional and tradit...The reducing efficiencies of the commonly used heat treatment methods and fermentation processes on aflatoxin M1 (AFM1) in Nigeria were investigated. Seventy samples of fresh cow milk from both conventional and traditional dairy cattle herds were collected and analyzed for the determination of AFM1 using Cobra-cell incorporated high performance liquid chromatography. Of these analyzed samples, 56 (80.0%) tested positive for AFM1 out of which 3 milk samples with high AFM1 concentrations were selectively pooled and subjected to varied conditions of heat treatments and fermentation processes using both indigenized and exotic strains of lactic acid bacteria (Lactobacillus bulgaricus + Streptococcus thermophilus and L. rhamnosus and L. plantarum) as starter cultures respectively. Both processes used either singly or combined, demonstrated high degrees of reducing effects on AFM1 levels. Sterilization of the milk at 121?C and 80?C under the same condition of time (15 - 20) min showed significant reduction of up to 58.8% (p 0.05) in the level of AFM1 when compared with the initial mean AFM1 concentration of the untreated fresh milk. The situation was however different around the boiling temperature of 100?C at which point the level of AFM1 reduction was found to be inconsistent. The indigenized combined strains showed some slight margins of AFM1 reduction in the proportions of (20.5, 30.8 and 43.9)% over and above that of the exotic strains (17.4, 30.0 and 41.1)% in 12 h, 48 h and 72 h of fermentation respectively. Generally, fermentation alone showed lower reduction of AFM1 in milk from 24.5% to 43.9% compared with the reducing activities of (35.4 to 58.8)% when heat-treated milk samples were subsequently subjected to varied fermentation conditions.展开更多
Biomass is a key parameter in fermentation process, directly influencing the performance of the fermentation system as well as the quality and yield of the targeted product. Hybrid soft-sensor modeling is a good metho...Biomass is a key parameter in fermentation process, directly influencing the performance of the fermentation system as well as the quality and yield of the targeted product. Hybrid soft-sensor modeling is a good method for on-line estimation of biomass. Structure of hybrid soft-sensor model is a key to improve the estimating accuracy. In this paper, a forward heuristic breadth-first reasoning approach based on rule match is proposed for constructing structure of hybrid model. First, strategy of forward heuristic reasoning about facts is introduced, which can reason complex hybrid model structure in the event of few known facts. Second, rule match degree is defined to obtain higher esti- mating accuracy. The experiment results of Nosiheptide fermentation process show that the hybrid modeling process can estimate biomass with higher accuracy by adding transcendental knowledge and partial mechanism to the process.展开更多
It has long been thought that bioprocess, with their inherent measurement difficulties and complex dynamics, posed almost insurmountable problems to engineers. A novel software sensor is proposed to make more effectiv...It has long been thought that bioprocess, with their inherent measurement difficulties and complex dynamics, posed almost insurmountable problems to engineers. A novel software sensor is proposed to make more effective use of those meas- urements that are already available, which enable improvement in fermentation process control. The proposed method is based on mixtures of Gaussian processes (GP) with expectation maximization (EM) algorithm employed for parameter estimation of mixture of models. The mixture model can alleviate computational complexity of GP and also accord with changes of operating condition in fermentation processes, i.e., it would certainly be able to examine what types of process-knowledge would be most relevant for local models’ specific operating points of the process and then combine them into a global one. Demonstrated by on-line estimate of yeast concentration in fermentation industry as an example, it is shown that soft sensor based state estimation is a powerful technique for both enhancing automatic control performance of biological systems and implementing on-line moni- toring and optimization.展开更多
