Intelligent control and adjustment method for high-precision fermentation and purification of stachyose

Abstract

The invention discloses an intelligent control and regulation method for high-precision fermentation and purification of stachyose, and relates to the related field of biological fermentation process control, and the method comprises the following steps: obtaining a stachyose mixed solution in a first sugar degree interval; after sterilization, eurotium cristatum is inoculated at a first preset temperature to start fermentation, and initial fermentation liquor is obtained; the content proportion change of stachyose and non-target saccharides is monitored in real time through HPLC, and sugar content monitoring data is obtained; introducing into membrane separation equipment for selective dialysis to obtain membrane transmittance monitoring data; performing stachyose enrichment dynamic evaluation according to the sugar content monitoring data and the membrane transmittance monitoring data, and generating a fermentation condition dynamic adjustment strategy based on an evaluation result; and adjusting and controlling the fermentation process. The technical problems of low fermentation efficiency and low purity caused by incapability of accurately monitoring and dynamically adjusting fermentation conditions in real time in existing stachyose fermentation and purification are solved, and the technical effect of improving the stachyose fermentation efficiency and purity by intelligently controlling the fermentation process is achieved.

Description

Technical Field

[0001] This application relates to the field of biological fermentation process control, and particularly to an intelligent control and adjustment method for the high-precision fermentation and purification of stachyose. Background Art

[0002] As a functional oligosaccharide, stachyose has important application values in the fields of food, medicine, etc. Its high-precision fermentation and purification are crucial for improving product quality and market competitiveness. Currently, the main method to solve the problem of stachyose fermentation and purification is to combine traditional fermentation processes with subsequent separation and purification steps, such as chromatographic separation, etc., to achieve the enrichment and purification of stachyose. However, due to the lack of real-time and accurate monitoring of the changes in sugar substances during the fermentation process, traditional methods are difficult to dynamically adjust the fermentation conditions, resulting in low fermentation efficiency and low stachyose purity, and unable to meet the market demand for high-purity stachyose.

[0003] In the related technologies at the present stage, there are technical problems in stachyose fermentation and purification, such as the inability to monitor in real time and accurately and dynamically adjust the fermentation conditions, resulting in low fermentation efficiency and low purity. Summary of the Invention

[0004] This application provides an intelligent control and adjustment method for the high-precision fermentation and purification of stachyose. By using technical means such as real-time monitoring of the content ratio changes of sugar substances in the fermentation broth through HPLC and obtaining membrane permeability monitoring data by using a membrane separation device, and based on these monitoring data, a dynamic evaluation of stachyose enrichment is carried out, and then a dynamic adjustment strategy for fermentation conditions is generated, etc. This solves the technical problems existing in the existing stachyose fermentation and purification, such as the inability to monitor in real time and accurately and dynamically adjust the fermentation conditions, resulting in low fermentation efficiency and low purity, and achieves the technical effect of improving the fermentation efficiency and purity of stachyose through intelligent control of the fermentation process.

[0005] This application provides an intelligent control and adjustment method for the high-precision fermentation and purification of stachyose, including: obtaining a stachyose mixture in a first sugar concentration range, where the stachyose mixture contains stachyose and non-target sugars that can be degraded by Eurotium cristatum; after sterilizing the stachyose mixture, inoculating Eurotium cristatum at a first preset temperature to start fermentation to obtain an initial fermentation broth; real-time monitoring the content ratio changes of stachyose and non-target sugars in the initial fermentation broth through HPLC to obtain sugar content monitoring data; introducing a membrane separation device to perform selective dialysis on the initial fermentation broth to obtain membrane permeability monitoring data, including the change rate of stachyose retention concentration and the change value of membrane flux; performing a dynamic evaluation of stachyose enrichment according to the sugar content monitoring data and the membrane permeability monitoring data, and generating a dynamic adjustment strategy for fermentation conditions based on the evaluation result; adjusting and controlling the fermentation process according to the dynamic adjustment strategy for fermentation conditions.

[0006] In a possible implementation, for the dynamic evaluation of stachyose enrichment based on the sugar content monitoring data and the membrane permeability monitoring data, and generating a dynamic adjustment strategy for the fermentation conditions, the following processing is performed: calculating real-time stachyose purity data based on the sugar content monitoring data; calculating the correlation coefficient between the change rate of stachyose retention concentration and the change value of membrane flux based on the membrane permeability monitoring data; fusing the real-time stachyose purity data with the correlation coefficient to obtain a comprehensive purity evaluation value; performing an analysis on the purity change trend based on the comprehensive purity evaluation value to obtain the real-time stachyose purity improvement rate; if the real-time stachyose purity improvement rate is less than or equal to a preset improvement rate threshold, generating a dynamic adjustment strategy for the fermentation conditions.

[0007] In a possible implementation, for the step of generating a dynamic adjustment strategy for the fermentation conditions if the real-time stachyose purity improvement rate is less than or equal to a preset improvement rate threshold, the following processing is performed: performing an attribution analysis on the purity change trend of stachyose to identify the key limiting sugars among the non-target sugars; constructing a fermentation condition optimization model based on the degradation characteristics of Eurotium cristatum for non-target sugars; optimizing the fermentation conditions through the fermentation condition optimization model based on the key limiting sugars to generate a dynamic adjustment strategy for the fermentation conditions.

[0008] In a possible implementation, for the step of performing an attribution analysis on the purity change trend of stachyose to identify the key limiting sugars among the non-target sugars, the following processing is performed: calculating real-time non-target sugar purity data based on the sugar content monitoring data; performing an analysis on the purity change trend based on the real-time non-target sugar purity data to obtain the real-time non-target sugar purity decrease rate; sorting the real-time non-target sugar purity decrease rates in ascending order, and determining the non-target sugar ranked first as the key limiting sugar.

[0009] In a possible implementation, for the step of constructing a fermentation condition optimization model based on the degradation characteristics of Eurotium cristatum for non-target sugars, the following processing is performed: measuring the degradation kinetic parameters of Eurotium cristatum for various non-target sugars under different fermentation conditions through preliminary experiments, and establishing the first response relationship, the second response relationship until the Nth response relationship, where N is the number of types of non-target sugars; constructing the first fermentation condition optimization branch, the second fermentation condition optimization branch until the Nth fermentation condition optimization branch based on the first response relationship, the second response relationship until the Nth response relationship; constructing a cross-branch coordination control mechanism based on the degradation kinetic coupling relationship between the optimization branches; integrating the first fermentation condition optimization branch, the second fermentation condition optimization branch until the Nth fermentation condition optimization branch and the cross-branch coordination control mechanism to construct a fermentation condition optimization model.

[0010] In a possible implementation, based on the key limiting sugars, the fermentation conditions are optimized through the fermentation condition optimization model to generate a dynamic adjustment strategy for fermentation conditions, and the following processing is performed: Based on the key limiting sugars, the Mth fermentation condition optimization branch is determined, where the Mth fermentation condition optimization branch is the branch corresponding one-to-one to the key limiting sugars, and M is greater than or equal to 1 and less than or equal to N; the Mth fermentation condition optimization branch optimizes the fermentation conditions according to the Mth response relationship and outputs an initial dynamic adjustment strategy for fermentation conditions; according to the cross-branch coordination control mechanism, the initial dynamic adjustment strategy for fermentation conditions is input into the remaining N - 1 branches for simulation prediction, the change amplitude of the degradation rate of each branch is calculated, and if the predicted degradation rate decrease amplitude of any one of the N - 1 branches is greater than or equal to the preset amplitude threshold, a constraint condition is generated; based on the constraint condition, the initial dynamic adjustment strategy for fermentation conditions is optimized and adjusted until the predicted degradation rate decrease amplitude of any one of the N - 1 branches is less than the preset amplitude threshold, and a dynamic adjustment strategy for fermentation conditions is generated.

