CN111893145A - Novel intelligent lysine biological fermentation method - Google Patents
Novel intelligent lysine biological fermentation method Download PDFInfo
- Publication number
- CN111893145A CN111893145A CN202010815128.9A CN202010815128A CN111893145A CN 111893145 A CN111893145 A CN 111893145A CN 202010815128 A CN202010815128 A CN 202010815128A CN 111893145 A CN111893145 A CN 111893145A
- Authority
- CN
- China
- Prior art keywords
- fermentation
- concentration
- tail gas
- thalli
- carbon source
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12P—FERMENTATION OR ENZYME-USING PROCESSES TO SYNTHESISE A DESIRED CHEMICAL COMPOUND OR COMPOSITION OR TO SEPARATE OPTICAL ISOMERS FROM A RACEMIC MIXTURE
- C12P13/00—Preparation of nitrogen-containing organic compounds
- C12P13/04—Alpha- or beta- amino acids
- C12P13/08—Lysine; Diaminopimelic acid; Threonine; Valine
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q3/00—Condition responsive control processes
Landscapes
- Organic Chemistry (AREA)
- Chemical & Material Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Zoology (AREA)
- Wood Science & Technology (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- General Engineering & Computer Science (AREA)
- Genetics & Genomics (AREA)
- Microbiology (AREA)
- Biotechnology (AREA)
- Biochemistry (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Immunology (AREA)
- Molecular Biology (AREA)
- Proteomics, Peptides & Aminoacids (AREA)
- Chemical Kinetics & Catalysis (AREA)
- General Chemical & Material Sciences (AREA)
- Preparation Of Compounds By Using Micro-Organisms (AREA)
- Apparatus Associated With Microorganisms And Enzymes (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
Abstract
The invention provides a novel intelligent lysine biological fermentation method, and relates to the technical field of biological fermentation. The novel lysine intelligent biological fermentation method comprises the following steps: 1) the biomass of the thalli is related to the concentration of an acid-producing stream, the addition of a carbon source stream and the addition of a nitrogen source stream: s1, detecting the thallus amount on line by using a microorganism concentration on-line analyzer, and acquiring the concentration of microorganisms in a fermentation tank in real time; and S2, analyzing the biomass of the bacteria, the concentration of an acid produced, the dosage of a carbon source flow and the dosage of a nitrogen source flow in different periods by theoretical analysis of the obtained large amount of test data. According to the invention, various parameters in the fermentation process are integrated and associated, the bacterial amount, the acid production rate, the carbon source and nitrogen source consumption rate and the tail gas analysis data are associated with dissolved oxygen control, so that the automatic control and automatic feeding of the fermentation process are realized, the manual operation is reduced to the maximum extent, and the intelligent fermentation is realized.
Description
Technical Field
The invention relates to the technical field of biological fermentation, in particular to a novel intelligent biological fermentation method for lysine.
Background
The fermenter is a bioreactor, and the bioreactor refers to a system of devices for providing a suitable reaction environment for living cells or enzymes and allowing them to proliferate or produce cells. The bioreactor provides a suitable growth environment for the growth and reproduction of bacteria and promotes the thalli to produce products required by people.
At present, the domestic fermentation tank is not manufactured with a large difference, but the control system difference is large, the single chip DCS group control system is low in cost, but the operation system is complicated, the operation quality is poor, and the maintenance cost is high. Based on the PLC integrated module programmable control system and the corresponding bus control technology, the running quality is stable, the maintenance cost is low, intelligent programming can be realized, and automatic control is realized.
At present, the research on lysine fermentation enters a bottleneck period, most of the research is focused on one aspect of the fermentation process, the fermentation is a complex biochemical process, the factors influencing the fermentation process are more, and the fermentation process is irreversibly influenced from the macro-level culture medium proportion, the fermentation temperature, the raw material quality and the like to the micro-level microbial secondary metabolism, metabolic regulation and the like. The main difference between the fermentation process and the chemical process is that living microbial cells participate in the fermentation process, compared with the whole fermentation system, microbial metabolism is an open system, and needs to continuously exchange substances and energy with the surrounding environment to maintain the life activity of the cells, and the complexity of life behaviors makes the fermentation process more difficult to control than the chemical catalysis process, so that the external environment has an important role in the influence of the intracellular metabolism of the microbes and the synthesis of target metabolites.
