CN112342263A - Method for predicting growth trend of fermentation bacteria in real time - Google Patents
Method for predicting growth trend of fermentation bacteria in real time Download PDFInfo
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- CN112342263A CN112342263A CN202011098295.2A CN202011098295A CN112342263A CN 112342263 A CN112342263 A CN 112342263A CN 202011098295 A CN202011098295 A CN 202011098295A CN 112342263 A CN112342263 A CN 112342263A
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- 238000000855 fermentation Methods 0.000 title claims abstract description 22
- 230000004151 fermentation Effects 0.000 title claims abstract description 22
- 238000000034 method Methods 0.000 title claims abstract description 17
- 241000894006 Bacteria Species 0.000 title claims description 14
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims abstract description 10
- 239000001301 oxygen Substances 0.000 claims abstract description 10
- 229910052760 oxygen Inorganic materials 0.000 claims abstract description 10
- 238000003756 stirring Methods 0.000 claims abstract description 8
- 238000004519 manufacturing process Methods 0.000 claims abstract description 7
- 241001052560 Thallis Species 0.000 abstract description 6
- 238000004458 analytical method Methods 0.000 abstract description 6
- 238000005070 sampling Methods 0.000 description 6
- 238000001514 detection method Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 4
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011109 contamination Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000007789 gas Substances 0.000 description 1
- 238000011081 inoculation Methods 0.000 description 1
- 230000036284 oxygen consumption Effects 0.000 description 1
- 230000001954 sterilising effect Effects 0.000 description 1
- 238000004659 sterilization and disinfection Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 238000000844 transformation Methods 0.000 description 1
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- 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
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/02—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving viable microorganisms
- C12Q1/04—Determining presence or kind of microorganism; Use of selective media for testing antibiotics or bacteriocides; Compositions containing a chemical indicator therefor
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Abstract
The invention discloses a method for predicting the growth trend of zymocyte in real time, which comprises the following steps: (1) detecting the air flow, the tank pressure, the dissolved oxygen and the stirring speed in the full-automatic fermentation tank in real time, establishing a formula to express the current growth state of the thalli in the tank,
f is the air inlet flow, R is the stirring speed, P is the pressure in the tank, DO is dissolved oxygen, and Z is the origin; the origin is obtained by performing 0-point correction on the thalli after the thalli are inoculated into a fermentation tank; (2) storing FUR according to a period, and drawing a corresponding growth curve according to data; (3) selecting 2 batches of data with better growth from the past production data to draw an optimal data interval; (4) comparing the curve drawn by the real-time FUR value in the step (2) with the optimal curve range in the step (3); (5) when the curve in the step (2) deviates from the optimal curve range, analyzing and correcting; the method is simple and easy to implement, has low cost, and realizes judgment and analysis of thallus growth trend.
Description
Technical Field
The invention relates to a method for predicting the growth trend of zymocyte in real time.
Background
The growth state of bacteria in the tank needs to be observed in real time in the fermentation process, and the prior art mainly depends on sampling off-line detection. The sampling detection is needed for some unstable strains every 1 hour, the sterilization needs 20 minutes before sampling, the detection needs about 10 minutes after sampling, one person needs to be specially arranged for sampling detection, and the risk of in-tank contamination is increased by frequent sampling. After the detection result is obtained, a professional engineer is required to analyze the current state and prejudge the growth trend of the current state, so that the subsequent process adjustment is determined. A fermentation period from 48 continuous hours to 1 continuous month is possible, and the labor intensity is very high. Therefore, the method can judge the growth state of bacteria on line and assist in prejudging the growth trend is an important function.
At present, a technology for observing the growth state by analyzing and detecting the Oxygen Uptake Rate (OUR) of tail gas is available, but the equipment price is very high, the use is inconvenient, the technology is not mature, and the capability of analyzing the current growth state is not provided.
Disclosure of Invention
The invention aims to solve the technical problem of overcoming the defects of the prior art and providing a method for predicting the growth trend of fermentation bacteria in real time, which is simple and easy to implement and low in cost and realizes the judgment and analysis of the growth trend of bacteria.