Due to its nutritional values, cassava has become an unavailable food and is one of the essential foods in the Republic of Congo. Fermentation of tubers is still traditional. Fiftyrod-shaped spore-forming bacteria wer...Due to its nutritional values, cassava has become an unavailable food and is one of the essential foods in the Republic of Congo. Fermentation of tubers is still traditional. Fiftyrod-shaped spore-forming bacteria were screened and carried out in batch mode for the fermentation abilities of cassava tubers in order to develop biotechnological starter. The Penetrometry Index (PI) has been used to screen bacteria and 16SrRNA as well as <i>fibE</i>one step multiplex PCR which were used to molecularly identify isolates. Emulsification Index, Proteolytic as well as amylolytic, and cellulolytic activities of some strains were quantitatively evaluated for prooving orgaleptic characterics. As results <i>Bacillus subtilis</i> (MT994787), <i>Bacillus subtillis</i> (MT994789), <i>Bacillus tequilensis</i> (MT994788), <i>Bacillus safensis</i>, and <i>Bacillus subtilis</i> have been identified. Single isolates were able to ferment tubers in 48 h and 72 hours meanwhile <i>Bacillus</i> consortia were able to shift fermentation of tubers from 48 hours to 24 hours. The consortium could be used as the major bacterial starters. Strains were associated with the ability to secrete biomolecules including biosurfactants, protease, amylase and cellulase.展开更多
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 nonlinea...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.展开更多
This paper theoretically studies the continuous immobilized cell (IMC) fer mentation system. A kinetic model of IMC is established, and the relational expressions between production rate, substrate concentration, biom...This paper theoretically studies the continuous immobilized cell (IMC) fer mentation system. A kinetic model of IMC is established, and the relational expressions between production rate, substrate concentration, biomass concentration and dilution rate in the IMC continuous stirred tank reactor (CSTR) are derived. These equations and some numerical calculations show that as compared with the free cell system the IMC system has many advantages: high production rate, steady operation, and being independent of the dilution rote. They also indicate that the diffusion of substrate is a constraint to the production of metablite.展开更多
Biosensors, which are the products of the biotechnology industry, are among the key projects of the 7th, 8th, and 9th Fiveyear Plans of China Science ＆ Technology Developing Programs, respectively, and they play an i...Biosensors, which are the products of the biotechnology industry, are among the key projects of the 7th, 8th, and 9th Fiveyear Plans of China Science ＆ Technology Developing Programs, respectively, and they play an important role in developing and reforming traditional biotechnology. SBA series biosensor analyzer, as the only one commercial biosensor in China, has attracted lots of attention in the process of information gathering and measurement for biological industry with the development of technology and society. In this paper, we presented an overview of the most important contributions dealing with the monitoring of the biochemical analytes in fermentation processes using SBA series biosensor analyzers in China. Future trends of the biosensor analyzer in China were also mentioned in the last section.展开更多
Traditional Chinese red sufu is a popular condiment,and typical flavor is an important indicator of sensory qualities in commercial products.In this study,the volatile aroma analysis of Wangzhihe red sufu(WRS)from dif...Traditional Chinese red sufu is a popular condiment,and typical flavor is an important indicator of sensory qualities in commercial products.In this study,the volatile aroma analysis of Wangzhihe red sufu(WRS)from different fermentation stages and four typical red sufu products from different locations was carried out by gas chromatography-mass spectrometry(GC–MS),gas chromatography-mass spectrometry/olfactory(GC–MS/O),electronic nose(E-nose)and sensory evaluation.Results showed that 106 volatile compounds were identified in Wangzhihe red sufu during fermentation process,in which phenolics and alcohols were dominant at molded and salted phetze stages,while esters and alcohols became predominate at post-fermentation stage.The volatile aroma substances varied at each fermentation stage.Furthermore,86 volatiles,including 16 aroma-active compounds,were detected in four typical red sufu products.The multivariate analysis results showed the difference in samples from different fermentation stages and typical red sufu products according to GC–MS and E-nose analysis.Combined with flavor omics,discriminant model was established for effective discrimination of samples from different fermentation stages and locations,as well as references to sufu maturity extent.The study presented a new strategy for quality evaluation of red sufu,which could be the supplement to quality evaluation standards.展开更多
基金Supported by the National Natural Science Foundation of China （20476007, 20676013）.