The fermentation industry is constantly updated in product research and development, new equipment and new technology application, and the following problems need to be solved to realize the industrialization and control of the fermentation process: firstly, establishing a biological model: secondly, the application of sensor technology; thirdly, optimization technology of complex biological process; system dynamics of a fourth fermentation process; finally, a suitable link is established between the fermentation system and the detection system by means of an interface technology. The production process of secondary metabolites is complex, high-yield strains show high-yield traits and require three levels of molecular-level genetic characteristics, cellular-level metabolic characteristics and engineering-level mass transfer characteristics to interact simultaneously, and global influence can be generated as long as a bottleneck is generated in a certain level link. Therefore, the high-yield strains obtained by various screening means need to show high-yield characters on production, and need to combine with basic theory research, obtain various online direct parameters, indirect parameters and offline parameters by reasoning and verification of a large number of tests and various modern detection means, and establish the correlation between the physiological characteristics of the strains and the biosynthesis process through multi-scale correlation analysis, so that the yield of the lysine-producing strains is pertinently improved, and the breeding work of the high-yield strains is guided.
Based on the above reasons, we have recognized that in the industrial fermentation process of biological medicine, food and the like, the measurement of tail gas oxygen and tail gas carbon dioxide is very important for understanding the macro-physiological metabolic characteristics of the fermentation process. By measuring the oxygen and the carbon dioxide in the tail gas, the oxygen consumption rate (OUR), the carbon dioxide production rate (CER) and the Respiratory Quotient (RQ) which are important physiological metabolic characteristic parameters of the cells can be calculated on line, and further the effective regulation and control of the fermentation process can be realized. The on-line mass spectrometer has high measurement precision and small drift, can simultaneously measure various fermentation tail gas components, has quick response and can circularly and continuously measure the tail gas of a plurality of tanks, and is an ideal tool for providing real-time information of the fermentation tail gas.
At present, automatic sterilization and automatic batching are realized in the control of a fermentation system in the prior art, and the operation of personnel is reduced, but the feeding operation in the feeding-batch fermentation process is still operation without manual experience, the feeding amount of a carbon source and the feeding amount of a nitrogen source and a growth factor in different periods need to be controlled, excessive accumulation is avoided on the basis of meeting the requirement of thallus growth and acid production, and the influence on thallus vitality is generated, meanwhile, for aerobic fermentation, dissolved oxygen control in the fermentation process still needs manual air volume adjustment and stirring, the current fermentation control system needs more manual operation, and the intelligent degree is not enough.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects in the prior art, the invention provides a novel intelligent lysine biological fermentation method, which solves the defects and shortcomings in the prior art.
(II) technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme: a novel intelligent lysine biological fermentation method comprises the following steps:
1) the biomass of the thalli is related to the concentration of an acid-producing stream, the addition of a carbon source stream and the addition of a nitrogen source stream:
s1, detecting the thallus amount on line by using a microorganism concentration on-line analyzer, acquiring the concentration of the microorganisms in the fermentation tank in real time, and sequentially marking the acquired values as W1、W2、W3...Wn；
S2, analyzing the biomass of the thalli, the concentration of an acid produced, the addition of a carbon source flow and the addition of a nitrogen source flow in different periods by theoretically analyzing the obtained large batch of test data, and sequentially obtaining the biomass of the thalli U, the concentration of the acid produced K, the addition of the carbon source flow C and the addition of the nitrogen source flow V;
s3, according to the analysis, the biomass of the thalli is related to the concentration of an acid-producing liquid, the adding amount of a carbon source liquid and the adding amount of a nitrogen source liquid, and different control standards are determined for different fermentation periods;
2) tail gas data is associated with dissolved oxygen control:
s1, combining with an on-line tail gas analyzer, and analyzing the fermentation tail gasAnalyzing the medium oxygen content and the carbon dioxide content to obtain an analysis result, and marking the oxygen content to be L1Carbon dioxide content L2；
S2, according to the analysis results of the oxygen content and the carbon dioxide content, obtaining the lysine fermentation oxygen consumption rate, the carbon dioxide production rate and the respiratory quotient, and directly reflecting the change condition of the lysine metabolic process through the content of oxygen and carbon dioxide in tail gas;
s3, controlling one variable by changing different fermentation conditions, analyzing the change condition of the tail gas, and obtaining the influence result of the fermentation conditions on the fermentation yield and the conversion rate of the lysine by combining the change of indexes of the fermentation process;
and S4, according to the result, associating the tail gas data with dissolved oxygen control, and correspondingly adjusting the fermentation control conditions.