In order to solve the technical problems, the invention provides a method for predicting the growth trend of fermentation bacteria in real time, which specifically comprises the following steps:
(1) detecting the air flow, the tank pressure, the dissolved oxygen and the stirring speed in the full-automatic fermentation tank in real time, establishing the following formula to visually express the thallus state in the tank, and defining the growth trend from the beginning to the current as FUR:
wherein F is air inlet flow m3/min, R is stirring rotation speed R/min, P is tank pressure Mpa, DO is dissolved oxygen mg/L, and Z is the origin;
the origin point is obtained by immediately correcting the thallus after the thallus is accessed into the fermentation tank by 0 point, and the origin point indicates the current state of the thallus;
(2) storing the FUR in the step (1) according to the period, and drawing a corresponding growth curve according to the data to prejudge the growth trend of the zymocyte; (3) selecting a plurality of good growing batch data from the previous production data to obtain an optimal curve range;
(4) comparing the curve drawn by the real-time FUR value in the step (2) with the optimal curve range in the step (3);
(5) and (3) when the curve in the step (2) deviates from the optimal curve range, analyzing and correcting.
The invention further defines the technical scheme as follows:
in the method for predicting the growth trend of the fermentation bacteria in real time, the production data selected in the step (3) is 2 batches of data.
In the method for predicting the growth trend of the fermenting bacteria in real time, the period for storing the FUR value in the step (2) is 1 min.
The invention has the beneficial effects that:
the method realizes judgment and analysis of the thallus growth trend with low cost, and provides a powerful support for popularizing online thallus growth analysis in the fermentation industry; meanwhile, the method also promotes the customers to strengthen the attention on each batch of data; the analysis of the growth trend of the thalli is a part which is regarded as important at present by foreign fermentation technology, and is also researched all the time, so that the pushing effect of the technology with too high cost on the domestic fermentation industry is very slight.
Drawings
FIG. 1 is a schematic diagram of a growth curve and an optimal growth curve according to an embodiment of the present invention.
Detailed Description
Example 1
The method for predicting the growth trend of the fermentation bacteria in real time provided by the embodiment specifically comprises the following steps:
(1) the oxygen in the culture solution needs to be consumed for the growth of the zymocyte, the more the thalli is, the larger the oxygen consumption is, the air flow, the tank pressure, the dissolved oxygen and the stirring rotating speed in the full-automatic fermentation tank are detected in real time, a formula is established to visually express the current growth state of the thalli in the tank, and the growth trend from the beginning to the current is defined as FUR:
wherein F is air inlet flow m3/min, R is stirring rotation speed R/min, P is tank pressure Mpa, DO is dissolved oxygen mg/L, and Z is the origin;
the origin point is obtained by immediately correcting the thallus after the thallus is accessed into the fermentation tank by 0 point, and the origin point indicates the current state of the thallus;
(2) storing the FUR in the step (1) according to a period, drawing a corresponding growth curve according to the data, and prejudging the growth trend of the fermentation bacteria, wherein the abscissa of the growth curve is the timing time after inoculation, the ordinate is a selected parameter value, and the parameter value can be an FUR value according to needs;
(3) selecting a plurality of good growing batch data from the previous production data as reference data 1 and reference data 2 in the graph to obtain an optimal curve range;
(4) comparing the curve drawn by the real-time FUR value in the step (2) with the optimal curve range in the step (3), wherein as shown in FIG. 1, the middle line in the graph is the curve drawn by the real-time FUR value, and the upper and lower curves respectively refer to the data 1 and the reference data 2 to obtain the optimal curve range;
(5) and (3) when the curve in the step (2) deviates from the optimal curve range, selecting other parameters for analysis and correction, and correspondingly adjusting the condition of the fermentation tank in time.
In this embodiment, the production data selected in step (3) is 2 batches of data.
In this embodiment, the period for storing the FUR value in step (2) is 1 min. In addition to the above embodiments, the present invention may have other embodiments. All technical solutions formed by adopting equivalent substitutions or equivalent transformations fall within the protection scope of the claims of the present invention.
Claims (3)
1. A method for predicting the growth trend of fermentation bacteria in real time is characterized by comprising the following steps:
(1) detecting the air flow, the tank pressure, the dissolved oxygen and the stirring speed in the full-automatic fermentation tank in real time, establishing the following formula to visually express the thallus state in the tank, and defining the growth trend from the beginning to the current as FUR:
wherein F is air inlet flow m3/min, R is stirring rotation speed R/min, P is tank pressure Mpa, DO is dissolved oxygen mg/L, and Z is the origin;
the origin point is obtained by immediately correcting the thallus after the thallus is accessed into the fermentation tank by 0 point, and the origin point indicates the current state of the thallus;
(2) storing the FUR in the step (1) according to the period, and drawing a corresponding growth curve according to the data to prejudge the growth trend of the zymocyte;
(3) selecting a plurality of good growing batch data from the previous production data to obtain an optimal curve range;
(4) comparing the curve drawn by the real-time FUR value in the step (2) with the optimal curve range in the step (3);
(5) and (3) when the curve in the step (2) deviates from the optimal curve range, analyzing and correcting.