文摘State estimation is the precondition and foundation of a bioprocess monitoring and optimal control. However,there are many difficulties in dealing with a non-linear system,such as the instability of process, un-modeled dynamics,parameter sensitivity,etc.This paper discusses the principles and characteristics of three different approaches,extended Kalman filters,strong tracking filters and unscented transformation based Kalman filters.By introducing the unscented transformation method and a sub-optimal fading factor to correct the prediction error covariance,an improved Kalman filter,unscented transformation based robust Kalman filter,is proposed. The performance of the algorithm is compared with the strong tracking filter and unscented transformation based Kalman filter and illustrated in a typical case study for glutathione fermentation process.The results show that the proposed algorithm presents better accuracy and stability on the state estimation in numerical calculations.
基金Supported by the National Natural Science Foundation of China（20776119） the National High Technology Research and Development Program of China（2007AA03Z456A） the Special Research Program of the Education Department of Shaanxi Province（07JK417）
文摘In order to improve the production of human-like collagen III(HLC III)by fed-batch culture of recombinant Escherichia coli BL21,the Plackett-Burman and Box-Behnken design were applied to optimize the fermentation process parameters.Three variables(induction time,inoculum age and pH),which have significant effects on HLC III production,were selected from eight variables by Plackett-Burman design.With the regression coefficient analysis in the Box-Behnken design,a relationship between HLC III production and three significant factors was obtained,and the optimum levels of the three variables were as follows:induction time 3.2h,inoculum age 12.6 h and pH 6.7.The 3D response surface plots and 2D contour plots created by the Box-Behnken design showed that the interaction between induction time and pH and that between innoculum age and pH were significant.An average 9.68 g·L1HLC III production was attained in the validation experiment under optimized condition,which was 80%higher than the yield of 5.36 g·L1before optimization.
基金Supported by the Natural Science Foundation of Jiangsu Province of China(BK20130531)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD[2011]6)Jiangsu Government Scholarship
文摘The dynamic soft sensor based on a single Gaussian process regression(GPR) model has been developed in fermentation processes.However,limitations of single regression models,for multiphase/multimode fermentation processes,may result in large prediction errors and complexity of the soft sensor.Therefore,a dynamic soft sensor based on Gaussian mixture regression(GMR) was proposed to overcome the problems.Two structure parameters,the number of Gaussian components and the order of the model,are crucial to the soft sensor model.To achieve a simple and effective soft sensor,an iterative strategy was proposed to optimize the two structure parameters synchronously.For the aim of comparisons,the proposed dynamic GMR soft sensor and the existing dynamic GPR soft sensor were both investigated to estimate biomass concentration in a Penicillin simulation process and an industrial Erythromycin fermentation process.Results show that the proposed dynamic GMR soft sensor has higher prediction accuracy and is more suitable for dynamic multiphase/multimode fermentation processes.
基金Supported by Scientific Research Fund of Sichuan University of Science&Engineering(2011RC12,2014KY02)Scientific Research Foundation of the Education Department of Sichuan Province(15ZA0222)+1 种基金Research Project of Liquor Making Biological Technology and Application of Key Laboratory of Sichuan Province(NJ2013-06)Sichuan Provincial Undergraduate Training Programs for Innovation and Entrepreneurship(201410622021)
文摘Hyaluronic acid （HA） is a high molecular weight glycosaminoglycan consisting of alternating D-glucuronic acid and N-acetylglueasamine and plays ex- tremely important roles in many biological processes. In this study, we optimized fermentation process for the production of HA by Streptococcus zooepidemicus ATCC35246, including fermentation broth composition and various fermentation parameters. The experimental results showed that the optimal fermentation broth composition was： glucose 45 g/L, yeast extract 10 g/L, tryptone 12 g/L, KH2PO4 2 g/L, K2HPO4 . 3H20 2 g/L, MgSO4 · 7H2O 2 g/L, and （NH4 ）2SO4 0.4 g/L. The optimal parameters involved in fermentation was： liquid volume 20%, pH 6. 0, rotation speed 180 r/min, fermentation temperature 35 ℃, fermentation duration 18 h, CTAB concentration 25 mg/L. Under the optimized conditions, the yield of HA was 0. 305 g/L, which was dramatically improved by 43.87% compared to that of 0. 212 g/L before optimization.