Preferably, the correlation between the cell biomass and the acid production concentration, the carbon source flow rate, and the nitrogen source flow rate further includes:
i) the method takes the rise of dissolved oxygen after the consumption of the bottom sugar as a control starting point, the thalli are in the logarithmic growth phase at the moment, the increase of the thalli amount is relatively quick, the sugar consumption is increased, the acid production rate is increased, after the thalli enter a stabilization period, the sugar consumption is stable, the acid production rate is stable, and then enter a fermentation later period, the carbon source consumption is reduced, and the acid production rate is reduced;
ii) establishing different stages of feeding formulas through experimental analysis, and obtaining feeding coefficients of different fermentation periods through calculation according to the control experience of early-stage artificial feeding to realize the automatic correlation of the biomass of the thalli and the feeding amount of the carbon source, wherein the calculation formula is as follows:
a＝c*v+d+p；
wherein a is the sugar feeding rate (t/m)3·h)；
c is a constant;
v is the increase of cell per unit (g/m)3·h)；
d is the sugar consumption rate (t/m)3·h)；
p is residual sugar control (5 g/L);
iii) correlating the nitrogen source flow rate with the carbon source flow rate according to the nitrogen source consumption level in different periods, and obtaining the carbon/nitrogen ratio in different periods according to the previous test to realize the automatic correlation of the nitrogen source flow rate and the carbon source flow rate;
iv) according to the calculated feeding coefficient, correlating all parameters in a control system to realize the correlation of the biomass of the thalli with the feeding amount of the carbon source and the feeding amount of the nitrogen source flow and realize automatic control.
Preferably, the tail gas data and dissolved oxygen control association further includes the following contents:
i) the lowest dissolved oxygen limit is determined to be 25% through earlier stage tests, and the lowest dissolved oxygen control value is set to be 25% in a fermentation system;
ii) determining a coordination relation between air volume and stirring by using tail gas analysis data, determining whether air volume is increased or rotating speed is adjusted firstly by analyzing tail gas data and fermentation process indexes, analyzing fermentation cost, reflecting the influence of an adjusting mode by using experimental data, and determining an optimal adjusting scheme on the basis of not influencing fermentation conversion rate;
iii) further controlling proper oxygen concentration and carbon dioxide concentration by analyzing tail gas data, linking air quantity and consumption, and adjusting air quantity supply according to sugar stream acceleration.
(III) advantageous effects
The invention provides a novel intelligent lysine biological fermentation method. The method has the following beneficial effects:
according to the invention, various parameters in the fermentation process are integrated and associated, the bacterial amount, the acid production rate, the carbon source and nitrogen source consumption rate and the tail gas analysis data are associated with dissolved oxygen control, so that the automatic control and automatic feeding of the fermentation process are realized, the manual operation is reduced to the maximum extent, and the intelligent fermentation is realized.
Detailed Description
The following will clearly and completely describe the technical solutions in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example (b):
the embodiment of the invention provides a novel intelligent lysine biological fermentation method, which comprises the following steps:
1) the biomass of the thalli is related to the concentration of an acid-producing stream, the addition of a carbon source stream and the addition of a nitrogen source stream:
s1, detecting the thallus amount on line by using a microorganism concentration on-line analyzer, acquiring the concentration of the microorganisms in the fermentation tank in real time, and sequentially marking the acquired values as W1、W2、W3...Wn；
S2, analyzing the biomass of the thalli, the concentration of an acid produced, the addition of a carbon source flow and the addition of a nitrogen source flow in different periods by theoretically analyzing the obtained large batch of test data, and sequentially obtaining the biomass of the thalli U, the concentration of the acid produced K, the addition of the carbon source flow C and the addition of the nitrogen source flow V;
s3, according to the analysis, the biomass of the thalli is related to the concentration of an acid-producing liquid, the adding amount of a carbon source liquid and the adding amount of a nitrogen source liquid, and different control standards are determined for different fermentation periods;
in the present invention, the correlation between the biomass of the cells and the concentration of the acid produced, the addition amount of the carbon source stream, and the addition amount of the nitrogen source stream further includes the following:
i) the method takes the rise of dissolved oxygen after the consumption of the bottom sugar as a control starting point, the thalli are in the logarithmic growth phase at the moment, the increase of the thalli amount is relatively quick, the sugar consumption is increased, the acid production rate is increased, after the thalli enter a stabilization period, the sugar consumption is stable, the acid production rate is stable, and then enter a fermentation later period, the carbon source consumption is reduced, and the acid production rate is reduced;
ii) establishing different stages of feeding formulas through experimental analysis, and obtaining feeding coefficients of different fermentation periods through calculation according to the control experience of early-stage artificial feeding to realize the automatic correlation of the biomass of the thalli and the feeding amount of the carbon source, wherein the calculation formula is as follows:
a＝c*v+d+p；
wherein a is the sugar feeding rate (t/m)3·h)；