[0011] In a possible implementation, the content ratio change of stachyose and non-target sugars in the initial fermentation broth is monitored in real time by HPLC to obtain sugar content monitoring data, and the following processing is performed: An HPLC online detection system is set in the fermentation tank, and the HPLC online detection system includes a micro pump, an online filter, and a detector; the micro pump extracts the initial fermentation broth at a preset time interval and a preset flow rate to obtain a fermentation broth sample; the fermentation broth sample is subjected to solid impurity removal through the online filter to obtain a standard fermentation broth sample; the detector detects the content ratio of stachyose and non-target sugars in the standard fermentation broth sample to generate sugar content monitoring data.

[0012] In a possible implementation, a membrane separation device is introduced to perform selective dialysis on the initial fermentation broth to obtain membrane permeability monitoring data, and the following processing is performed: A membrane separation device is set in the extracorporeal circulation pipeline of the fermentation tank, and the membrane separation device includes a hollow fiber membrane module, a peristaltic pump, a first detector, and a second detector, where the first detector is set in the retention side circulation pipeline, and the second detector is set at the permeate side outlet; the peristaltic pump pumps the initial fermentation broth into the membrane separation device at a preset flow rate, and selective dialysis is performed through the hollow fiber membrane module to obtain a retentate and a permeate; the stachyose concentration data of the retentate is obtained in real time through the first detector, and the flow rate data of the permeate is obtained in real time through the second detector; the change rate of the stachyose retention concentration and the membrane flux change value are respectively calculated according to the stachyose concentration data and the flow rate data.

[0013] In a possible implementation, for the fermentation process regulation and control according to the fermentation condition dynamic adjustment strategy, the following processing is performed: a multi-parameter coupling sensor is arranged in the fermentation tank; the multi-parameter coupling sensor monitors the temperature, dissolved oxygen and stirring speed in the fermentation tank in real time to obtain real-time fermentation condition monitoring data; according to the fermentation condition dynamic adjustment strategy and the real-time fermentation condition monitoring data, the fermentation conditions in the fermentation tank are adjusted through a PID controller to perform fermentation process regulation and control.

[0014] In a possible implementation, after the fermentation process regulation and control according to the fermentation condition dynamic adjustment strategy, the following processing is further performed: when the stachyose purity in the sugar content monitoring data is greater than or equal to a first preset purity and the non-target sugar purity is less than or equal to a second preset purity, the fermentation is terminated to obtain a high-purity fermentation broth; after sterilizing the high-purity fermentation broth, the system temperature is controlled to be less than or equal to a second preset temperature, and precipitation and decolorization treatment are performed through activated carbon to obtain a first purified solution; the first purified solution is subjected to impurity and bacteria removal treatment through an ultrafiltration membrane to obtain a second purified solution; the second purified solution is subjected to desalting and non-target sugar removal treatment through a nanofiltration membrane and then concentrated to a second sugar concentration range to obtain a concentrated fermentation broth; after spray drying treatment of the concentrated fermentation broth, stachyose dry powder with a stachyose purity greater than or equal to a third preset purity is obtained.

[0015] It is intended to adopt the intelligent control and regulation method for high-precision fermentation and purification of stachyose proposed in this application. First, a stachyose mixture in a first sugar concentration range is obtained. The stachyose mixture contains stachyose and non-target sugars that can be degraded by Eurotium cristatum. Then, after sterilizing the stachyose mixture, Eurotium cristatum is inoculated at a first preset temperature to initiate fermentation to obtain an initial fermentation broth. Then, the content ratio changes of stachyose and non-target sugars in the initial fermentation broth are monitored in real time through HPLC to obtain sugar content monitoring data. At the same time, a membrane separation device is introduced to perform selective dialysis on the initial fermentation broth to obtain membrane permeability monitoring data, including the change rate of stachyose retention concentration and the change value of membrane flux. Then, a dynamic evaluation of stachyose enrichment is performed according to the sugar content monitoring data and the membrane permeability monitoring data, and a fermentation condition dynamic adjustment strategy is generated based on the evaluation result. Finally, the fermentation process is regulated and controlled according to the fermentation condition dynamic adjustment strategy. The technical effect of improving the fermentation efficiency and purity of stachyose by intelligent control of the fermentation process is achieved. Description of the Drawings

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments of the present invention will be briefly introduced below. Flowcharts are used in this application to illustrate the operations performed by the methods according to the embodiments of this application. It should be understood that the operations in the front or below do not necessarily need to be precisely executed in sequence. On the contrary, according to needs, various steps can be executed in reverse order or simultaneously. At the same time, other operations can also be added to these processes, or one or several operations can be removed from these processes.

[0017] Figure 1 It is a schematic flow diagram of the intelligent control and adjustment method for the high-precision fermentation and purification of stachyose provided by the embodiments of this application.

[0018] Figure 2 It is a schematic flow diagram of generating a dynamic adjustment strategy for fermentation conditions in the intelligent control and adjustment method for the high-precision fermentation and purification of stachyose provided by the embodiments of this application. Detailed implementation manners

[0019] The above description is only an overview of the technical solutions of this application. In order to be able to more clearly understand the technical means of this application, it can be implemented according to the content of the description. And in order to make the above and other purposes, features, and advantages of this application more obvious and understandable, the following specifically gives the detailed implementation manners of this application.

[0020] In order to make the purpose, technical solutions, and advantages of this application clearer, the following will further describe this application in detail in conjunction with the accompanying drawings. The described embodiments should not be regarded as limitations of this application. All other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of this application.

[0021] In the following description, "some embodiments" are involved, which describe a subset of all possible embodiments. However, it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict. The terms "first\second" involved are only used to distinguish similar objects and do not represent a specific order for the objects. The terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units does not necessarily limit to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application.

[0022] The embodiments of this application provide an intelligent control and adjustment method for the high-precision fermentation and purification of stachyose, such asFigure 1 As shown, the method includes: Step S100: Obtain a stachyose mixture in a first sugar concentration range, where the stachyose mixture contains stachyose and non-target sugars that can be degraded by Eurotium cristatum.

[0023] Specifically, obtain a stachyose mixture in a first sugar concentration range through a raw material preparation system. The raw material preparation system is used to mix stachyose concentrated juice and purified water and adjust the sugar concentration to the first sugar concentration range. The first sugar concentration range refers to the sugar concentration range of the stachyose mixture, which is set to be about 10 °Brix, specifically 9 °Brix to 11 °Brix. This range is optimized to ensure that Eurotium cristatum has the best fermentation efficiency and the ability to selectively degrade non-target sugars during the subsequent fermentation process. Use a sugar concentration detection device (such as a refractometer or an on-line sugar sensor) to monitor the sugar concentration of the stachyose mixture in real time. The stachyose mixture is a solution containing stachyose and non-target sugars (such as fructose, sucrose, raffinose, mannotriose, etc.) that can be degraded by Eurotium cristatum. Eurotium cristatum is a microorganism that enriches stachyose by degrading non-target sugars during the fermentation process.