基金National Natural Science Foundation of China(No.20676013)
文摘The soft-sensor modeling for fermentation process based on standard support vector regression(SVR) needs to solve the quadratic programming problem(QPP) which will often lead to large computational burdens, slow convergence rate, low solving efficiency, and etc. In order to overcome these problems, a method of soft-sensor modeling for fermentation process based on geometric SVR is presented. In the method, the problem of solving the SVR soft-sensor model is converted into the problem of finding the nearest points between two convex hulls (CHs) or reduced convex hulls (RCHs) in geometry. Then a geometric algorithm is adopted to generate soft-sensor models of fermentation process efficiently. Furthermore, a swarm energy conservation particle swarm optimization (SEC-PSO) algorithm is proposed to seek the optimal parameters of the augmented training sample sets, the RCH size, and the kernel function which are involved in geometric SVR modeling. The method is applied to the soft-sensor modeling for a penicillin fermentation process. The experimental results show that, compared with the method based on the standard SVR, the proposed method of soft-sensor modeling based on geometric SVR for fermentation process can generate accurate soft-sensor models and has much less amount of computation, faster convergence rate, and higher efficiency.
基金Supported by Industrial Promotion Project of Shandong Science and Technology Park in 2017(2017YQ016).
文摘This paper studied the fermentation rules of apple cider vinegar from fruit juice,to provide a theoretical guidance for the production of apple cider vinegar.Using Fuji apples as raw materials,the process parameters(fermentation temperature,fermentation time,stirring speed,and inoculation amount)of apple cider vinegar fermentation were optimized through single-factor experiments and response surface analysis.The results indicated that the fermentation temperature had no significant effect on the total acid content of apple cider vinegar fermentation,the fermentation time had an extremely significant effect on the total acid content of apple cider vinegar fermentation,and the stirring speed and inoculation amount had a significant effect on the total acid content of apple cider vinegar fermentation.Through process optimization,the optimal process parameters for apple cider vinegar fermentation are fermentation temperature of 33℃,fermentation time of 39 h,stirring speed of 1500 r/min,and acetic acid bacteria inoculation amount of 7%.Under such conditions,the total acid content of fermented apple cider vinegar is 62.22 g/L,very close to the predicted value of the model,indicating that the process parameters of acetic acid fermentation obtained by response surface methodology(RSM)optimization are reliable and can be used for actual production prediction.
文摘Purebred microorganisms were employed to upgrade the fermentation process of Zhejiang rosy vinegar. The fermentation cycle was greatly shorten from 5 months to 72 d. The transformation rate of raw materials was increased from 1:4.5 in the traditional fermentation to 1:5 or more in the upgraded fermentation. The content of organic acids in the traditional vinegar (TRV), the upgraded vinegar (UPV) and the submerged fermentation vinegar (SFV) were also investigated by HPLC. No significant difference was found regarding the proportion of phenylethanol to the total volatile components in UPV (7.47% ± 0.00324%) and TRV (7.23% ± 0.00329%), but it was significantly higher than that in SFV (2.26% ± 0.00143%). This study provides deep insight into upgrading the fermentation process of Zhejiang rosy vinegar by purebred microorganisms.
基金Supported by the National Natural Science Foundation of China(20676013,61240047)
文摘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.