c is a constant;
v is a unitIncrease in cell number (g/m)3·h)；
d is the sugar consumption rate (t/m)3·h)；
p is residual sugar control (5 g/L);
iii) correlating the nitrogen source flow rate with the carbon source flow rate according to the nitrogen source consumption level in different periods, and obtaining the carbon/nitrogen ratio in different periods according to the previous test to realize the automatic correlation of the nitrogen source flow rate and the carbon source flow rate;
iv) according to the calculated feeding coefficient, correlating all parameters in a control system to realize the correlation of the biomass of the thalli with the feeding amount of the carbon source and the feeding amount of the nitrogen source flow and realize automatic control;
2) tail gas data is associated with dissolved oxygen control:
s1, analyzing the oxygen content and the carbon dioxide content in the fermentation tail gas by combining with an online tail gas analyzer to obtain an analysis result, wherein the content of the marked oxygen is L1Carbon dioxide content L2；
S2, according to the analysis results of the oxygen content and the carbon dioxide content, obtaining the lysine fermentation oxygen consumption rate, the carbon dioxide production rate and the respiratory quotient, directly reflecting the change condition of the lysine metabolic process through the content of oxygen and carbon dioxide in tail gas, and intuitively reflecting the influence of the change of control parameters on the metabolic process in the lysine fermentation process;
s3, controlling one variable by changing different fermentation conditions, analyzing the change condition of the tail gas, and obtaining the influence result of the fermentation conditions on the fermentation yield and the conversion rate of the lysine by combining the change of indexes of the fermentation process;
s4, according to the results, the tail gas data is associated with dissolved oxygen control, fermentation control conditions are correspondingly adjusted, and the control process is more refined, so that the lysine production conversion rate can be further improved, the yield is improved, and the fermentation cost is saved;
in the invention, the tail gas data and dissolved oxygen control association also comprises the following contents:
i) the lowest dissolved oxygen limit is determined to be 25% through earlier stage tests, and the lowest dissolved oxygen control value is set to be 25% in a fermentation system;
ii) determining a coordination relation between air volume and stirring by using tail gas analysis data, determining whether air volume is increased or rotating speed is adjusted firstly by analyzing tail gas data and fermentation process indexes, analyzing fermentation cost, reflecting the influence of an adjusting mode by using experimental data, and determining an optimal adjusting scheme on the basis of not influencing fermentation conversion rate;
and iii) further controlling proper oxygen concentration and carbon dioxide concentration by analyzing tail gas data, linking air quantity and consumption, adjusting air quantity supply according to sugar flow acceleration, avoiding air quantity waste, reducing accumulation of other substances, improving conversion rate and further saving fermentation cost.
According to the invention, various parameters in the fermentation process are integrated and associated, the bacterial amount, the acid production rate, the carbon source and nitrogen source consumption rate and the tail gas analysis data are associated with dissolved oxygen control, so that the automatic control and automatic feeding of the fermentation process are realized, the manual operation is reduced to the maximum extent, and the intelligent fermentation is realized.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (3)
1. A novel lysine intelligent biological fermentation method is characterized in that: the process comprises the following steps:
1) the biomass of the thalli is related to the concentration of an acid-producing stream, the addition of a carbon source stream and the addition of a nitrogen source stream:
s1, detecting the thallus amount on line by using a microorganism concentration on-line analyzer, acquiring the concentration of the microorganisms in the fermentation tank in real time, and sequentially marking the acquired values as W1、W2、W3...Wn；
S2, analyzing the biomass of the thalli, the concentration of an acid produced, the addition of a carbon source flow and the addition of a nitrogen source flow in different periods by theoretically analyzing the obtained large batch of test data, and sequentially obtaining the biomass of the thalli U, the concentration of the acid produced K, the addition of the carbon source flow C and the addition of the nitrogen source flow V;
s3, according to the analysis, the biomass of the thalli is related to the concentration of an acid-producing liquid, the adding amount of a carbon source liquid and the adding amount of a nitrogen source liquid, and different control standards are determined for different fermentation periods;
2) tail gas data is associated with dissolved oxygen control:
s1, analyzing the oxygen content and the carbon dioxide content in the fermentation tail gas by combining with an online tail gas analyzer to obtain an analysis result, wherein the content of the marked oxygen is L1Carbon dioxide content L2；
S2, according to the analysis results of the oxygen content and the carbon dioxide content, obtaining the lysine fermentation oxygen consumption rate, the carbon dioxide production rate and the respiratory quotient, and directly reflecting the change condition of the lysine metabolic process through the content of oxygen and carbon dioxide in tail gas;
s3, sequentially changing different fermentation conditions, controlling one variable, analyzing the change condition of the tail gas, and obtaining the influence result of the fermentation conditions on the fermentation yield and the conversion rate of the lysine by combining the change of indexes of the fermentation process;
and S4, according to the result, associating the tail gas data with dissolved oxygen control, and correspondingly adjusting the fermentation control conditions.