[0024] The specific operation steps can be as follows: Add stachyose concentrated juice with a sugar concentration of 50 °Brix to the fermentation tank, add an appropriate amount of purified water, stir evenly, dilute the system to a sugar concentration of about 10 °Brix, and use a refractometer to detect the diluted sugar concentration to ensure it is about 10 °Brix.

[0025] For example, add 500 g of stachyose concentrated juice with a content of 60% (mass percentage of stachyose in total sugar) (initial sugar concentration 50 °Brix) to a 5 L fermentation tank, then add 2000 g of purified water. After stirring evenly, detect the sugar concentration through a refractometer, and adjust it to 10 °Brix.

[0026] Step S200: After sterilizing the stachyose mixture, inoculate Eurotium cristatum at a first preset temperature to start fermentation and obtain an initial fermentation broth.

[0027] Specifically, use the heating and cooling system of the fermentation tank to perform high-temperature sterilization treatment on the stachyose mixture with adjusted sugar concentration (such as 121 °C, 15 minutes). After sterilization, cool the system to the first preset temperature through the cooling system. The first preset temperature refers to the preset fermentation start temperature during the fermentation process to ensure the best growth and metabolic activity of Eurotium cristatum. This temperature is optimized through experiments to ensure that the bacterial strain can quickly adapt to the environment and start fermentation after inoculation, such as 30 °C. When the system temperature reaches the first preset temperature, use an automatic inoculation device to inoculate the Eurotium cristatum bacterial strain (such as 200 mL of cultured bacterial liquid) to start the fermentation process.

[0028] For example, the diluted stachyose mixture is sterilized at 121°C for 15 minutes. After sterilization, the temperature of the fermentation broth is reduced to 30°C through a cooling system. At this time, the temperature sensor monitors the temperature of the fermentation broth in real time to ensure that it is stable at 30°C. Then, 200 mL of cultured Eurotium cristatum is inoculated to start fermentation.

[0029] Step S300: Monitor the change in the content ratio of stachyose and non-target sugars in the initial fermentation broth in real time by HPLC to obtain sugar content monitoring data.

[0030] Specifically, a high performance liquid chromatograph (HPLC) is used to monitor the stachyose and non-target sugars in the fermentation broth in real time. Among them, HPLC is an analytical instrument used to separate and detect the sugar components in the fermentation broth. The HPLC data is automatically collected and analyzed by the chromatographic workstation software to obtain sugar content monitoring data.

[0031] The specific operation steps can be as follows: 60 minutes after the start of fermentation, samples are regularly taken from the fermenter (for example, once every 20 minutes) and injected into the HPLC system. The HPLC system separates and detects stachyose and non-target sugars (fructose, sucrose, raffinose, mannotriose) according to the set chromatographic conditions. The chromatographic workstation software automatically records the detection results and calculates the change in the content ratio of each sugar.

[0032] In a possible implementation manner, the step of monitoring the change in the content ratio of stachyose and non-target sugars in the initial fermentation broth in real time by HPLC to obtain sugar content monitoring data, step S300 further includes step S310: Set up an HPLC on-line detection system in the fermenter. The HPLC on-line detection system includes a micro pump, an on-line filter and a detector. Specifically, install an HPLC on-line detection system in the fermenter. The HPLC on-line detection system includes a micro pump, an on-line filter and a detector, which are used to extract and detect the fermentation broth sample in real time. Ensure that the micro pump, the on-line filter and the detector are correctly connected, and calibrate the HPLC system to ensure the accuracy of the detection results.

[0033] Step S320: The micro pump extracts the initial fermentation broth at a preset time interval and a preset flow rate to obtain a fermentation broth sample. Specifically, set the time interval and flow rate of the micro pump, and the micro pump extracts the fermentation broth sample according to the set parameters. For example, set the micro pump to extract 1 mL of fermentation broth sample every 20 minutes.

[0034] Step S330: After the fermentation broth sample is subjected to solid impurity removal through the on-line filter, a standard fermentation broth sample is obtained. Specifically, the extracted fermentation broth sample is passed through an on-line filter to remove solid impurities, obtaining a filtered standard fermentation broth sample. For example, the fermentation broth sample is passed through an on-line filter with a pore size of 0.45 μm to obtain a standard fermentation broth sample after removing solid impurities.

[0035] Step S340: The detector detects the content ratio of stachyose and non-target saccharides in the standard fermentation broth sample, generating sugar content monitoring data. Specifically, the standard fermentation broth sample is injected into an HPLC detector. The HPLC system separates and detects each saccharide component according to the set chromatographic conditions. The chromatographic workstation software automatically records the detection results and calculates the content ratio of each saccharide. For example, the HPLC detector detects at a wavelength of 254 nm, the mobile phase is methanol-water (volume ratio 70:30), the flow rate is 1.0 mL / min, and the detection results show that the stachyose content gradually increases and the non-target saccharide content gradually decreases. This implementation method can, through the HPLC on-line detection system, monitor in real time the change in the content ratio of stachyose and non-target saccharides in the fermentation broth, thereby achieving precise control of the fermentation process. This real-time monitoring method can promptly detect abnormal situations during the fermentation process and dynamically adjust the fermentation conditions according to the monitoring data to ensure the efficient progress of the fermentation process.

[0036] Step S400: A membrane separation device is introduced to perform selective dialysis on the initial fermentation broth, obtaining membrane permeability monitoring data, including the change rate of stachyose retention concentration and the change value of membrane flux.

[0037] Specifically, an ultrafiltration or nanofiltration membrane device is used to perform selective dialysis on the fermentation broth, and the membrane flux and the change rate of stachyose retention concentration are monitored in real time through a flow meter and a concentration sensor. Specifically, the fermentation broth is introduced into the membrane separation device, and an appropriate operating pressure is set. The membrane flux is monitored in real time through a flow meter, and the stachyose retention concentration is monitored through a concentration sensor. The change value of the membrane flux and the change rate of the stachyose retention concentration are recorded to generate membrane permeability monitoring data for subsequent dynamic evaluation. For example, the fermentation broth is subjected to selective dialysis through a nanofiltration membrane with a molecular weight cut-off of 500 Da, and the operating pressure is set at 0.5 MPa.

[0038] Among them, the retention concentration of stachyose refers to the concentration of stachyose on the upstream side (retention side) of the membrane during the membrane separation process. The change rate refers to the change amount of the stachyose retention concentration per unit time, reflecting the enrichment efficiency of stachyose during the membrane separation process. During the membrane separation process, the concentration of stachyose on the upstream side of the membrane is monitored in real time through a concentration sensor, and the concentration value of stachyose is recorded at regular intervals. The change rate of the stachyose retention concentration is calculated by dividing the concentration difference between adjacent time points by the time interval. By monitoring the change rate of the stachyose retention concentration, the enrichment situation of stachyose can be understood in real time, providing data support for subsequent dynamic evaluation.

[0039] Among them, the membrane flux refers to the volume of liquid passing through a unit membrane area per unit time, expressed in L / m 2 ·h. The change value refers to the change amount of the membrane flux per unit time, reflecting the permeation situation of non-target saccharides during the membrane separation process. During the membrane separation process, the liquid flow rate passing through the membrane is monitored in real time through a flow meter, and the flow rate value is recorded at regular intervals. The membrane flux is calculated based on the flow rate and the membrane area. The change value of the membrane flux is calculated by dividing the membrane flux difference between adjacent time points by the time interval. By monitoring the change value of the membrane flux, the degradation and permeation situation of non-target saccharides can be understood in real time. The larger the change value of the membrane flux, the more the degradation and permeation of non-target saccharides, and the better the enrichment effect.