文摘Current research is concerned with the stability of stochastic logistic equation with Ornstein-Uhlenbeck process. First, this research proves that the stochastic logistic model with Ornstein-Uhlenbeck process has a positive solution. After that, it also introduces the sufficient conditions for stochastically stability of stochastic logistic model for cell growth of microorganism in fermentation process for positive equilibrium point by using Lyapunov function. In addition, this research establishes the sufficient conditions for zero solution as mentioned in Appendix A due to the cell growth of microorganism μmax, which cannot be negative in fermentation process. Furthermore, for numerical simulation, current research uses the 4-stage stochastic Runge-Kutta (SRK4) method to show the reality of the results.
文摘The reducing efficiencies of the commonly used heat treatment methods and fermentation processes on aflatoxin M1 (AFM1) in Nigeria were investigated. Seventy samples of fresh cow milk from both conventional and traditional dairy cattle herds were collected and analyzed for the determination of AFM1 using Cobra-cell incorporated high performance liquid chromatography. Of these analyzed samples, 56 (80.0%) tested positive for AFM1 out of which 3 milk samples with high AFM1 concentrations were selectively pooled and subjected to varied conditions of heat treatments and fermentation processes using both indigenized and exotic strains of lactic acid bacteria (Lactobacillus bulgaricus + Streptococcus thermophilus and L. rhamnosus and L. plantarum) as starter cultures respectively. Both processes used either singly or combined, demonstrated high degrees of reducing effects on AFM1 levels. Sterilization of the milk at 121?C and 80?C under the same condition of time (15 - 20) min showed significant reduction of up to 58.8% (p 0.05) in the level of AFM1 when compared with the initial mean AFM1 concentration of the untreated fresh milk. The situation was however different around the boiling temperature of 100?C at which point the level of AFM1 reduction was found to be inconsistent. The indigenized combined strains showed some slight margins of AFM1 reduction in the proportions of (20.5, 30.8 and 43.9)% over and above that of the exotic strains (17.4, 30.0 and 41.1)% in 12 h, 48 h and 72 h of fermentation respectively. Generally, fermentation alone showed lower reduction of AFM1 in milk from 24.5% to 43.9% compared with the reducing activities of (35.4 to 58.8)% when heat-treated milk samples were subsequently subjected to varied fermentation conditions.
基金Supported by the National Natural Science Foundation of China (20476007)
文摘Biomass is a key parameter in fermentation process, directly influencing the performance of the fermentation system as well as the quality and yield of the targeted product. Hybrid soft-sensor modeling is a good method for on-line estimation of biomass. Structure of hybrid soft-sensor model is a key to improve the estimating accuracy. In this paper, a forward heuristic breadth-first reasoning approach based on rule match is proposed for constructing structure of hybrid model. First, strategy of forward heuristic reasoning about facts is introduced, which can reason complex hybrid model structure in the event of few known facts. Second, rule match degree is defined to obtain higher esti- mating accuracy. The experiment results of Nosiheptide fermentation process show that the hybrid modeling process can estimate biomass with higher accuracy by adding transcendental knowledge and partial mechanism to the process.
基金Project (No. 2002AA412010) supported by the National High-TechResearch and Development Program (863) of China
文摘It has long been thought that bioprocess, with their inherent measurement difficulties and complex dynamics, posed almost insurmountable problems to engineers. A novel software sensor is proposed to make more effective use of those meas- urements that are already available, which enable improvement in fermentation process control. The proposed method is based on mixtures of Gaussian processes (GP) with expectation maximization (EM) algorithm employed for parameter estimation of mixture of models. The mixture model can alleviate computational complexity of GP and also accord with changes of operating condition in fermentation processes, i.e., it would certainly be able to examine what types of process-knowledge would be most relevant for local models’ specific operating points of the process and then combine them into a global one. Demonstrated by on-line estimate of yeast concentration in fermentation industry as an example, it is shown that soft sensor based state estimation is a powerful technique for both enhancing automatic control performance of biological systems and implementing on-line moni- toring and optimization.