2. The method for predicting the growth trend of fermentative bacteria in real time according to claim 1, wherein: the production data selected in the step (3) is 2 batches of data.
3. The method for predicting the growth trend of fermentative bacteria in real time according to claim 1, wherein: the period for storing the FUR value in the step (2) is 1 min.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011098295.2A CN112342263B (en) | 2020-10-14 | Method for pre-judging growth trend of fermenting bacteria in real time |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011098295.2A CN112342263B (en) | 2020-10-14 | Method for pre-judging growth trend of fermenting bacteria in real time |
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| Publication Number | Publication Date |
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| CN112342263A true CN112342263A (en) | 2021-02-09 |
| CN112342263B CN112342263B (en) | 2024-05-31 |
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|---|---|---|---|---|
| JP2007252367A (en) * | 2006-02-24 | 2007-10-04 | Toray Ind Inc | Method for producing chemical by continuous fermentation and continuous fermentation apparatus |
| US20090048816A1 (en) * | 2006-01-28 | 2009-02-19 | Abb Research Ltd | Method for on-line prediction of future performance of a fermentation unit |
| US20090117647A1 (en) * | 2006-07-14 | 2009-05-07 | Abb Research Ltd. | Method for on-line optimization of a fed-batch fermentation unit to maximize the product yield |
| CN101775430A (en) * | 2008-09-11 | 2010-07-14 | 华东理工大学 | Method and device for optimizing and amplifying fermentation process |
| US20130252271A1 (en) * | 2012-03-22 | 2013-09-26 | Biomerieux, Inc. | Method and system for detection of microbial growth in a specimen container |
| CN104250657A (en) * | 2013-06-28 | 2014-12-31 | 华东理工大学 | Method for fermental cultivation of marine fungi for production of anticancer compound 1403 C |
| CN105095587A (en) * | 2015-08-04 | 2015-11-25 | 莆田学院 | Microbial fermentation optimizing method based on bacterium foraging algorithm |
| CN106290240A (en) * | 2016-08-29 | 2017-01-04 | 江苏大学 | A kind of method based on near-infrared spectral analysis technology to Yeast Growth curve determination |
| CN109913483A (en) * | 2017-12-12 | 2019-06-21 | 上海清流生物医药科技有限公司 | A kind of fermentation manufacturing technique of protein drug |
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090048816A1 (en) * | 2006-01-28 | 2009-02-19 | Abb Research Ltd | Method for on-line prediction of future performance of a fermentation unit |
| JP2007252367A (en) * | 2006-02-24 | 2007-10-04 | Toray Ind Inc | Method for producing chemical by continuous fermentation and continuous fermentation apparatus |
| US20090117647A1 (en) * | 2006-07-14 | 2009-05-07 | Abb Research Ltd. | Method for on-line optimization of a fed-batch fermentation unit to maximize the product yield |
| CN101775430A (en) * | 2008-09-11 | 2010-07-14 | 华东理工大学 | Method and device for optimizing and amplifying fermentation process |
| US20130252271A1 (en) * | 2012-03-22 | 2013-09-26 | Biomerieux, Inc. | Method and system for detection of microbial growth in a specimen container |
| CN104250657A (en) * | 2013-06-28 | 2014-12-31 | 华东理工大学 | Method for fermental cultivation of marine fungi for production of anticancer compound 1403 C |
| CN105095587A (en) * | 2015-08-04 | 2015-11-25 | 莆田学院 | Microbial fermentation optimizing method based on bacterium foraging algorithm |
| CN106290240A (en) * | 2016-08-29 | 2017-01-04 | 江苏大学 | A kind of method based on near-infrared spectral analysis technology to Yeast Growth curve determination |
| CN109913483A (en) * | 2017-12-12 | 2019-06-21 | 上海清流生物医药科技有限公司 | A kind of fermentation manufacturing technique of protein drug |
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