[0040] In a possible implementation, the introduced membrane separation device performs selective dialysis on the initial fermentation broth to obtain membrane permeability monitoring data. Step S400 further includes step S410, where a membrane separation device is arranged in the extracorporeal circulation pipeline of the fermenter. The membrane separation device includes a hollow fiber membrane module, a peristaltic pump, a first detector, and a second detector. Among them, the first detector is arranged in the retentate side circulation pipeline, and the second detector is arranged at the permeate side outlet. Specifically, the hollow fiber membrane module is installed in the extracorporeal circulation pipeline of the fermenter to ensure that the fermentation broth can undergo selective dialysis through the membrane module. The peristaltic pump is connected between the fermenter and the membrane module and is used to pump the fermentation broth into the membrane separation device at a preset flow rate. The first detector is arranged in the retentate side circulation pipeline and is used to monitor the stachyose concentration of the retentate in real time. The second detector is arranged at the permeate side outlet and is used to monitor the flow rate of the permeate in real time. A membrane separation device is installed in the extracorporeal circulation pipeline of the fermenter to ensure that the hollow fiber membrane module, the peristaltic pump, the first detector, and the second detector are correctly connected, and the detectors are calibrated to ensure the accuracy of the monitoring data. Among them, the hollow fiber membrane module is composed of many fine hollow fibers, which have a microporous structure that allows small molecules (such as degradation products of non-target sugars) to pass through, while large molecules (such as stachyose) are retained. The peristaltic pump pushes the liquid to flow by squeezing the hose, and the flow rate can be controlled by adjusting the pump speed. The first detector uses an optical or electrochemical method to measure the stachyose concentration in the retentate in real time. The second detector uses a flow sensor to measure the flow rate of the permeate in real time.

[0041] Step S420, the peristaltic pump pumps the initial fermentation broth into the membrane separation device at a preset flow rate, and selective dialysis is performed through the hollow fiber membrane module to obtain a retentate and a permeate. Specifically, set the flow rate of the peristaltic pump (for example, 100 mL / min). The peristaltic pump pumps the initial fermentation broth into the hollow fiber membrane module at the set flow rate. The fermentation broth passes through the hollow fiber membrane module, and the metabolites of non-target sugars degraded by Eurotium cristatum pass through the membrane, while stachyose is retained.

[0042] Step S430, the stachyose concentration data of the retentate is obtained in real time through the first detector, and the flow rate data of the permeate is obtained in real time through the second detector. Specifically, the first detector monitors the stachyose concentration of the retentate in real time, and the second detector monitors the flow rate of the permeate in real time, and the data of the stachyose concentration and the permeate flow rate are recorded.

[0043] Step S440: Calculate the change rate of stachyose retention concentration and the change value of membrane flux respectively based on the stachyose concentration data and the flow rate data. Specifically, calculate the change rate of stachyose retention concentration by dividing the difference in stachyose concentration between adjacent time points by the time interval. Calculate the change value of membrane flux by dividing the difference in permeate flow rate between adjacent time points by the time interval. This implementation method can monitor the change rate of membrane flux and stachyose retention concentration in real time through the membrane separation device. Combining with HPLC data, it can comprehensively monitor the enrichment of stachyose and the degradation of non-target sugars during the fermentation process, providing more comprehensive data support for the dynamic evaluation of stachyose enrichment, thereby optimizing the fermentation conditions and improving the enrichment efficiency and purity of stachyose.

[0044] Step S500: Conduct a dynamic evaluation of stachyose enrichment based on the sugar content monitoring data and the membrane permeability monitoring data, and generate a dynamic adjustment strategy for fermentation conditions based on the evaluation results.

[0045] Specifically, use a computer control system to process and analyze the HPLC monitoring data and the membrane permeability monitoring data. Based on a preset evaluation algorithm, conduct a dynamic evaluation of the stachyose enrichment effect. According to the evaluation results, automatically generate a fermentation condition adjustment strategy, such as adjusting the fermentation temperature, stirring speed, or dissolved oxygen content, etc.

[0046] As Figure 2 shown, in a possible implementation method, for the step of conducting a dynamic evaluation of stachyose enrichment based on the sugar content monitoring data and the membrane permeability monitoring data, and generating a dynamic adjustment strategy for fermentation conditions based on the evaluation results, step S500 further includes step S510: Calculate the real-time purity data of stachyose based on the sugar content monitoring data. Specifically, obtain the content data of stachyose and non-target sugars from the HPLC detector, and calculate the real-time purity of stachyose. The formula is: Real-time purity of stachyose = Content of stachyose / (Content of stachyose + Total content of non-target sugars).

[0047] Step S520: Calculate the correlation coefficient between the change rate of stachyose retention concentration and the change value of membrane flux based on the membrane permeability monitoring data. Specifically, obtain the change rate of stachyose retention concentration and the change value of membrane flux from the membrane separation device, and use statistical methods to calculate the correlation coefficient. The formula is: Correlation coefficient = Cov(X,Y) / (σ X σ Y ), where X is the change rate of stachyose retention concentration, Y is the change value of membrane flux, Cov(X,Y) is the covariance, σ X and σ YThe standard deviations of X and Y, respectively. The correlation coefficient reflects the correlation between the change rate of the stachyose retention concentration and the change value of the membrane flux. A higher correlation coefficient indicates a strong positive or negative correlation between the two. As a supplementary index for purity evaluation, if the correlation coefficient is high, it means that the change in membrane flux can better reflect the retention of stachyose, thereby enhancing the reliability of purity evaluation.

[0048] Step S530: Integrate the real-time purity data of the stachyose with the correlation coefficient to obtain a comprehensive purity evaluation value. Specifically, perform a joint analysis on the real-time purity data of the stachyose and the correlation coefficient, and adopt a multi-dimensional dynamic evaluation strategy to generate a more reliable comprehensive purity evaluation value. Specifically, according to the magnitude of the correlation coefficient, adjust the credibility weight of the real-time purity data of the stachyose to generate a comprehensive purity evaluation value. For example, if the correlation coefficient > 0.9 indicates a high degree of matching between the membrane separation process and fermentation degradation, the credibility of the HPLC data is increased, and the calculation formula for the comprehensive purity evaluation value can be, for example: Comprehensive purity evaluation value = real-time purity data of stachyose × 1.05 (slightly revised upward to enhance confidence); if the correlation coefficient < 0.5 indicates that there may be deviations in the membrane separation or fermentation process (such as a decrease in bacterial activity), the credibility of the HPLC data is reduced, and the calculation formula for the comprehensive purity evaluation value can be, for example: Comprehensive purity evaluation value = real-time purity data of stachyose × 0.9 (weight reduction treatment); if 0.5 ≤ correlation coefficient ≤ 0.9 indicates the normal range, the calculation formula for the comprehensive purity evaluation value can be, for example: Comprehensive purity evaluation value = real-time purity data of stachyose.

[0049] Step S540: Analyze the purity change trend based on the comprehensive purity evaluation value to obtain the real-time purity improvement rate of the stachyose. Specifically, through time series analysis, calculate the change trend of the stachyose purity. The calculation formula for the real-time purity improvement rate of the stachyose is: Real-time purity improvement rate of stachyose = (current comprehensive purity evaluation value - comprehensive purity evaluation value at the previous time point) / comprehensive purity evaluation value at the previous time point × 100%.