文摘Due to its nutritional values, cassava has become an unavailable food and is one of the essential foods in the Republic of Congo. Fermentation of tubers is still traditional. Fiftyrod-shaped spore-forming bacteria were screened and carried out in batch mode for the fermentation abilities of cassava tubers in order to develop biotechnological starter. The Penetrometry Index (PI) has been used to screen bacteria and 16SrRNA as well as <i>fibE</i>one step multiplex PCR which were used to molecularly identify isolates. Emulsification Index, Proteolytic as well as amylolytic, and cellulolytic activities of some strains were quantitatively evaluated for prooving orgaleptic characterics. As results <i>Bacillus subtilis</i> (MT994787), <i>Bacillus subtillis</i> (MT994789), <i>Bacillus tequilensis</i> (MT994788), <i>Bacillus safensis</i>, and <i>Bacillus subtilis</i> have been identified. Single isolates were able to ferment tubers in 48 h and 72 hours meanwhile <i>Bacillus</i> consortia were able to shift fermentation of tubers from 48 hours to 24 hours. The consortium could be used as the major bacterial starters. Strains were associated with the ability to secrete biomolecules including biosurfactants, protease, amylase and cellulase.
基金Supported by the National Natural Science Foundation of China(61573052)
文摘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.
文摘This paper theoretically studies the continuous immobilized cell (IMC) fer mentation system. A kinetic model of IMC is established, and the relational expressions between production rate, substrate concentration, biomass concentration and dilution rate in the IMC continuous stirred tank reactor (CSTR) are derived. These equations and some numerical calculations show that as compared with the free cell system the IMC system has many advantages: high production rate, steady operation, and being independent of the dilution rote. They also indicate that the diffusion of substrate is a constraint to the production of metablite.
基金Supported by the Postdoctoral Innovation Fund of Shandong Province(201303032)the Independent Innovation Projects of Shandong Province(2012CX20505)the National 863 High Technology Project of the Ministry of Science and Technology of China(2012AA021201)
文摘Biosensors, which are the products of the biotechnology industry, are among the key projects of the 7th, 8th, and 9th Fiveyear Plans of China Science ＆ Technology Developing Programs, respectively, and they play an important role in developing and reforming traditional biotechnology. SBA series biosensor analyzer, as the only one commercial biosensor in China, has attracted lots of attention in the process of information gathering and measurement for biological industry with the development of technology and society. In this paper, we presented an overview of the most important contributions dealing with the monitoring of the biochemical analytes in fermentation processes using SBA series biosensor analyzers in China. Future trends of the biosensor analyzer in China were also mentioned in the last section.
基金the National Key R&D program of China(2016YFD0400500)Beijing Postdoctoral Research Foundation(2018-ZZ-120)Chinese Academy of Engineering Project(2018-XY-28).
文摘Traditional Chinese red sufu is a popular condiment,and typical flavor is an important indicator of sensory qualities in commercial products.In this study,the volatile aroma analysis of Wangzhihe red sufu(WRS)from different fermentation stages and four typical red sufu products from different locations was carried out by gas chromatography-mass spectrometry(GC–MS),gas chromatography-mass spectrometry/olfactory(GC–MS/O),electronic nose(E-nose)and sensory evaluation.Results showed that 106 volatile compounds were identified in Wangzhihe red sufu during fermentation process,in which phenolics and alcohols were dominant at molded and salted phetze stages,while esters and alcohols became predominate at post-fermentation stage.The volatile aroma substances varied at each fermentation stage.Furthermore,86 volatiles,including 16 aroma-active compounds,were detected in four typical red sufu products.The multivariate analysis results showed the difference in samples from different fermentation stages and typical red sufu products according to GC–MS and E-nose analysis.Combined with flavor omics,discriminant model was established for effective discrimination of samples from different fermentation stages and locations,as well as references to sufu maturity extent.The study presented a new strategy for quality evaluation of red sufu,which could be the supplement to quality evaluation standards.