2. The intelligent new lysine biofermentation method of claim 1, wherein: the correlation between the thallus biomass and the acid production concentration, the adding amount of the carbon source flow and the adding amount of the nitrogen source flow also comprises the following contents:
i) the method takes the rise of dissolved oxygen after the consumption of the bottom sugar as a control starting point, the thalli are in the logarithmic growth phase at the moment, the increase of the thalli amount is relatively quick, the sugar consumption is increased, the acid production rate is increased, after the thalli enter a stabilization period, the sugar consumption is stable, the acid production rate is stable, and then enter a fermentation later period, the carbon source consumption is reduced, and the acid production rate is reduced;
ii) establishing different stages of feeding formulas through experimental analysis, and obtaining feeding coefficients of different fermentation periods through calculation according to the control experience of early-stage artificial feeding to realize the automatic correlation of the biomass of the thalli and the feeding amount of the carbon source, wherein the calculation formula is as follows:
a＝c*v+d+p；
wherein a is the sugar feeding rate (t/m)3·h)；
c is a constant;
v is the increase of cell per unit (g/m)3·h)；
d is the sugar consumption rate (t/m)3·h)；
p is residual sugar control (5 g/L);
iii) correlating the nitrogen source flow rate with the carbon source flow rate according to the nitrogen source consumption level in different periods, and obtaining the carbon/nitrogen ratio in different periods according to the previous test to realize the automatic correlation of the nitrogen source flow rate and the carbon source flow rate;
iv) according to the calculated feeding coefficient, correlating all parameters in a control system to realize the correlation of the biomass of the thalli with the feeding amount of the carbon source and the feeding amount of the nitrogen source flow and realize automatic control.
3. The intelligent new lysine biofermentation method of claim 1, wherein: the tail gas data and dissolved oxygen control association also comprises the following contents:
i) the lowest dissolved oxygen limit is determined to be 25% through earlier stage tests, and the lowest dissolved oxygen control value is set to be 25% in a fermentation system;
ii) determining a coordination relation between air volume and stirring by using tail gas analysis data, determining whether air volume is increased or rotating speed is adjusted firstly by analyzing tail gas data and fermentation process indexes, analyzing fermentation cost, reflecting the influence of an adjusting mode by using experimental data, and determining an optimal adjusting scheme on the basis of not influencing fermentation conversion rate;
iii) further controlling proper oxygen concentration and carbon dioxide concentration by analyzing tail gas data, linking air quantity and consumption, and adjusting air quantity supply according to sugar stream acceleration.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010815128.9A CN111893145A (en) | 2020-08-13 | 2020-08-13 | Novel intelligent lysine biological fermentation method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010815128.9A CN111893145A (en) | 2020-08-13 | 2020-08-13 | Novel intelligent lysine biological fermentation method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111893145A true CN111893145A (en) | 2020-11-06 |
Family
ID=73230337
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010815128.9A Pending CN111893145A (en) | 2020-08-13 | 2020-08-13 | Novel intelligent lysine biological fermentation method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111893145A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115948622A (en) * | 2022-09-22 | 2023-04-11 | 北京蓝晶微生物科技有限公司 | Microbial fermentation control method, device, system, equipment and medium |
| CN117263367A (en) * | 2023-11-21 | 2023-12-22 | 天津创业环保集团股份有限公司 | On-line control method and system for sewage treatment activated sludge process |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101763036A (en) * | 2009-12-29 | 2010-06-30 | 江苏大学 | Lysine fermentation process feeding prediction control system and method based on fuzzy neural network |