[0050] Step S550: If the real-time purity improvement rate of the stachyose is less than or equal to the preset improvement rate threshold, generate a dynamic adjustment strategy for fermentation conditions. Specifically, set a preset purity improvement rate threshold, compare the real-time purity improvement rate of the stachyose with the threshold. If the real-time purity improvement rate of the stachyose is less than or equal to the threshold, generate a dynamic adjustment strategy for fermentation conditions. This implementation method, by combining HPLC data and membrane permeability monitoring data, provides a more accurate and reliable method for evaluating the purity of stachyose. By dynamically correcting the purity data, real-time monitoring of the purity change trend, and adjusting the fermentation conditions as needed, it can significantly improve the enrichment efficiency and purity of stachyose, while enhancing the stability and repeatability of the fermentation process.

[0051] In a possible implementation, if the real-time purity improvement rate of stachyose is less than or equal to the preset improvement rate threshold, a dynamic adjustment strategy for fermentation conditions is generated. Step S550 further includes step S551, which conducts an attribution analysis on the purity change trend of stachyose to identify the key limiting sugars among the non-target sugars. Specifically, through statistical analysis methods, the key factors affecting the purity change of stachyose are identified to determine which non-target sugars have a significant impact on the improvement of stachyose purity. For example, assuming that through attribution analysis, it is found that the change in the content of fructose has a significant impact on the improvement of stachyose purity, then fructose is identified as the key limiting sugar.

[0052] Step S552, based on the degradation characteristics of Eurotium cristatum to non-target sugars, constructs an optimization model for fermentation conditions. Specifically, the degradation rates of Eurotium cristatum to fructose, sucrose, raffinose, and mannotriose are determined through experiments. According to the degradation characteristics, an optimization model for fermentation conditions is constructed. The input of the model is the key limiting sugar, and the output is the optimized fermentation conditions.

[0053] Step S553, based on the key limiting sugars, optimizes the fermentation conditions through the fermentation condition optimization model to generate a dynamic adjustment strategy for fermentation conditions. Specifically, the fermentation condition optimization model is used to calculate the optimal fermentation conditions according to the information of the key limiting sugars. According to the model output, a dynamic adjustment strategy for fermentation conditions is generated, such as adjusting the fermentation temperature or the ventilation volume, etc. This implementation method identifies the key limiting sugars that have a significant impact on the improvement of stachyose purity through attribution analysis, which can help adjust the fermentation conditions more accurately and improve the purity improvement efficiency.

[0054] In a possible implementation, for the attribution analysis on the purity change trend of stachyose to identify the key limiting sugars among the non-target sugars, step S551 further includes step S5511, which calculates the real-time purity data of non-target sugars according to the sugar content monitoring data. Specifically, the content data of stachyose and each non-target sugar are obtained from the HPLC detector, and the real-time purity of each non-target sugar is calculated. The formula is: real-time purity data of non-target sugars = content of non-target sugars / (content of stachyose + total content of non-target sugars).

[0055] Step S5512, based on the real-time purity data of non-target sugars, conducts a purity change trend analysis to obtain the real-time purity decline rate of non-target sugars. Specifically, through time series analysis, the change trend of the purity of each non-target sugar is calculated. The real-time purity decline rate of non-target sugars is calculated. The formula is: real-time purity decline rate of non-target sugars = (real-time purity data of non-target sugars at the previous time point - real-time purity data of non-target sugars at the current time point) / real-time purity data of non-target sugars at the previous time point × 100%.

[0056] Step S5513: Ascendingly sort the real-time purity decline rates of the non-target saccharides, and determine the non-target saccharide ranked first in the sorting as the key limiting saccharide. Specifically, ascendingly sort the real-time purity decline rates of all non-target saccharides, and determine the non-target saccharide ranked first in the sorting as the key limiting saccharide. For example, after ascendingly sorting the real-time purity decline rates of fructose, sucrose, raffinose, and mannotriose, it is found that the real-time purity decline rate of fructose is the lowest and ranks first, then fructose is determined as the key limiting saccharide. This implementation method can quantify the degradation rate of each non-target saccharide by analyzing the real-time purity decline rate of the non-target saccharides, thereby clearly identifying the non-target saccharide with the slowest degradation rate, and then specifically optimizing the fermentation conditions, reducing unnecessary adjustments, and improving the efficiency of stachyose purity improvement.

[0057] In a possible implementation method, based on the degradation characteristics of Eurotium cristatum to non-target saccharides, a fermentation condition optimization model is constructed. Step S552 further includes step S5521: Determine the degradation kinetic parameters of Eurotium cristatum to various non-target saccharides under different fermentation conditions through preliminary experiments, and establish the first response relationship, the second response relationship, and up to the Nth response relationship, where N is the number of types of non-target saccharides. Specifically, design preliminary experiments with different fermentation conditions, such as temperature (30°C, 32°C, 34°C), stirring speed (100 rpm, 150 rpm, 200 rpm), and dissolved oxygen content (20%, 30%, 40%). Under each condition, determine the degradation rate and efficiency of Eurotium cristatum to each non-target saccharide. According to the experimental data, establish the degradation kinetic model of each non-target saccharide, that is, the response relationship.

[0058] Step S5522: Based on the first response relationship, the second response relationship, and up to the Nth response relationship, construct the first fermentation condition optimization branch, the second fermentation condition optimization branch, and up to the Nth fermentation condition optimization branch. Specifically, analyze the degradation kinetic models of each non-target saccharide, and determine the degradation rate under different conditions. According to the experimental data, construct the fermentation condition optimization branch of each non-target saccharide.

[0059] Step S5523: Based on the degradation kinetic coupling relationship between the optimization branches, construct a cross-branch coordinated control mechanism. Specifically, by analyzing the mutual influence relationship between the degradation kinetic parameters of Eurotium cristatum to different non-target saccharides, establish a multi-objective collaborative regulation mechanism. First, identify the synergistic or antagonistic relationship between the degradation conditions of each saccharide (for example, increasing the temperature may promote the degradation of fructose but inhibit the degradation of raffinose), and then construct a dynamic weight allocation algorithm to dynamically adjust the priority of fermentation conditions according to the real-time monitored degradation rate of each saccharide, ensuring that the removal efficiency of other saccharides will not be significantly affected due to optimizing the degradation of a certain saccharide.

[0060] For example, when the system identifies fructose as the key limiting sugar, the initial strategy is to increase the temperature to 32 °C to accelerate its degradation. However, monitoring shows that the degradation rate of raffinose decreases by more than 20%. At this time, the coordination mechanism is activated: the temperature is adjusted back to 30 °C, and at the same time, the stirring speed is increased from 100 rpm to 150 rpm and the dissolved oxygen content is maintained at 30%. This adjustment keeps the fructose degradation rate at 90% of the optimized level, while the raffinose degradation rate recovers to 95% of the initial value, achieving a multi-objective balance.

[0061] Step S5524, integrate the first fermentation condition optimization branch, the second fermentation condition optimization branch up to the Nth fermentation condition optimization branch and the cross-branch coordination control mechanism to construct a fermentation condition optimization model. Specifically, systematically integrate the independent optimization branches of each non-target sugar and the cross-branch coordination control mechanism to construct a global optimization model. This model takes the key limiting sugar identification result and the degradation kinetic parameters of each sugar as inputs, calculates the optimal fermentation condition combination through a multi-objective optimization algorithm (such as the weighted summation method), and outputs a specific adjustment plan including parameters such as temperature, dissolved oxygen content, and stirring speed, to achieve the optimal control strategy for the current fermentation state. This implementation method can intelligently balance the degradation requirements of different sugars by constructing a fermentation condition optimization model containing a cross-branch coordination control mechanism, avoid significantly affecting the degradation efficiency of other non-target sugars while giving priority to dealing with key limiting sugars, and thus overall improve the enrichment efficiency of stachyose.

[0062] In a possible implementation manner, based on the key limiting sugar, optimize the fermentation conditions through the fermentation condition optimization model to generate a dynamic adjustment strategy for fermentation conditions. Step S553 further includes step S5531, based on the key limiting sugar, determine the Mth fermentation condition optimization branch, where the Mth fermentation condition optimization branch is the branch corresponding one-to-one to the key limiting sugar, and M is greater than or equal to 1 and less than or equal to N. Specifically, according to the identified key limiting sugar (such as fructose), select the corresponding Mth branch (such as the fructose fermentation condition optimization branch) from the N constructed fermentation condition optimization branches. Each branch corresponds strictly to a non-target sugar to ensure targeted optimization. For example, when fructose is identified as the key limiting sugar, the "fructose fermentation condition optimization branch" is automatically selected as the Mth branch, which contains all the kinetic parameters and response relationships of fructose degradation.

[0063] Step S5532: The Mth fermentation condition optimization branch optimizes the fermentation conditions according to the Mth response relationship and outputs the initial strategy for dynamic adjustment of fermentation conditions. Specifically, the selected Mth fermentation condition optimization branch calculates the optimal fermentation conditions based on its exclusive response relationship (the kinetic model established in step S5521). For example, the fructose fermentation condition optimization branch, based on the pre-experiment data, outputs the initial strategy under the current fermentation state (temperature 30°C, dissolved oxygen 20%): "Raise the temperature to 32°C and adjust the stirring speed to 120 rpm", which is expected to increase the fructose degradation rate by 25%.

[0064] Step S5533: According to the cross-branch coordination control mechanism, input the initial strategy for dynamic adjustment of fermentation conditions into the remaining N - 1 branches for simulation prediction, calculate the change amplitude of the degradation rate of each branch. If the predicted degradation rate decrease amplitude of any one of the N - 1 branches is greater than or equal to the preset amplitude threshold, generate a constraint condition. Specifically, input the initial strategy for dynamic adjustment of fermentation conditions into the remaining N - 1 branches (such as the sucrose, raffinose, and mannotriose branches) for simulation. Calculate the predicted degradation rate change through the response relationship of each branch. If the predicted degradation rate decrease of any branch ≥ the preset threshold (such as 10%), then generate a constraint condition. For example, the initial strategy for dynamic adjustment of fermentation conditions causes the predicted degradation rate of the raffinose branch to decrease by 15% (exceeding the 10% threshold), and the system generates a constraint condition: "The temperature adjustment amplitude shall not exceed +1.5°C".

[0065] Step S5534: Based on the constraint condition, optimize and adjust the initial strategy for dynamic adjustment of fermentation conditions until the predicted degradation rate decrease amplitude of any one of the N - 1 branches is less than the preset amplitude threshold, and generate the dynamic adjustment strategy for fermentation conditions. Specifically, re-optimize the initial strategy for dynamic adjustment of fermentation conditions under the restriction of the constraint condition. Through iterative calculation, find an adjustment plan that meets the degradation requirements of all branches. For example: First-round optimization: Temperature +2°C (initial) → Raffinose rate decreases by 15% (violation); Second-round optimization: Temperature +1.5°C → Raffinose rate decreases by 8% (qualified), but the fructose rate only increases by 18%; Final strategy: Temperature +1.5°C and at the same time dissolved oxygen +5%, making the fructose rate increase by 22% and the raffinose rate only decrease by 5%. This implementation method realizes the global optimal control of the stachyose purification process through multi-branch collaborative optimization, ensuring the maximization of the degradation efficiency of key limiting sugars (such as fructose) while intelligently restricting the negative impact on the degradation of other non-target sugars.

[0066] Step S600: Adjust and control the fermentation process according to the dynamic adjustment strategy for fermentation conditions.

[0067] Specifically, a PLC (Programmable Logic Controller) or DCS (Distributed Control System) is used to automatically adjust parameters such as the temperature of the fermenter. Among them, the actuators include heaters, coolers, agitators, ventilation valves, etc. Among them, the PLC is a device for industrial automation control, which can control the operating parameters of the fermenter according to a preset program; the DCS (Distributed Control System) is a system for complex industrial process control, which can centrally monitor and decentralized control multiple devices. For example, the PLC receives the dynamic adjustment strategy of fermentation conditions. According to the adjustment strategy, the PLC controls the heater or cooler to adjust the temperature of the fermenter to the set value, and / or controls the pH adjustment pump to add acid or alkali to adjust the pH to the set value, and / or adjusts the ventilation valve to adjust the ventilation volume to the set value, and / or controls the agitator to stir at the set speed to ensure that the fermentation broth is evenly mixed.

[0068] In a possible implementation manner, for the fermentation process adjustment and control according to the dynamic adjustment strategy of the fermentation conditions, step S600 further includes step S610 of arranging multi-parameter coupling sensors in the fermenter. Specifically, an integrated multi-parameter coupling sensor is deployed inside the fermenter. This sensor adopts a modular design and can synchronously collect key parameters such as temperature, dissolved oxygen (DO), and agitation speed, and transmit the data to the control system in real time through an industrial bus (such as RS485 or PROFIBUS). For example, an integrated sensor with a PT100 temperature probe, an optical dissolved oxygen electrode, and a Hall effect tachometer is installed at a height of 1 / 3 from the bottom of the tank to ensure the representativeness of the measurement. Among them, the temperature measurement range is 0~50°C, the accuracy is ±0.1°C, the dissolved oxygen measurement range is 0%~100% air saturation, the accuracy is ±0.5%, and the agitation speed measurement range is 0~300 rpm, the accuracy is ±1 rpm.

[0069] Step S620, the multi-parameter coupling sensor monitors the temperature, dissolved oxygen, and agitation speed in the fermenter in real time to obtain real-time fermentation condition monitoring data. Specifically, the multi-parameter coupling sensor continuously collects data at a frequency of 1 Hz, and generates structured real-time monitoring data after signal conditioning. The control system packs the temperature, DO, and agitation speed data into a unified data frame through timestamp alignment technology. For example, at a certain moment, the data frame shows: temperature 30.2°C, DO 25.3%, agitation speed 105 rpm, forming a deviation input with the target values (temperature 32°C, DO 30%, 120 rpm) of the dynamic adjustment strategy of the fermentation conditions. The data stream example is as follows: sensor → signal converter → PLC → data frame format: [timestamp][temperature][DO][rotation speed].

[0070] Step S630: According to the dynamic adjustment strategy of the fermentation conditions and the real-time fermentation condition monitoring data, adjust the fermentation conditions in the fermenter through a PID controller to perform fermentation process regulation and control. Specifically, a three-channel independent PID controller is adopted to process the deviation signals of temperature, DO, and stirring speed respectively. The PID controller calculates and outputs a control quantity based on the difference between the target value of the dynamic adjustment strategy of the fermentation conditions and the real-time fermentation condition monitoring data. For example, for temperature control, the duty cycle of the heating jacket (0% - 100%) is adjusted through PID output. When the measured temperature is 30.2°C and the target temperature is 32°C, the output heating power is 75%. For DO control, the PID adjusts the opening degree of the intake valve and the stirring compensation. When the measured DO is 25.3% and the target DO is 30%, the solenoid valve is opened to 60% and the stirring speed is increased to 115 rpm. When the DO response lags, a feedforward control is started to increase the stirring speed 10 seconds in advance. If the sensor data mutates (such as a sudden 10% drop in DO), the Kalman filter algorithm is triggered to eliminate noise, and at the same time, the redundant sensor verification is started to ensure control reliability. This implementation method realizes the real-time and precise regulation of the fermentation conditions through the closed-loop linkage of multi-parameter coupled sensing and intelligent PID control, improving the fermentation stability and product consistency.

[0071] In a possible implementation manner, after performing the fermentation process regulation and control according to the dynamic adjustment strategy of the fermentation conditions, the method further includes: when the stachyose purity in the sugar content monitoring data is greater than or equal to a first preset purity, and the non-target sugar purity is less than or equal to a second preset purity, terminate the fermentation to obtain a high-purity fermentation broth; after performing sterilization treatment on the high-purity fermentation broth, control the system temperature to be less than or equal to a second preset temperature, and perform precipitation and decolorization treatment through activated carbon to obtain a first purified liquid; pass the first purified liquid through an ultrafiltration membrane for impurity and bacteria removal treatment to obtain a second purified liquid; pass the second purified liquid through a nanofiltration membrane for desalting and removing impurity sugars and then concentrate it to a second sugar concentration range to obtain a concentrated fermentation broth; after performing spray drying treatment on the concentrated fermentation broth, obtain stachyose dry powder with a stachyose purity greater than or equal to a third preset purity.

[0072] Specifically, the fermentation is terminated when the system detects that the preset purity threshold is reached. The first preset purity refers to the lowest target percentage of stachyose in the total sugar content, which is determined through previous experiments and can ensure the economy and feasibility of subsequent purification processes (for example, set to 97%). The second preset purity refers to the highest allowable residual ratio of non-target sugars in the total sugar, which is set according to the final product specification requirements (for example, ≤0.5%). When HPLC monitoring shows that the stachyose purity ≥ the first preset purity and the non-target sugar purity ≤ the second preset purity, the fermentation is immediately terminated. The control system will record this as the optimal harvest point and automatically turn off the stirring and ventilation, and start the subsequent treatment procedure.

[0073] Sterilize the system where fermentation has terminated. The second preset temperature refers to the highest safe temperature to be reached in the post-sterilization cooling process, which should be able to maintain product stability while avoiding degradation of heat-sensitive components (for example, set at 45°C). For example, during the treatment, an instant high-temperature sterilization process is used, maintaining at 90°C (allowing a ±2°C fluctuation) for 30 - 50 seconds, and then immediately cooling to ≤ the second preset temperature. These process parameters are determined through microbial validation tests, which can ensure the sterilization effect while maximizing the retention of active ingredients.

[0074] Perform decolorization and purification on the sterilized system. The first purified liquid refers to the intermediate product obtained after the decolorization treatment. During the treatment, food-grade activated carbon is added at a ratio of 0.1 - 0.5% weight / volume (i.e., 0.1 - 0.5 g / 100 mL), preferably 0.4%, and stirred at a temperature below the second preset temperature for 20 - 40 minutes (preferably 30 minutes). After decolorization, the carbon residue is removed through a pre-filter. For example, after a certain batch is treated with 0.2% activated carbon for 30 minutes, the color value of the system drops from 1500 IU to below 50 IU, meeting the standard of the first purified liquid.

[0075] Perform membrane separation on the first purified liquid to obtain the second purified liquid. The ultrafiltration membrane refers to a separation membrane with a molecular weight cut-off in the range of 1 - 100 kDa (preferably 10 kDa). During operation, the pressure is controlled at 0.1 - 0.5 MPa (preferably 0.3 MPa), and the temperature is maintained at 20 - 40°C. Through this step, macromolecular impurities and microorganisms can be removed, reducing the turbidity of the system to below 0.1 NTU, meeting the requirements of the second purified liquid.

[0076] Concentrate and purify the second purified liquid. The second sugar degree range refers to the target concentration range of the final concentrated liquid (for example, 20 - 30°Brix, preferably 25°Brix). A nanofiltration membrane with a molecular weight cut-off of 200 - 800 Da (preferably 500 Da) is used and operated at 0.3 - 0.7 MPa (preferably 0.5 MPa). This step can simultaneously achieve the triple effects of desalination, removing impurity sugars, and concentration. For example, when a certain batch is concentrated to 25.3°Brix, the conductivity drops to below 50 μS / cm.

[0077] Dry the concentrated fermentation broth to obtain the final product. The third preset purity refers to the minimum purity standard of the finished stachyose dry powder (for example, ≥95%, preferably ≥96%). During spray drying, the inlet temperature is controlled at 160 - 200°C (preferably 180°C), and the outlet temperature is 70 - 80°C (preferably 75°C). The water content of the obtained dry powder is ≤5% (preferably ≤3.5%). For example, a certain batch obtains stachyose dry powder with a purity of 96.3%. This implementation method realizes the efficient conversion from fermentation broth to high-purity stachyose dry powder by intelligently controlling the fermentation end point and optimizing the multi-stage purification process, ensuring the efficiency and stability of the entire process.

[0078] In the embodiments of the present application, technical means such as real-time monitoring of the content ratio change of saccharide substances in the fermentation broth by HPLC, obtaining membrane permeation rate monitoring data using a membrane separation device, and dynamically evaluating the enrichment of stachyose based on these monitoring data, and then generating a dynamic adjustment strategy for fermentation conditions are adopted, which solves the technical problems existing in the existing fermentation and purification of stachyose, such as the inability to accurately monitor and dynamically adjust the fermentation conditions in real time, resulting in low fermentation efficiency and low purity, and achieves the technical effect of improving the fermentation efficiency and purity of stachyose by intelligently controlling the fermentation process.

[0079] The above specific embodiments do not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of the present application shall be included within the protection scope of the present application. In some cases, the actions or steps recorded in the present application can be executed in a different order from that in the embodiments and still achieve the desired results. Additionally, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. An intelligent control and regulation method for high-precision fermentation and purification of stachyose, characterized in that, The method includes: Obtaining a stachyose mixture in a first sugar concentration range, where the stachyose mixture contains stachyose and non-target sugars that can be degraded by Eurotium cristatum; After sterilizing the stachyose mixture, inoculating Eurotium cristatum at a first preset temperature to initiate fermentation to obtain an initial fermentation broth; Real-time monitoring of the content ratio changes of stachyose and non-target sugars in the initial fermentation broth by HPLC to obtain sugar content monitoring data; Introducing a membrane separation device to perform selective dialysis on the initial fermentation broth to obtain membrane permeability monitoring data, including the change rate of stachyose retention concentration and the change value of membrane flux; Performing dynamic evaluation of stachyose enrichment based on the sugar content monitoring data and the membrane permeability monitoring data, and generating a dynamic adjustment strategy for fermentation conditions based on the evaluation results; Adjusting and controlling the fermentation process according to the dynamic adjustment strategy for fermentation conditions.

2. The intelligent control and adjustment method for high-precision fermentation and purification of stachyose as described in claim 1, wherein, The performing dynamic evaluation of stachyose enrichment based on the sugar content monitoring data and the membrane permeability monitoring data, and generating a dynamic adjustment strategy for fermentation conditions includes: Calculating real-time purity data of stachyose based on the sugar content monitoring data; Calculating the correlation coefficient between the change rate of stachyose retention concentration and the change value of membrane flux based on the membrane permeability monitoring data; Fusing the real-time purity data of stachyose with the correlation coefficient to obtain a comprehensive purity evaluation value; Performing analysis on the purity change trend according to the comprehensive purity evaluation value to obtain the real-time purity improvement rate of stachyose; If the real-time purity improvement rate of stachyose is less than or equal to a preset improvement rate threshold, generating a dynamic adjustment strategy for fermentation conditions.

3. The intelligent control and adjustment method for high-precision fermentation and purification of stachyose according to claim 2, characterized in that, The if the real-time purity improvement rate of stachyose is less than or equal to a preset improvement rate threshold, generating a dynamic adjustment strategy for fermentation conditions includes: Performing attribution analysis on the purity change trend of stachyose to identify the key limiting sugars in the non-target sugars; Constructing a fermentation condition optimization model based on the degradation characteristics of Eurotium cristatum for non-target sugars; Based on the key limiting sugars, optimizing the fermentation conditions through the fermentation condition optimization model to generate a dynamic adjustment strategy for fermentation conditions.

4. The intelligent control and adjustment method for high-precision fermentation and purification of stachyose according to claim 3, characterized in that, The performing attribution analysis on the purity change trend of stachyose to identify the key limiting sugars in the non-target sugars includes: Calculating real-time purity data of non-target sugars based on the sugar content monitoring data; Performing analysis on the purity change trend according to the real-time purity data of non-target sugars to obtain the real-time purity decrease rate of non-target sugars; Arranging the real-time purity decrease rates of the non-target sugars in ascending order, and determining the non-target sugar ranked first as the key limiting sugar.

5. The intelligent control and adjustment method for high-precision fermentation and purification of stachyose according to claim 3, characterized in that, The constructing a fermentation condition optimization model based on the degradation characteristics of Eurotium cristatum for non-target sugars includes: Determining the degradation kinetic parameters of Eurotium cristatum for various non-target sugars under different fermentation conditions through preliminary experiments, and establishing the first response relationship, the second response relationship until the Nth response relationship, where N is the number of types of non-target sugars; Based on the first response relationship, the second response relationship until the Nth response relationship, constructing the first fermentation condition optimization branch, the second fermentation condition optimization branch until the Nth fermentation condition optimization branch; Construct a cross-branch coordinated control mechanism based on the degradation kinetic coupling relationship among the optimization branches; Integrate the first fermentation condition optimization branch, the second fermentation condition optimization branch up to the Nth fermentation condition optimization branch and the cross-branch coordinated control mechanism to construct a fermentation condition optimization model.

6. The intelligent control and regulation method for high-precision fermentation and purification of stachyose according to claim 5, characterized in that Based on the key limiting sugars, optimize the fermentation conditions through the fermentation condition optimization model to generate a dynamic adjustment strategy for fermentation conditions, including: Based on the key limiting sugars, determine the Mth fermentation condition optimization branch, where the Mth fermentation condition optimization branch is the branch corresponding one-to-one to the key limiting sugars, and M is greater than or equal to 1 and less than or equal to N; The Mth fermentation condition optimization branch optimizes the fermentation conditions according to the Mth response relationship and outputs an initial dynamic adjustment strategy for fermentation conditions; According to the cross-branch coordinated control mechanism, input the initial dynamic adjustment strategy for fermentation conditions into the remaining N-1 branches for simulation prediction, calculate the change amplitude of the degradation rate of each branch, and if the predicted degradation rate decrease amplitude of any N-1 branch is greater than or equal to the preset amplitude threshold, generate a constraint condition; Based on the constraint condition, optimize and adjust the initial dynamic adjustment strategy for fermentation conditions until the predicted degradation rate decrease amplitude of any N-1 branch is less than the preset amplitude threshold, and generate a dynamic adjustment strategy for fermentation conditions.

7. The intelligent control and regulation method for high-precision fermentation and purification of stachyose according to claim 1, characterized in that, The content ratio change of stachyose and non-target sugars in the initial fermentation broth is monitored in real time by HPLC to obtain sugar content monitoring data, including: Set an HPLC on-line detection system in the fermentation tank, and the HPLC on-line detection system includes a micro pump, an on-line filter and a detector; The micro pump extracts the initial fermentation broth at a preset time interval and a preset flow rate to obtain a fermentation broth sample; The fermentation broth sample is subjected to solid impurity removal through the on-line filter to obtain a standard fermentation broth sample; The detector detects the content ratio of stachyose and non-target sugars in the standard fermentation broth sample to generate sugar content monitoring data.

8. The intelligent control and adjustment method for high-precision fermentation and purification of stachyose according to claim 1, characterized in that Introduce a membrane separation device to perform selective dialysis on the initial fermentation broth to obtain membrane permeability monitoring data, including: Set a membrane separation device in the external circulation pipeline of the fermentation tank. The membrane separation device includes a hollow fiber membrane module, a peristaltic pump, a first detector and a second detector. Among them, the first detector is arranged on the retentate side circulation pipeline, and the second detector is arranged at the permeate side outlet; The peristaltic pump pumps the initial fermentation broth into the membrane separation device at a preset flow rate, and performs selective dialysis through the hollow fiber membrane module to obtain a retentate and a permeate; Obtain the stachyose concentration data of the retentate in real time through the first detector, and obtain the flow rate data of the permeate in real time through the second detector; Calculate the change rate of the stachyose retention concentration and the membrane flux change value respectively according to the stachyose concentration data and the flow rate data.

9. The intelligent control and adjustment method for high-precision fermentation and purification of stachyose as claimed in claim 1, wherein, The fermentation process is regulated and controlled according to the dynamic adjustment strategy of the fermentation conditions, including: Arrange multi-parameter coupling sensors in the fermentation tank; The multi-parameter coupling sensors monitor the temperature, dissolved oxygen and stirring speed in the fermentation tank in real time to obtain real-time fermentation condition monitoring data; According to the dynamic adjustment strategy of the fermentation conditions and the real-time fermentation condition monitoring data, the fermentation conditions in the fermenter are adjusted by a PID controller to carry out fermentation process regulation and control.

10. The intelligent control and adjustment method for high-precision fermentation and purification of stachyose according to claim 1, characterized in that, After carrying out fermentation process regulation and control according to the dynamic adjustment strategy of the fermentation conditions, it further includes: When the purity of stachyose in the sugar content monitoring data is greater than or equal to the first preset purity and the purity of non-target sugars is less than or equal to the second preset purity, the fermentation is terminated to obtain a high-purity fermentation broth; After sterilizing the high-purity fermentation broth, the system temperature is controlled to be less than or equal to the second preset temperature, and precipitation and decolorization treatment are carried out with activated carbon to obtain a first purified liquid; The first purified liquid is subjected to impurity and bacteria removal treatment through an ultrafiltration membrane to obtain a second purified liquid; The second purified liquid is subjected to desalting and non-target sugar removal treatment through a nanofiltration membrane and then concentrated to the second sugar concentration range to obtain a concentrated fermentation broth; After spray-drying the concentrated fermentation broth, stachyose dry powder with a stachyose purity greater than or equal to the third preset purity is obtained.

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