| CN101967501A (en) * | 2009-07-27 | 2011-02-09 | 中国科学院过程工程研究所 | Method for producing lysine by feedback supplement based on pH |
| CN107964506A (en) * | 2016-10-19 | 2018-04-27 | 深圳华大基因研究院 | A kind of feeding medium during fermentation Optimal Control System and method |
-
2020
- 2020-08-13 CN CN202010815128.9A patent/CN111893145A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101967501A (en) * | 2009-07-27 | 2011-02-09 | 中国科学院过程工程研究所 | Method for producing lysine by feedback supplement based on pH |
| CN101763036A (en) * | 2009-12-29 | 2010-06-30 | 江苏大学 | Lysine fermentation process feeding prediction control system and method based on fuzzy neural network |
| CN107964506A (en) * | 2016-10-19 | 2018-04-27 | 深圳华大基因研究院 | A kind of feeding medium during fermentation Optimal Control System and method |
Non-Patent Citations (3)
| Title |
|---|
| 刘仲汇 等: "尾气在线检测分析在发酵中的应用", 《发酵科技通讯》, vol. 41, no. 4, pages 32 - 35 * |
| 张俊刚 等: "溶氧对氨基酸发酵的影响及控制", 《科技视界》, no. 35, pages 223 * |
| 梁恒宇 等: "基于高通量生物反应器和分段式pH反馈补料技术发酵生产L-赖氨酸", 《食品研究与开发》, vol. 37, no. 6, pages 176 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115948622A (en) * | 2022-09-22 | 2023-04-11 | 北京蓝晶微生物科技有限公司 | Microbial fermentation control method, device, system, equipment and medium |
| CN117263367A (en) * | 2023-11-21 | 2023-12-22 | 天津创业环保集团股份有限公司 | On-line control method and system for sewage treatment activated sludge process |
| CN117263367B (en) * | 2023-11-21 | 2024-03-22 | 天津创业环保集团股份有限公司 | On-line control method and system for sewage treatment activated sludge process |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Anderlei et al. | Online respiration activity measurement (OTR, CTR, RQ) in shake flasks | |
| JP5018104B2 (en) | Cell culture method and cell culture apparatus | |
| JP6955531B2 (en) | Bioreactor process control | |
| CN103698541B (en) | Glutamic acid fermentation on-line detecting system and adopt the method for this system on-line checkingi | |
| CN101484572A (en) | A method for on-line optimization of a fed-batch fermentation unit to maximize the product yield | |
| CN102965272B (en) | The implementation method of Fermentation linkage device and fermentation linkage | |
| Minihane et al. | Fed-batch culture technology | |
| CN111893145A (en) | Novel intelligent lysine biological fermentation method | |
| US11603517B2 (en) | Method for monitoring a biotechnological process | |
| Henson | Biochemical reactor modeling and control | |
| US3384553A (en) | Method and equipment for aerobic fermentation on liquid culture mediums | |
| CN1312368A (en) | Automatically controlled fermentor device for process optimization and data amplification | |
| CN116540533A (en) | Digital twin technology-based fermentation dissolved oxygen concentration optimization control method | |
| Calam et al. | Microbial aspects of fermentation process development | |
| Kager et al. | A generic biomass soft sensor and its application in bioprocess development | |
| Akgün et al. | Application of an improved continuous parallel shaken bioreactor system for three microbial model systems | |
| CN101235397A (en) | Regulation and control of lactic acid fermentation by utilizing oxidation-reduction potential | |
| Hrnčiřík et al. | Software sensors for biomass concentration estimation in filamentous microorganism cultivation process | |
| Kumara Behera et al. | Material-balance calculation of fermentation processes | |
| Kim et al. | Control of intracellular ammonium level using specific oxygen uptake rate for overproduction of citric acid by Aspergillus niger | |
| CN202924999U (en) | Fermentation linkage device | |
| CN103509883A (en) | Novel feeding regulation and control process applicable to multiple microorganism fermentation | |
| RU2811437C1 (en) | Method of cultivating methane-oxidizing microorganisms | |
| Yunus et al. | Kinetic Study of Microbial Growth in Anaerobic Digestion of Solid Waste | |
| CN102154097A (en) | Device for automatically regulating and controlling oxidation-reduction potential and application thereof |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |