Chitosan oligosaccharide fermentation control method and system

Abstract

The present invention relates to a chitosan oligosaccharide fermentation control method and system, and relates to the technical field of fermentation control, including: obtaining a fermentation control parameter space, randomly generating multiple initial fermentation control parameters, performing chitosan dissolution analysis according to the initial pH and initial chitosan concentration in the initial fermentation control parameters, obtaining multiple initial chitosan dissolution parameters, performing contact analysis between enzyme and chitosan, obtaining multiple initial chitosan contact parameters, performing contact analysis between enzyme and oxygen, obtaining multiple initial oxygen contact parameters, respectively combining multiple initial fermentation times to perform chitosan oligosaccharide fermentation prediction, obtaining multiple fermentation yield parameters and multiple overdecomposition parameters, and calculating multiple initial fermentation fitnesses; continuing to perform iterative optimization of fermentation control parameters, obtaining optimal fermentation control parameters, and performing chitosan oligosaccharide fermentation control. The present invention achieves the technical effect of considering the contact between enzyme, chitosan and oxygen, optimizing chitosan fermentation control and improving fermentation effect.

Description

Technical Field

[0001] The invention relates to the technical field of fermentation control, and in particular to a chitosan oligosaccharide fermentation control method and system. Background Art

[0002] Chitosan is a natural polysaccharide extracted from chitin, which is widely found in the shells of crustaceans. Chitosan can be partially degraded to produce chitooligosaccharides, which have been widely used in food, medicine, agriculture and other fields due to their unique biological activities, such as antibacterial, antioxidant and immunomodulatory effects.

[0003] During the fermentation of chitosan oligosaccharides, the solubility and degradation efficiency of chitosan directly affect the production and quality of chitosan oligosaccharides. For example, when the chitosan concentration is high, the solution viscosity increases, the mass transfer resistance increases, and the contact between the enzyme and chitosan is insufficient. The high viscosity also affects the oxygen transfer efficiency during the fermentation process, thereby affecting the metabolic activity of microorganisms and the catalytic efficiency of oxygen-dependent enzymes. The prior art chitosan oligosaccharide fermentation control generally simply adjusts the control variables without considering the contact between the enzyme, chitosan and oxygen, resulting in poor chitosan oligosaccharide fermentation effect. Summary of the invention

[0004] The invention aims to solve the technical problem that the chitosan oligosaccharide fermentation control in the prior art does not take into account the contact between enzyme, chitosan and oxygen, resulting in poor chitosan oligosaccharide fermentation effect.

[0005] In a first aspect, the present invention provides a chitosan oligosaccharide fermentation control method, comprising: obtaining a fermentation control parameter space for producing chitosan oligosaccharides by fermentation based on chitosan, randomly generating a plurality of initial fermentation control parameters in the fermentation control parameter space, performing chitosan dissolution analysis according to an initial pH and an initial chitosan concentration in each initial fermentation control parameter, and obtaining a plurality of initial chitosan dissolution parameters, wherein the fermentation control parameters include chitosan concentration, pH and fermentation time;

[0006] According to the multiple initial chitosan dissolution parameters, performing a contact analysis between the enzyme and chitosan to obtain multiple initial chitosan contact parameters, and performing a contact analysis between the enzyme and oxygen to obtain multiple initial oxygen contact parameters;

[0007] According to the multiple initial chitosan contact parameters and the multiple initial oxygen contact parameters, respectively combined with multiple initial fermentation times, chitosan oligosaccharide fermentation prediction is performed to obtain multiple fermentation yield parameters and multiple overdecomposition parameters, and multiple initial fermentation fitnesses are calculated;

[0008] Continue to iterate and optimize the fermentation control parameters. During the optimization process, calculate the comprehensive contact parameters according to the chitosan contact parameters and the oxygen contact parameters. Select and exchange the fermentation control parameters according to the comprehensive contact parameters until the optimization converges and obtains the optimal fermentation control parameters for chitosan oligosaccharide fermentation control.

[0009] In a second aspect, the present invention provides a chitosan oligosaccharide fermentation control system, the system comprising:

[0010] An initial dissolution analysis module is used to obtain a fermentation control parameter space for producing chitosan oligosaccharides by fermentation based on chitosan, randomly generate multiple initial fermentation control parameters in the fermentation control parameter space, and perform chitosan dissolution analysis according to the initial pH and initial chitosan concentration in each initial fermentation control parameter to obtain multiple initial chitosan dissolution parameters, wherein the fermentation control parameters include chitosan concentration, pH and fermentation time;

[0011] A contact analysis module, for performing a contact analysis between the enzyme and chitosan according to the multiple initial chitosan dissolution parameters to obtain multiple initial chitosan contact parameters, and performing a contact analysis between the enzyme and oxygen to obtain multiple initial oxygen contact parameters;

[0012] A fitness acquisition module, for predicting chitosan oligosaccharide fermentation according to the multiple initial chitosan contact parameters and the multiple initial oxygen contact parameters, respectively in combination with multiple initial fermentation times, obtaining multiple fermentation yield parameters and multiple overdecomposition parameters, and calculating multiple initial fermentation fitnesses;

[0013] The fermentation optimization module is used to continue the iterative optimization of the fermentation control parameters. During the optimization process, the comprehensive contact parameters are calculated according to the chitosan contact parameters and the oxygen contact parameters. The fermentation control parameters are selected and exchanged according to the comprehensive contact parameters until the optimization converges and the optimal fermentation control parameters are obtained to control the chitosan oligosaccharide fermentation.

[0014] In a third aspect, the present invention provides an electronic device, comprising: a memory for storing a computer software program; and a processor for reading and executing the computer software program, thereby realizing the chitosan oligosaccharide fermentation control method of the first aspect.

[0015] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer software program stored therein, and when the computer software program is executed by a processor, the chitosan oligosaccharide fermentation control method of the first aspect is implemented.

[0016] The present invention, through one or more technical schemes mentioned above, randomly generates multiple initial fermentation control parameters in the fermentation control parameter space, and performs chitosan dissolution analysis according to each initial parameter to obtain multiple initial chitosan dissolution parameters. This process can effectively solve the problem of insufficient chitosan dissolution, thereby improving the contact efficiency between chitosan and enzyme. On this basis, by analyzing the contact between enzyme and chitosan, multiple chitosan contact parameters are obtained to ensure that the enzyme and chitosan are in full contact, significantly improve the degradation rate of chitosan, and thus improve the production efficiency of chitosan oligosaccharides. At the same time, oxygen contact analysis is also performed to obtain multiple initial oxygen contact parameters, optimize the transfer efficiency of oxygen and chitosan, ensure that the activity of microorganisms and enzymes is maintained during the fermentation process, and improve the fermentation effect. By combining multiple initial chitosan contact parameters and initial oxygen contact parameters, and further combining fermentation time to predict chitosan oligosaccharide fermentation, multiple fermentation yield parameters and over-decomposition parameters are obtained, and by calculating the initial fermentation fitness, the fermentation control parameters are iteratively optimized, and finally the optimal fermentation control parameters are obtained. The present invention improves the stability and efficiency of the fermentation process through dynamic adjustment and optimization, prevents excessive degradation of chitosan oligosaccharides, ensures the quality and yield of the product, and thus significantly improves the fermentation control production effect of chitosan oligosaccharides. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A schematic diagram of a chitosan oligosaccharide fermentation control method provided by an embodiment of the present invention;

[0018] Figure 2 A schematic diagram of the structure of a chitosan oligosaccharide fermentation control system provided by an embodiment of the present invention;

[0019] Figure 3 A functional block diagram of an electronic device provided by an embodiment of the present invention;

[0020] Figure 4 A principle block diagram of the computer-readable storage medium provided by the present invention.

[0021] In the accompanying drawings, the components represented by the reference numerals are listed as follows:

[0022] An initial dissolution analysis module 11 , a contact analysis module 12 , a fitness acquisition module 13 , a fermentation optimization module 14 , an electronic device 100 , a memory 110 , a processor 120 , a computer program 111 , and a computer-readable storage medium 200 . DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0024] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, "plurality" means two or more, unless otherwise clearly and specifically defined.

[0025] In the description of the present application, the term "for example" is used to mean "used as an example, illustration or description". Any embodiment described as "for example" in the present application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any technician in the field to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes will not be elaborated in detail to avoid unnecessary details to obscure the description of the present invention. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in the present application.

[0026] Example 1

[0027] like Figure 1 As shown, the embodiment of the present invention provides a chitosan oligosaccharide fermentation control method, comprising the following steps.

[0028] S10: obtaining a fermentation control parameter space for producing chitosan oligosaccharides by fermentation based on chitosan, randomly generating a plurality of initial fermentation control parameters in the fermentation control parameter space, performing chitosan dissolution analysis according to an initial pH and an initial chitosan concentration in each initial fermentation control parameter, and obtaining a plurality of initial chitosan dissolution parameters, wherein the fermentation control parameters include chitosan concentration, pH and fermentation time;

[0029] In the embodiment of the present application, a fermentation control parameter space is first defined, and the fermentation control parameter space includes the adjustment range of the fermentation control parameters for producing chitosan oligosaccharides by fermentation of chitosan. The fermentation control parameters include three main variables: chitosan concentration, pH, and fermentation time. Therefore, the fermentation control parameter space includes the adjustment intervals of chitosan concentration, pH, and fermentation time.

[0030] Among them, other fermentation parameters affecting fermentation can be set based on control variables by those skilled in the art, such as controlling chitosan concentration, pH and fermentation time, while keeping other fermentation parameters the same, such as controlling the temperature to 50°C and selecting Bacillus cereus as the fermentation strain.

[0031] A plurality of initial fermentation control parameters are randomly generated in the fermentation control parameter space, and each control parameter combination represents a specific fermentation condition, wherein each initial fermentation control parameter includes the initial concentration of chitosan, the pH value of the fermentation environment, and the fermentation duration.

[0032] After generating a plurality of initial fermentation control parameters, chitosan dissolution analysis is performed according to the combination of each initial fermentation control parameter, that is, the dissolution of chitosan is evaluated according to the set initial pH value and chitosan concentration. Because the solubility of chitosan directly affects the efficiency of subsequent enzymatic degradation, if chitosan cannot be fully dissolved, the contact between enzyme and chitosan will be limited, resulting in a decrease in the efficiency of chitosan oligosaccharide production. Through dissolution analysis, a plurality of initial chitosan dissolution parameters are obtained. For example, the initial chitosan dissolution parameters include the solubility of chitosan, the viscosity of the solution, etc., which can be used to evaluate the dissolution behavior of chitosan under different fermentation conditions.

[0033] Step S10 in the method provided in the embodiment of the present application includes:

[0034] Obtaining the chitosan concentration range, pH range and fermentation time range for producing chitooligosaccharides by fermentation based on chitosan;

[0035] Based on the chitosan concentration range, pH range and fermentation time range, a fermentation control parameter space is generated.

[0036] In the examples of the present application, three key parameter ranges affecting the fermentation process are selected and determined: chitosan concentration range, pH range and fermentation time range. These parameters directly determine the overall reaction environment and fermentation effect of the fermentation process.

[0037] The chitosan concentration range refers to the initial concentration of the chitosan solution during the fermentation process. The chitosan concentration has a significant effect on the viscosity of the solution, the mass transfer efficiency of the enzyme, and the final chitosan oligosaccharide production. Too high a chitosan concentration will increase the viscosity of the solution and affect the contact between the enzyme and the substrate, while too low a concentration may result in insufficient chitosan oligosaccharide production. For example, the chitosan concentration range is 10g / L to 30g / L, or 0.5%-3%.

[0038] The pH value determines the solubility of chitosan and the activity of enzymes. Chitosan dissolves more easily in an acidic environment, while enzymes are most active within a specific pH range. For example, the pH range is between 4.5 and 8.

[0039] The fermentation time range refers to the time required for the fermentation process. If the fermentation time is too short, chitosan cannot be fully degraded into chitooligosaccharides; if the time is too long, chitooligosaccharides may be excessively degraded into smaller oligosaccharides or even monosaccharides. For example, the fermentation time range is between 24 hours and 72 hours.

[0040] Based on the determined chitosan concentration range, pH range and fermentation time range, a fermentation control parameter space of all possible fermentation condition combinations is formed. The fermentation control parameter space contains all possible combinations of chitosan concentration, pH and fermentation time during the fermentation process, and each combination is a fermentation control parameter. Multiple initial fermentation control parameters are randomly generated in the fermentation control parameter space as the first generation solution for optimizing the chitosan oligosaccharide fermentation control parameters and optimizing the control of the fermentation process.

[0041] By constructing the fermentation control parameter space and combining experimental data with model calculations, a comprehensive optimization plan can be provided for the fermentation process to ensure that chitosan is fermented under optimal conditions and to maximize the yield and quality of chitosan oligosaccharides.

[0042] Step S10 in the method provided in the embodiment of the present application includes:

[0043] Randomly generate a plurality of initial fermentation control parameters in the fermentation control parameter space, each of which includes an initial chitosan concentration, an initial pH and an initial fermentation time;

[0044] According to the historical chitosan oligosaccharide fermentation data, the sample chitosan concentration set and sample pH set were collected, and the viscosity of the chitosan solution at different sample chitosan concentrations and sample pH was collected, and the sample chitosan dissolution parameter set was obtained by annotation;

[0045] Using the sample chitosan concentration set, the sample pH set and the sample chitosan dissolution parameter set, constructing a chitosan dissolution classifier;

[0046] The chitosan dissolution classifier is used to classify the chitosan dissolution of the initial pH and the initial chitosan concentration within each initial fermentation control parameter to obtain a plurality of initial chitosan dissolution parameters.

[0047] In the embodiment of the present application, a plurality of initial fermentation control parameters are randomly generated in the defined fermentation control parameter space, each of which includes an initial chitosan concentration, an initial pH and an initial fermentation time.

[0048] Based on the historical chitosan oligosaccharide fermentation data, the chitosan concentration and pH in the chitosan oligosaccharide fermentation data in the historical time were collected to obtain the sample chitosan concentration set and the sample pH set. Furthermore, the viscosity of the chitosan solution under different sample chitosan concentrations and pH conditions was measured. The viscosity of the chitosan solution reflects the solubility of chitosan under different concentrations and pH conditions. The viscosity of the chitosan solution was marked as the sample chitosan dissolution parameter to form a sample chitosan dissolution parameter set. The viscosity of the chitosan solution will affect the degree of contact between the enzyme and chitosan and oxygen during the fermentation process, thereby affecting the fermentation effect.

[0049] For example, the sample chitosan concentration includes 1.2%, 2.0%, and 1.5%, and the sample pH includes 5.5, 6.0, and 4.8. The corresponding chitosan solution viscosities under different sample chitosan concentrations and pH conditions include 120 cP, 250 cP, and 200 cP, which are marked as sample chitosan dissolution parameters to form a sample chitosan dissolution parameter set.

[0050] Furthermore, a chitosan dissolution classifier is constructed based on the sample chitosan concentration set, the sample pH set and the sample chitosan dissolution parameter set. The classifier uses the sample chitosan concentration set, the sample pH set and the corresponding dissolution parameter set to form a classification model that can identify the dissolution state of the chitosan solution under different fermentation conditions through data construction. The chitosan dissolution classifier can classify and obtain the dissolution parameters of chitosan according to the input initial chitosan concentration and initial pH, thereby providing a reference for the control of the fermentation process.

[0051] Exemplarily, the chitosan concentration of the sample is used as the primary classification node, the pH of the sample is used as the secondary classification node, and the chitosan dissolution parameter of the sample is used as the classification output to construct a chitosan dissolution classifier. When the initial chitosan concentration and the initial pH are input, the initial chitosan concentration can be classified into the corresponding chitosan concentration interval, and the initial pH can be classified into the corresponding pH interval, and then the chitosan dissolution parameters corresponding to the chitosan concentration interval and the pH interval are obtained and output.

[0052] Optionally, a chitosan dissolution classifier can also be constructed based on a BP (back propagation) neural network. The constructed chitosan dissolution classifier uses a Sigmoid function, a sample chitosan concentration set, and a sample pH set as input data. The input data is transmitted layer by layer, from the input layer to the hidden layer and then to the output layer, and the output value of each node is calculated. The linear input is converted into a nonlinear output through an activation function. Then the error between the predicted output and the true label is calculated, and the true label is the sample chitosan dissolution parameter set. The mean square error (MSE) or cross entropy loss is usually used as a loss function. Further, according to the error of the loss function, the error is back-propagated from the output layer to the hidden layer and the input layer through the BP algorithm, and the weights and biases of each layer are updated. The weights are adjusted by the gradient descent algorithm to gradually reduce the error. The weights are updated by the back propagation algorithm, and the optimization algorithms such as stochastic gradient descent (SGD), Adam and other algorithms are used to optimize the model, so that the neural network gradually converges and the error continues to decrease. Until the error is less than the requirement, such as 5%, the training converges, and the chitosan dissolution classifier is obtained. The trained chitosan dissolution classifier can analyze and output the corresponding initial chitosan dissolution parameters according to the input initial pH and initial chitosan concentration. For example, when the input initial chitosan concentration and initial pH are 1.2% and 5.5, the output chitosan dissolution parameter is viscosity 120 cP.

[0053] The constructed chitosan dissolution classifier is used to input the initial pH and initial chitosan concentration in each initial fermentation control parameter into chitosan dissolution classification, and a plurality of initial chitosan dissolution parameters are obtained.

[0054] Multiple initial chitosan dissolution parameters are used to determine the solubility of chitosan under different fermentation conditions, helping to optimize the contact efficiency between enzyme and chitosan and the oxygen mass transfer efficiency. By accurately analyzing the dissolution state of chitosan under each initial fermentation control parameter, the fermentation process can be precisely adjusted to improve the fermentation efficiency and the final yield of chitosan oligosaccharides.

[0055] S20: performing a contact analysis between the enzyme and chitosan according to the multiple initial chitosan dissolution parameters to obtain multiple initial chitosan contact parameters, and performing a contact analysis between the enzyme and oxygen to obtain multiple initial oxygen contact parameters;

[0056] In the examples of the present application, the contact analysis between the enzyme, chitosan and oxygen was further performed using a plurality of initial chitosan dissolution parameters.

[0057] The multiple initial chitosan dissolution parameters reflect the viscosity of the chitosan solution under the multiple initial fermentation control parameters, which affect the contact between the enzyme and chitosan, as well as the oxygen transfer efficiency in the chitosan solution, and thus affect the fermentation reaction effect.

[0058] For example, the molecular diffusion theory and mass transfer coefficient (kL) model can be used to quantify the contact efficiency between enzyme and chitosan. Chitosan solutions with higher viscosity may hinder the diffusion of enzymes, thereby reducing mass transfer efficiency. Chitosan solutions with lower viscosity can enhance the contact between enzymes and substrates and promote reaction efficiency. By calculating the initial chitosan contact parameters, multiple indicators reflecting the actual contact between enzymes and chitosan, such as mass transfer coefficient and diffusion coefficient, are obtained to form multiple initial chitosan contact parameters.

[0059] Alternatively, the degradation rate of chitosan under different initial chitosan dissolution parameters while other variables are the same can also be analyzed to reflect the contact condition between the enzyme and chitosan.

[0060] Furthermore, the contact between enzyme and oxygen was analyzed to obtain multiple initial oxygen contact parameters. In the aerobic fermentation process, oxygen is a key factor in maintaining enzyme activity and microbial metabolism. Oxygen diffuses into the fermentation liquid through liquid mass transfer. Insufficient oxygen concentration will lead to decreased activity of microorganisms and enzymes, reducing the degradation efficiency of chitosan.

[0061] Alternatively, the contact between the enzyme and oxygen can be reflected by analyzing the dissolved oxygen concentration under different initial chitosan dissolution parameters.

[0062] By performing contact analysis between enzyme and chitosan, and contact analysis between enzyme and oxygen, the present invention can quantify and optimize the enzymatic degradation efficiency and oxygen mass transfer efficiency during the fermentation process. By obtaining and analyzing the initial chitosan contact parameters and oxygen contact parameters, not only the contact between enzyme and chitosan under different chitosan dissolution parameters but also the oxygen transfer effect under different chitosan dissolution parameters are obtained, and fermentation control optimization is performed based on this, thereby ultimately improving the yield and quality of chitosan oligosaccharides.

[0063] Step S20 in the method provided in the embodiment of the present application includes:

[0064] According to the historical chitosan oligosaccharide fermentation data, the sample chitosan dissolution parameter set is collected, and the sample chitosan contact parameter set is obtained by annotating the chitosan degradation rate of different sample chitosan dissolution parameters under the preset fermentation conditions;

[0065] Using the sample chitosan dissolution parameter set and the sample chitosan contact parameter set to train a chitosan contact analyzer;

[0066] The chitosan contact analyzer is used to perform enzyme and chitosan contact analysis on the multiple initial chitosan dissolution parameters respectively to obtain multiple initial chitosan contact parameters.

[0067] In the embodiment of the present application, based on the historical data of chitosan oligosaccharide fermentation, a sample chitosan dissolution parameter set is collected, and the sample chitosan dissolution parameter includes the viscosity of the chitosan solution, which reflects the physical state and dissolution effect of chitosan in the solution. The sample chitosan dissolution parameter set is data reflecting the dissolution of chitosan under different concentrations, pH and other conditions in the historical chitosan oligosaccharide fermentation data.

[0068] Furthermore, in order to quantify the degree of contact between enzyme and chitosan under different sample chitosan dissolution parameters, chitosan fermentation degradation test was carried out under preset fermentation conditions using different sample chitosan dissolution parameters to obtain the chitosan degradation rate under different sample chitosan dissolution parameters, which was marked as the sample chitosan contact parameter to obtain a set of sample chitosan contact parameters.

[0069] Exemplarily, the preset fermentation conditions may be the most commonly set fermentation condition parameters other than the sample chitosan dissolution parameters, such as the fermentation temperature that is set the most times, etc., as the preset fermentation conditions, to perform a quantitative analysis of the contact between the enzyme and chitosan under the controlled variables using the sample chitosan dissolution parameters.

[0070] Exemplarily, the sample chitosan dissolution parameters include viscosity 200 cP, viscosity 250 cP and viscosity 300 cP. Under the preset fermentation conditions, chitosan fermentation degradation test was carried out using different sample chitosan dissolution parameters, and the obtained chitosan degradation rates included 1.5 g / L·h, 1.2 g / L·h, and 1.0 g / L·h, which were marked as sample chitosan contact parameters. The larger the sample chitosan contact parameter, the more sufficient the contact between the enzyme and chitosan.

[0071] Furthermore, based on the sample chitosan dissolution parameter set and the sample chitosan contact parameter set, training is performed to construct a chitosan contact analyzer. The chitosan contact analyzer is a model used to analyze and predict the adequacy of the contact between enzymes and chitosan. It can predict the contact effect between enzymes and chitosan based on the input chitosan dissolution parameters, that is, the quantified chitosan contact parameters. By using these historical data, the chitosan contact analyzer can learn the dissolution and contact of chitosan under different conditions, and provide accurate predictions for the contact efficiency evaluation during the fermentation process.

[0072] Wherein, illustratively, based on the neural network in machine learning, a chitosan contact analyzer is constructed and trained, which includes an input layer, a hidden layer and an output layer. During the training process, the sample chitosan dissolution parameter is passed to the hidden layer through the input layer as input data, and is passed to the output layer after being processed by the activation function to generate the predicted chitosan contact parameter, and the forward propagation is used to calculate the output result of the model. The error between the chitosan contact parameter predicted by the model and the sample chitosan contact parameter in the real label is calculated by the loss function. Using the trained chitosan contact analyzer, the enzyme and chitosan contact analysis is performed on multiple initial chitosan dissolution parameters. Specifically, multiple initial chitosan dissolution parameters are input into the chitosan contact analyzer, and data processing and analysis are performed to obtain multiple initial chitosan contact parameters. According to the error calculated by the loss function, the weight of the hidden layer is updated using the back propagation algorithm, and the parameters of the chitosan contact analyzer are optimized by gradient descent. Each iteration adjusts the model parameters so that the model prediction error is gradually reduced. For example, until the error is less than 4%, the training is completed. The trained chitosan contact analyzer can output corresponding chitosan contact parameters according to the input chitosan dissolution parameters. For example, when the input chitosan dissolution parameter is a viscosity of 200 cP, the output chitosan contact parameter is 1.5 g / L·h. The trained chitosan contact analyzer is used to perform enzyme and chitosan contact analysis on multiple initial chitosan dissolution parameters. Specifically, multiple initial chitosan dissolution parameters are input into the chitosan contact analyzer, and data processing and analysis are performed to obtain multiple initial chitosan contact parameters.

[0073] By analyzing key parameters such as chitosan solubility and viscosity, the contact efficiency between enzyme and chitosan is evaluated, thereby obtaining multiple initial chitosan contact parameters. Multiple initial chitosan contact parameters can accurately reflect the contact between enzyme and chitosan under different initial fermentation control parameters, help optimize the mass transfer efficiency during the fermentation process, and increase the degradation rate of chitosan.

[0074] The present invention realizes accurate quantitative analysis and prediction of chitosan dissolution and enzymatic contact by training a chitosan contact analyzer based on historical data. The analyzer is used to analyze chitosan dissolution parameters under multiple initial fermentation conditions, and the initial chitosan contact parameters are successfully obtained, providing solid technical support for the optimization control analysis of the fermentation process.

[0075] Step S20 in the method provided in the embodiment of the present application further includes:

[0076] According to the historical chitosan oligosaccharide fermentation data, the sample chitosan dissolution parameter set was collected, and the dissolved oxygen concentration under different sample chitosan dissolution parameters was tested, which was marked as the sample oxygen contact parameter set;

[0077] Using the sample chitosan dissolution parameter set and the sample oxygen contact parameter set to train an oxygen contact analyzer;

[0078] The oxygen contact analyzer is used to perform enzyme and oxygen contact analysis on the multiple initial chitosan dissolution parameters to obtain multiple initial oxygen contact parameters.

[0079] In the present application, the chitosan dissolution parameters include the viscosity of the chitosan solution, which affects the contact between oxygen and enzyme, and further affects the activity of the enzyme and the fermentation effect. Therefore, the contact analysis between enzyme and oxygen is performed based on the chitosan dissolution parameters.

[0080] Among them, based on the historical chitosan oligosaccharide fermentation data, by collecting chitosan dissolution parameters and oxygen contact data, an oxygen mass transfer analysis tool in the fermentation process was constructed to optimize the oxygen supply in the fermentation process and ensure the efficiency and quality of chitosan oligosaccharide production. Specifically, first, based on the historical chitosan oligosaccharide fermentation data, the chitosan dissolution parameters in the previous chitosan oligosaccharide fermentation process, that is, the viscosity of the chitosan solution, were collected to obtain a sample chitosan dissolution parameter set. The sample chitosan dissolution parameter set is the same as the sample chitosan dissolution parameter set in the aforementioned content.

[0081] Furthermore, in order to further analyze the mass transfer efficiency of oxygen during the fermentation process, the dissolved oxygen concentration of the chitosan solution under different sample chitosan dissolution parameter conditions was tested and labeled as the sample oxygen contact parameter to obtain a set of sample oxygen contact parameters. By measuring the amount of oxygen that can be dissolved in the chitosan solution during the fermentation process, the mass transfer efficiency of oxygen in the fermentation broth is reflected. The dissolved oxygen concentration is a key indicator for evaluating the oxygen supply in the fermentation broth, especially for aerobic fermentation processes, where insufficient oxygen concentration will directly affect the metabolic activity of microorganisms and the activity of enzymatic reactions. Through testing, a set of sample oxygen contact parameters was labeled, which reflects the mass transfer efficiency of oxygen in the fermentation broth under different chitosan dissolution conditions.

[0082] Exemplarily, the sample chitosan dissolution parameters include viscosity 150 cP, viscosity 200 cP, and viscosity 250 cP, and the dissolved oxygen concentrations under different sample chitosan dissolution parameters are 7.5 mg / L, 6.0 mg / L, and 5.0 mg / L, which are marked as sample oxygen contact parameters.

[0083] Furthermore, the sample chitosan dissolution parameter set and the sample oxygen contact parameter set are used to train the oxygen contact analyzer for analyzing the oxygen contact parameters under different chitosan dissolution parameters, that is, the degree of contact between the enzyme and oxygen. Among them, the training process of the oxygen contact analyzer is the same as the training process of the chitosan contact analyzer, but the training data is different. The training process will not be repeated. Referring to the above content, in the training data of the oxygen contact analyzer, the sample chitosan dissolution parameter set is used as the input data, and the sample oxygen contact parameter set is used as the true label of the output data for training. The trained oxygen contact analyzer can output the oxygen contact parameter according to the input chitosan dissolution parameter. For example, if the input chitosan dissolution parameter is a viscosity of 150 cP, the output oxygen contact parameter is 7.5 mg / L.

[0084] Through the trained oxygen contact analyzer, multiple initial chitosan dissolution parameters are analyzed. By inputting multiple initial chitosan dissolution parameters into the oxygen contact analyzer, the oxygen contact analyzer can predict the contact efficiency between the enzyme and oxygen, thereby obtaining multiple initial oxygen contact parameters. The oxygen contact parameters help evaluate the effectiveness of oxygen transfer during the fermentation process, ensure that the optimal conditions for the enzymatic reaction are met, and improve the degradation rate of chitosan and the production efficiency of chitosan oligosaccharides.

[0085] The present invention collects chitosan dissolution parameters and oxygen contact parameters of samples and uses these data to train an oxygen contact analyzer, thereby achieving accurate prediction of oxygen mass transfer efficiency under different fermentation conditions.

[0086] S30: According to the multiple initial chitosan contact parameters and the multiple initial oxygen contact parameters, respectively combined with multiple initial fermentation times, chitosan oligosaccharide fermentation prediction is performed to obtain multiple fermentation yield parameters and multiple overdecomposition parameters, and multiple initial fermentation fitnesses are calculated;

[0087] In the examples of the present application, chitosan contact parameters and oxygen contact parameters are key factors affecting enzymatic degradation efficiency and microbial activity during fermentation, and they respectively describe the contact between enzyme and chitosan and oxygen and chitosan under fermentation conditions, which directly affects the efficiency of chitosan oligosaccharide production. Therefore, based on multiple initial chitosan contact parameters and multiple initial oxygen contact parameters, combined with multiple fermentation times, chitosan oligosaccharide fermentation is predicted, specifically predicting the yield of chitosan oligosaccharides after fermentation, and the proportion of chitosan oligosaccharide overdecomposition, and calculating the initial fermentation fitness of multiple initial fermentation control parameters to evaluate the advantages and disadvantages of multiple initial fermentation control parameters during fermentation control optimization.

[0088] Among them, if the fermentation time is too long, or the chitosan contact parameters and oxygen contact parameters are too large, the fermentation rate will be too high, causing excessive degradation of chitosan oligosaccharides during the fermentation process, affecting product quality. Therefore, the fermentation fitness is calculated by analyzing the overdecomposition parameters.

[0089] Step S30 in the method provided in the embodiment of the present application includes:

[0090] According to the historical chitosan oligosaccharide fermentation data, the sample chitosan contact parameter set, the sample oxygen contact parameter set and the sample fermentation time set were collected, and according to the chitosan oligosaccharide yield after fermentation and the content of over-degraded chitosan oligosaccharide, the sample fermentation yield parameter set and the sample over-decomposition parameter set were annotated;

[0091] The sample chitosan contact parameter set, the sample oxygen contact parameter set and the sample fermentation time set are used to train a fermentation predictor in combination with the sample fermentation yield parameter set and the sample overdecomposition parameter set;

[0092] The fermentation predictor is used to predict the fermentation of chitosan oligosaccharides based on the multiple initial chitosan contact parameters, the multiple initial oxygen contact parameters and the multiple initial fermentation times, so as to obtain multiple fermentation yield parameters and multiple overdecomposition parameters;

[0093] Calculate multiple initial fermentation fitness as follows:

[0094] ;

[0095] Among them, IFF is the fermentation fitness, w1 and w2 are weights, CTS r is the fermentation yield parameter, G r For over-decomposition parameters, CTS y is the preset fermentation yield parameter corresponding to the chitosan concentration.

[0096] In the embodiment of the present application, according to the historical chitosan oligosaccharide fermentation data, data collection is performed on chitosan oligosaccharide fermentation data with the same fermentation condition parameters except chitosan concentration, pH and fermentation time, for example, data collection is performed on chitosan oligosaccharide fermentation data with the same chitosan weight, fermentation temperature, etc. Specifically, chitosan contact parameters, oxygen contact parameters and fermentation time in the historical chitosan oligosaccharide fermentation data are collected to obtain a sample chitosan contact parameter set, a sample oxygen contact parameter set and a sample fermentation time set. Among them, the sample chitosan contact parameter and the sample oxygen contact parameter can be processed and obtained based on the method in the above content.

[0097] Furthermore, according to the chitosan oligosaccharide fermentation yield after fermentation in each historical chitosan oligosaccharide fermentation data, for example, the content of chitosan oligosaccharide in the solution after fermentation, it is marked as a sample fermentation yield parameter to obtain a sample fermentation yield parameter set. And the content of over-degraded chitosan oligosaccharides with a small molecular weight is tested and collected, marked as sample over-decomposition parameters, and a sample over-decomposition parameter set is obtained. The marking can be performed manually or by automatic standard. Among them, the over-degraded chitosan oligosaccharides can be detected by setting a molecular weight threshold, for example, a molecular weight less than 1,000 Da is regarded as an over-degraded chitosan oligosaccharide.

[0098] Exemplarily, the chitosan contact parameters of the samples include degradation rates of 1.5 g / L·h, 1.2 g / L·h, and 1.0 g / L·h, the oxygen contact parameters of the samples include dissolved oxygen concentrations of 7.5 mg / L, 6.0 mg / L, and 5.0 mg / L, the fermentation times of the samples include, for example, 36 h, 48 h, and 60 h, the fermentation yield parameters of the samples under the corresponding conditions, i.e., the chitosan oligosaccharide contents, are, for example, 9 g / L, 8 g / L, and 7 g / L, the overdecomposition parameters of the samples and the overdecomposed chitosan oligosaccharide contents are, for example, 0.5 g / L, 0.7 g / L, and 1.0 g / L.

[0099] Furthermore, a fermentation predictor is trained by using a set of sample chitosan contact parameters, a set of sample oxygen contact parameters and a set of sample fermentation time, in combination with the set of sample fermentation yield parameters and the set of sample over-decomposition parameters. The fermentation predictor can predict the amount of chitosan oligosaccharide generated and the over-decomposition situation, i.e., the sample fermentation yield parameters and the sample over-decomposition parameters, after inputting the chitosan contact parameters, oxygen contact parameters and fermentation time by learning the complex relationship between different sample chitosan contact parameters, sample oxygen contact parameters and sample fermentation time. Exemplarily, the fermentation predictor is trained by machine learning techniques, such as BP neural network or random forest algorithm, and the trained fermentation predictor can simulate the multivariate relationship in the fermentation process and quickly and accurately predict the fermentation yield and over-decomposition content of chitosan oligosaccharides. The trained fermentation predictor can predict the fermentation yield parameters and over-decomposition parameters after fermentation based on the input chitosan contact parameters, oxygen contact parameters and fermentation time. For example, when the input chitosan contact parameters, oxygen contact parameters and fermentation time are 1.5 g / L·h, 7.5 mg / L and 36h, the output fermentation yield parameters and over-decomposition parameters are 9 g / L and 0.5 g / L.

[0100] The trained fermentation predictor is used to predict the fermentation of chitosan oligosaccharides based on the current multiple initial chitosan contact parameters, multiple initial oxygen contact parameters and multiple initial fermentation times. Specifically, the multiple initial chitosan contact parameters, multiple initial oxygen contact parameters and multiple initial fermentation times are combined accordingly and input into the fermentation predictor. Multiple fermentation yield parameters and multiple overdecomposition parameters are obtained through data processing and prediction.

[0101] Furthermore, based on the multiple fermentation yield parameters and the multiple overdecomposition parameters, the advantages and disadvantages of the multiple initial fermentation control parameters are evaluated, and the multiple initial fermentation fitness of the multiple initial fermentation control parameters are specifically calculated as follows:

[0102] ;

[0103] Wherein, IFF is the fermentation fitness, w1 and w2 are weights, which respectively reflect the importance of chitosan oligosaccharide fermentation yield and overdecomposition parameters, and can be set based on those skilled in the art, for example, 0.6 and 0.4, CTS r is the fermentation yield parameter, G r For over-decomposition parameters, CTS y It is the preset fermentation yield parameter corresponding to the chitosan concentration. Exemplarily, a set of historical chitosan oligosaccharide fermentation yield parameters when the chitosan concentration is the aforementioned multiple initial chitosan concentrations can be obtained in the historical chitosan oligosaccharide data, and then the mean is calculated as the average fermentation yield parameter for chitosan oligosaccharide fermentation under different initial chitosan concentrations, as the preset fermentation yield parameter corresponding to different initial chitosan concentrations. In the formula, the first term represents the logarithmic ratio of the fermentation yield to the preset fermentation yield, which is used to measure the relative performance of the yield. The larger the term, the closer the fermentation yield is to or exceeds the expected value, and the greater the fermentation fitness. The second term is used to reflect the degree of over-decomposition. The smaller the value, the less over-decomposition phenomenon, and the greater the fermentation fitness. By using a logarithmic function, the negative impact of over-decomposition on fermentation fitness can be effectively amplified.

[0104] The larger the initial fermentation fitness among multiple initial fermentation fitnesses, the better the corresponding initial fermentation control parameters and the better the fermentation effect. It is based on the analysis of enzymes, chitosan and oxygen in the previous steps and is obtained by fermentation prediction calculation, which is relatively accurate and takes into account the influence of the solubility viscosity of the chitosan solution on the fermentation for prediction analysis and calculation.

[0105] The present invention combines the fermentation predictor trained by historical fermentation data. The model can effectively predict the final fermentation results under different fermentation conditions by learning the effects of chitosan contact, oxygen contact and fermentation time on yield and over-decomposition. In addition, by calculating the initial fermentation fitness, the advantages and disadvantages of different fermentation conditions can be evaluated, and the fermentation parameters can be dynamically adjusted, such as adjusting the chitosan concentration, pH and fermentation time within the fermentation control parameters, to optimize the production process of chitosan oligosaccharides. The logarithmic function and balanced weight design in the formula ensure a reasonable trade-off between yield and over-decomposition, so that the fermentation conditions can be optimized.

[0106] S40: Continue to iterate and optimize the fermentation control parameters. During the optimization process, the comprehensive contact parameters are calculated according to the chitosan contact parameters and the oxygen contact parameters. The fermentation control parameters are selected and exchanged according to the comprehensive contact parameters until the optimization converges and the optimal fermentation control parameters are obtained to perform chitosan oligosaccharide fermentation control.

[0107] In the embodiment of the present application, after processing and calculating to obtain multiple initial fermentation fitnesses of multiple initial fermentation control parameters, the advantages and disadvantages of the multiple initial fermentation control parameters can be reflected. The greater the initial fermentation fitness, the better the initial fermentation control parameter.

[0108] Continue to iteratively optimize the fermentation control parameters in the fermentation control parameter space, including continuing to randomly select the fermentation control parameters in the fermentation control parameter space, and obtain the fermentation fitness through the above steps for analysis and processing.

[0109] Among them, during the optimization process, the comprehensive contact parameters are calculated based on the chitosan contact parameters and oxygen contact parameters obtained from the analysis of each fermentation control parameter, and the fermentation control parameters are selected and exchanged based on the comprehensive contact parameters. For example, the chitosan concentration range within two fermentation control parameters is randomly selected for exchange to generate new fermentation control parameters. The random exchange is used to improve the randomness and accuracy of the optimization.

[0110] Until the optimization converges, for example, the number of optimization rounds reaches 100, the fermentation control parameters with the maximum fermentation fitness are output, and the optimal fermentation control parameters are obtained, which are used for chitosan oligosaccharide fermentation control. Through continuous parameter iteration and convergence judgment, the key variables in the fermentation process can be accurately controlled, the fermentation efficiency can be improved, the excessive degradation of the product can be reduced, and the stability and repeatability of the fermentation process can be ensured.

[0111] Step S40 in the method provided in the embodiment of the present application includes:

[0112] Select the initial fermentation control parameter with the largest initial fermentation fitness as the target fermentation control parameter;

[0113] Taking the target fermentation control parameter as the target, adjusting other multiple initial fermentation control parameters to obtain multiple updated fermentation control parameters;

[0114] According to the multiple initial chitosan contact parameters and the multiple initial oxygen contact parameters, a multiple initial comprehensive contact parameters are obtained by weighted calculation, and a multiple initial exchange probabilities are obtained by allocation;

[0115] Processing the multiple updated chitosan contact parameters and the multiple updated oxygen contact parameters obtained from the multiple updated fermentation control parameters, performing weighted calculation to obtain multiple updated fermentation contact parameters, and allocating to obtain multiple updated exchange probabilities;

[0116] According to the multiple initial exchange probabilities and the multiple updated exchange probabilities, randomly selecting a preset number of initial fermentation control parameters and updated fermentation control parameters from the multiple initial fermentation control parameters and the multiple updated fermentation control parameters to perform random parameter exchange to obtain multiple variant fermentation control parameters;

[0117] Continue to randomly generate, update and exchange the fermentation control parameters in the fermentation control parameter space until the iterative optimization converges, and output the fermentation control parameters with the maximum fermentation fitness as the optimal fermentation control parameters.

[0118] In the embodiment of the present application, based on the multiple initial fermentation fitnesses of the multiple initial fermentation control parameters obtained by the analysis and processing in the above content, the initial fermentation control parameter with the largest initial fermentation fitness is selected as the current optimal target fermentation control parameter.

[0119] Further, after the target fermentation control parameter is screened out, it is used as the target for adjusting and optimizing other relatively poor initial fermentation control parameters, and the remaining multiple initial fermentation control parameters are adjusted to be close to the target fermentation control parameter. The adjustment method can be achieved by setting the step size and other methods, so that multiple initial fermentation control parameters are adjusted to be close to the target fermentation control parameter, and multiple updated fermentation control parameters are obtained. Exemplarily, the adjustment step size of chitosan concentration, pH and fermentation time is set to 0.1%, 0.1 and 0.5h. With the chitosan concentration, pH and fermentation time within the target fermentation control parameter as the adjustment direction, the chitosan concentration, pH and fermentation time within the adjustment of the other multiple initial fermentation control parameters are adjusted according to the step size to obtain multiple updated fermentation control parameters.

[0120] Furthermore, the initial comprehensive contact parameter of each initial fermentation control parameter is obtained by weighted calculation according to the multiple initial chitosan contact parameters and the multiple initial oxygen contact parameters. For example, the weights of the initial chitosan contact parameter and the oxygen contact parameter are 0.55 and 0.45 respectively, and the weighted calculated initial comprehensive contact parameter can reflect the comprehensive contact between the enzyme, chitosan and oxygen during the fermentation process under each initial fermentation control parameter.

[0121] For example, the initial chitosan contact parameter is 1.5 g / L·h, the initial oxygen contact parameter is 7.5 mg / L, and the initial chitosan contact parameter and the initial oxygen contact parameter are weighted and calculated as (0.55×1.5)+(0.45×7.5)=4.2. The initial comprehensive contact parameter is 0.42, reflecting the comprehensive contact between the enzyme, chitosan and oxygen during the fermentation process under the initial fermentation control parameters.

[0122] Further, according to the multiple initial comprehensive contact parameters, multiple initial exchange probabilities are allocated, for example, the ratio of each initial comprehensive contact parameter to the sum of multiple initial comprehensive contact parameters is calculated as the initial exchange probability. The larger the initial comprehensive contact parameter, the more sufficient the contact between the enzyme, chitosan and oxygen under the corresponding initial fermentation control parameters, and exchanging these initial fermentation control parameters may produce better fermentation control parameters, so a larger initial exchange probability is set.

[0123] Through the steps in the aforementioned content, multiple updated chitosan contact parameters and multiple updated oxygen contact parameters of multiple updated fermentation control parameters are processed, and weighted calculation is performed on each updated chitosan contact parameter and multiple updated oxygen contact parameters according to the same weight and weighted calculation to obtain multiple updated fermentation contact parameters, and further calculate the ratio of each updated fermentation contact parameter to the sum of multiple updated fermentation contact parameters as the updated exchange probability. In this way, multiple updated exchange probabilities are obtained.

[0124] After processing to obtain multiple initial exchange probabilities and multiple updated exchange probabilities, a preset number of initial fermentation control parameters and updated fermentation control parameters are randomly selected from the multiple initial fermentation control parameters and the multiple updated fermentation control parameters for random parameter exchange. The preset number is, for example, 50% of the number of the multiple initial fermentation control parameters, or a fixed number such as 5. During the selection process, the multiple initial fermentation control parameters and the multiple updated fermentation control parameters are randomly selected according to the multiple initial exchange probabilities and the multiple updated exchange probabilities. The larger the initial exchange probability and the updated exchange probability, the greater the probability that the corresponding initial fermentation control parameters and the updated fermentation control parameters are selected. Among them, the selection can be based on a random algorithm in the prior art.

[0125] After selecting and obtaining a preset number of initial fermentation control parameters and updated fermentation control parameters, a mapping relationship between the preset number of initial fermentation control parameters and the updated fermentation control parameters is randomly constructed, for example, one initial fermentation control parameter corresponds to any updated fermentation control parameter, and the preset number of initial fermentation control parameters and the updated fermentation control parameters are paired to form a one-to-one mapping relationship.

[0126] Then, the corresponding initial fermentation control parameters and the parameters in the updated fermentation control parameters are randomly selected for exchange, for example, one or more of the chitosan concentration, pH or fermentation time in the corresponding initial fermentation control parameters and the updated fermentation control parameters are randomly selected for exchange, for example, the initial fermentation control parameters and the pH in the updated fermentation control parameters are exchanged to form new fermentation control parameters. That is, variant fermentation control parameters. In this way, after completing the random selection and exchange, multiple variant fermentation control parameters are obtained. Through the above-mentioned random selection and random exchange, the randomness and globality of the optimization can be fully improved, thereby improving the accuracy of the optimization.

[0127] Furthermore, based on the steps in the aforementioned content, the fermentation fitness of multiple variant fermentation control parameters can be calculated and obtained.

[0128] After a round of generating, updating and exchanging fermentation control parameters, the fermentation control parameters can continue to be randomly generated, updated and exchanged in the fermentation control parameter space, for example, a new plurality of initial fermentation control parameters can be randomly regenerated, and then the fermentation fitness is processed and calculated based on the steps in the aforementioned content, as well as updated and exchanged until the iterative optimization converges, for example, when a preset number of optimization rounds, such as 100 rounds, is reached, the optimization converges.

[0129] After the optimization converges, for example, after the total number of optimization rounds reaches 150, the fermentation control parameter with the maximum fermentation fitness is output as the optimal fermentation control parameter to complete the optimization. Exemplarily, the optimal fermentation control parameter includes a combination of optimal chitosan concentration, optimal pH and optimal fermentation time, and the optimal chitosan concentration, optimal pH and optimal fermentation time are 1%, 6.5 and 36 h, respectively. Under the optimal fermentation control parameter, the fermentation yield parameter is the highest, reaching 9 g / L. The overdecomposition parameter is the lowest, at 0.5 g / L.

[0130] The present invention optimizes fermentation control parameters through multiple steps of iteration such as screening, adjustment, weighted calculation and random exchange, and gradually improves fermentation conditions until the optimization converges. Finally, the fermentation control parameter with the maximum fermentation fitness is output as the optimal fermentation control parameter to achieve efficient control and quality improvement of chitosan oligosaccharide production.

[0131] The embodiments of the present application achieve the following technical effects through the above specific implementation methods:

[0132] The present invention, through one or more technical schemes mentioned above, randomly generates multiple initial fermentation control parameters in the fermentation control parameter space, and performs chitosan dissolution analysis according to each initial parameter to obtain multiple initial chitosan dissolution parameters. This process can effectively solve the problem of insufficient chitosan dissolution, thereby improving the contact efficiency between chitosan and enzyme. On this basis, by analyzing the contact between enzyme and chitosan, multiple chitosan contact parameters are obtained to ensure that the enzyme and chitosan are in full contact, significantly improve the degradation rate of chitosan, and thus improve the production efficiency of chitosan oligosaccharides. At the same time, oxygen contact analysis is also performed to obtain multiple initial oxygen contact parameters, optimize the transfer efficiency of oxygen and chitosan, ensure that the activity of microorganisms and enzymes is maintained during the fermentation process, and improve the fermentation effect. By combining multiple initial chitosan contact parameters and initial oxygen contact parameters, and further combining fermentation time to predict chitosan oligosaccharide fermentation, multiple fermentation yield parameters and over-decomposition parameters are obtained, and by calculating the initial fermentation fitness, the fermentation control parameters are iteratively optimized, and finally the optimal fermentation control parameters are obtained. The present invention improves the stability and efficiency of the fermentation process through dynamic adjustment and optimization, prevents excessive degradation of chitosan oligosaccharides, ensures the quality and yield of the product, and thus significantly improves the fermentation control production effect of chitosan oligosaccharides.

[0133] Example 2

[0134] like Figure 2 As shown, based on the same inventive concept as the chitosan oligosaccharide fermentation control method provided in Example 1, an embodiment of the present invention provides a chitosan oligosaccharide fermentation control system, the system comprising:

[0135] The initial dissolution analysis module 11 is used to obtain a fermentation control parameter space for producing chitosan oligosaccharides by fermentation based on chitosan, randomly generate multiple initial fermentation control parameters in the fermentation control parameter space, perform chitosan dissolution analysis according to the initial pH and initial chitosan concentration in each initial fermentation control parameter, and obtain multiple initial chitosan dissolution parameters, wherein the fermentation control parameters include chitosan concentration, pH and fermentation time;

[0136] A contact analysis module 12, for performing a contact analysis between the enzyme and chitosan according to the multiple initial chitosan dissolution parameters to obtain multiple initial chitosan contact parameters, and performing a contact analysis between the enzyme and oxygen to obtain multiple initial oxygen contact parameters;

[0137] The fitness acquisition module 13 is used to predict the fermentation of chitosan oligosaccharides according to the multiple initial chitosan contact parameters and the multiple initial oxygen contact parameters, respectively in combination with the multiple initial fermentation times, to obtain multiple fermentation yield parameters and multiple overdecomposition parameters, and to calculate multiple initial fermentation fitnesses;

[0138] The fermentation optimization module 14 is used to continue the iterative optimization of the fermentation control parameters. During the optimization process, the comprehensive contact parameters are calculated according to the chitosan contact parameters and the oxygen contact parameters. The fermentation control parameters are selected and exchanged according to the comprehensive contact parameters until the optimization converges and the optimal fermentation control parameters are obtained to perform chitosan oligosaccharide fermentation control.

[0139] Furthermore, the initial dissolution analysis module 11 is also used for:

[0140] Obtaining the chitosan concentration range, pH range and fermentation time range for producing chitooligosaccharides by fermentation based on chitosan;

[0141] Based on the chitosan concentration range, pH range and fermentation time range, a fermentation control parameter space is generated.

[0142] Furthermore, the initial dissolution analysis module 11 is also used for:

[0143] Randomly generate a plurality of initial fermentation control parameters in the fermentation control parameter space, each of which includes an initial chitosan concentration, an initial pH and an initial fermentation time;

[0144] According to the historical chitosan oligosaccharide fermentation data, the sample chitosan concentration set and sample pH set were collected, and the viscosity of the chitosan solution at different sample chitosan concentrations and sample pH was collected, and the sample chitosan dissolution parameter set was obtained by annotation;

[0145] Using the sample chitosan concentration set, the sample pH set and the sample chitosan dissolution parameter set, constructing a chitosan dissolution classifier;

[0146] The chitosan dissolution classifier is used to classify the chitosan dissolution of the initial pH and the initial chitosan concentration within each initial fermentation control parameter to obtain a plurality of initial chitosan dissolution parameters.

[0147] Furthermore, the contact analysis module 12 is also used for:

[0148] According to the historical chitosan oligosaccharide fermentation data, the sample chitosan dissolution parameter set is collected, and the sample chitosan contact parameter set is obtained by annotating the chitosan degradation rate of different sample chitosan dissolution parameters under the preset fermentation conditions;

[0149] Using the sample chitosan dissolution parameter set and the sample chitosan contact parameter set to train a chitosan contact analyzer;

[0150] The chitosan contact analyzer is used to perform enzyme and chitosan contact analysis on the multiple initial chitosan dissolution parameters respectively to obtain multiple initial chitosan contact parameters.

[0151] Furthermore, the contact analysis module 12 is also used for:

[0152] According to the historical chitosan oligosaccharide fermentation data, the sample chitosan dissolution parameter set was collected, and the dissolved oxygen concentration under different sample chitosan dissolution parameters was tested, which was marked as the sample oxygen contact parameter set;

[0153] Using the sample chitosan dissolution parameter set and the sample oxygen contact parameter set to train an oxygen contact analyzer;

[0154] The oxygen contact analyzer is used to perform enzyme and oxygen contact analysis on the multiple initial chitosan dissolution parameters to obtain multiple initial oxygen contact parameters.

[0155] Furthermore, the fitness acquisition module 13 is also used for:

[0156] According to the historical chitosan oligosaccharide fermentation data, the sample chitosan contact parameter set, the sample oxygen contact parameter set and the sample fermentation time set were collected, and according to the chitosan oligosaccharide yield after fermentation and the content of over-degraded chitosan oligosaccharide, the sample fermentation yield parameter set and the sample over-decomposition parameter set were annotated;

[0157] The sample chitosan contact parameter set, the sample oxygen contact parameter set and the sample fermentation time set are used to train a fermentation predictor in combination with the sample fermentation yield parameter set and the sample overdecomposition parameter set;

[0158] The fermentation predictor is used to predict the fermentation of chitosan oligosaccharides based on the multiple initial chitosan contact parameters, the multiple initial oxygen contact parameters and the multiple initial fermentation times, so as to obtain multiple fermentation yield parameters and multiple overdecomposition parameters;

[0159] Calculate multiple initial fermentation fitness as follows:

[0160] ;

[0161] Among them, IFF is the fermentation fitness, w1 and w2 are weights, CTS r is the fermentation yield parameter, G r For over-decomposition parameters, CTS y is the preset fermentation yield parameter corresponding to the chitosan concentration.

[0162] Furthermore, the fermentation optimization module 14 is also used for:

[0163] Select the initial fermentation control parameter with the largest initial fermentation fitness as the target fermentation control parameter;

[0164] Taking the target fermentation control parameter as the target, adjusting other multiple initial fermentation control parameters to obtain multiple updated fermentation control parameters;

[0165] According to the multiple initial chitosan contact parameters and the multiple initial oxygen contact parameters, a multiple initial comprehensive contact parameters are obtained by weighted calculation, and a multiple initial exchange probabilities are obtained by allocation;

[0166] Processing the multiple updated chitosan contact parameters and the multiple updated oxygen contact parameters obtained from the multiple updated fermentation control parameters, performing weighted calculation to obtain multiple updated fermentation contact parameters, and allocating to obtain multiple updated exchange probabilities;

[0167] According to the multiple initial exchange probabilities and the multiple updated exchange probabilities, randomly selecting a preset number of initial fermentation control parameters and updated fermentation control parameters from the multiple initial fermentation control parameters and the multiple updated fermentation control parameters to perform random parameter exchange to obtain multiple variant fermentation control parameters;

[0168] Continue to randomly generate, update and exchange the fermentation control parameters in the fermentation control parameter space until the iterative optimization converges, and output the fermentation control parameters with the maximum fermentation fitness as the optimal fermentation control parameters.

[0169] See also Figure 3 , Figure 3 Schematic diagram of an electronic device provided by an embodiment of the present invention. Figure 3 As shown, an embodiment of the present invention provides an electronic device 100, including a memory 110, a processor 120, and a computer program 111 stored in the memory 110 and executable on the processor 120. When the processor 120 executes the computer program 111, the steps of the method in Example 1 are implemented.

[0170] See also Figure 4 , Figure 4 A schematic diagram of an embodiment of a computer-readable storage medium provided in an embodiment of the present invention. Figure 4 As shown, this embodiment provides a computer-readable storage medium 200 on which a computer program 111 is stored. When the computer program 111 is executed by a processor, the steps of the method in Embodiment 1 are implemented.

[0171] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0172] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0173] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0174] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0175] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0176] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0177] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A chitosan oligosaccharide fermentation control method, characterized in that: The method comprises: Obtaining a fermentation control parameter space for producing chitosan oligosaccharides by fermentation based on chitosan, randomly generating a plurality of initial fermentation control parameters in the fermentation control parameter space, performing chitosan dissolution analysis according to the initial pH and initial chitosan concentration in each initial fermentation control parameter, and obtaining a plurality of initial chitosan dissolution parameters, wherein the fermentation control parameters include chitosan concentration, pH and fermentation time, the fermentation control parameter space includes a chitosan concentration range, a pH range and a fermentation time range, and the initial chitosan dissolution parameters include chitosan viscosity; According to the multiple initial chitosan dissolution parameters, performing a contact analysis between enzyme and chitosan to obtain multiple initial chitosan contact parameters, and performing a contact analysis between enzyme and oxygen to obtain multiple initial oxygen contact parameters, wherein the initial chitosan contact parameter includes a chitosan degradation rate, and the initial oxygen contact parameter includes a dissolved oxygen concentration; According to the multiple initial chitosan contact parameters and the multiple initial oxygen contact parameters, respectively combined with multiple initial fermentation times, chitosan oligosaccharide fermentation prediction is performed to obtain multiple fermentation yield parameters and multiple overdecomposition parameters, and multiple initial fermentation fitnesses are calculated; Continue to iterate and optimize the fermentation control parameters. During the optimization process, calculate the comprehensive contact parameters according to the chitosan contact parameters and the oxygen contact parameters. Select and exchange the fermentation control parameters according to the comprehensive contact parameters until the optimization converges and the optimal fermentation control parameters are obtained to control the chitosan oligosaccharide fermentation. The comprehensive contact parameters are obtained by weighted calculation of the chitosan contact parameters and the oxygen contact parameters. According to the multiple initial chitosan contact parameters and the multiple initial oxygen contact parameters, the chitosan oligosaccharide fermentation prediction is performed in combination with the multiple initial fermentation times to obtain multiple fermentation yield parameters and multiple over-decomposition parameters, including: According to the historical chitosan oligosaccharide fermentation data, the sample chitosan contact parameter set, the sample oxygen contact parameter set and the sample fermentation time set were collected, and according to the chitosan oligosaccharide yield after fermentation and the content of over-degraded chitosan oligosaccharide, the sample fermentation yield parameter set and the sample over-decomposition parameter set were annotated; The sample chitosan contact parameter set, the sample oxygen contact parameter set and the sample fermentation time set are used to train a fermentation predictor in combination with the sample fermentation yield parameter set and the sample overdecomposition parameter set; The fermentation predictor is used to predict the fermentation of chitosan oligosaccharides based on the multiple initial chitosan contact parameters, the multiple initial oxygen contact parameters and the multiple initial fermentation times, so as to obtain multiple fermentation yield parameters and multiple overdecomposition parameters; Calculate multiple initial fermentation fitness as follows: Among them, IFF is the fermentation fitness, w1 and w2 are weights, CTS r is the fermentation yield parameter, G r For over-decomposition parameters, CTS y is the preset fermentation yield parameter corresponding to the chitosan concentration; Wherein, a plurality of initial fermentation control parameters are randomly generated in the fermentation control parameter space, and chitosan dissolution analysis is performed according to the initial pH and initial chitosan concentration in each initial fermentation control parameter, including: Randomly generate a plurality of initial fermentation control parameters in the fermentation control parameter space, each of which includes an initial chitosan concentration, an initial pH and an initial fermentation time; According to the historical chitosan oligosaccharide fermentation data, the sample chitosan concentration set and sample pH set were collected, and the viscosity of the chitosan solution at different sample chitosan concentrations and sample pH was collected, and the sample chitosan dissolution parameter set was obtained by annotation; Using the sample chitosan concentration set, the sample pH set and the sample chitosan dissolution parameter set, constructing a chitosan dissolution classifier; Using the chitosan dissolution classifier, the initial pH and initial chitosan concentration in each initial fermentation control parameter are classified into chitosan dissolution classes to obtain a plurality of initial chitosan dissolution parameters; Wherein, according to the multiple initial chitosan dissolution parameters, performing contact analysis between enzyme and chitosan comprises: According to the historical chitosan oligosaccharide fermentation data, the sample chitosan dissolution parameter set is collected, and the sample chitosan contact parameter set is obtained by annotating the chitosan degradation rate of different sample chitosan dissolution parameters under the preset fermentation conditions; Using the sample chitosan dissolution parameter set and the sample chitosan contact parameter set to train a chitosan contact analyzer; Using the chitosan contact analyzer, respectively performing enzyme and chitosan contact analysis on the multiple initial chitosan dissolution parameters to obtain multiple initial chitosan contact parameters; Among them, the contact analysis of enzyme and oxygen is carried out to obtain multiple initial oxygen contact parameters, including: According to the historical chitosan oligosaccharide fermentation data, the sample chitosan dissolution parameter set was collected, and the dissolved oxygen concentration under different sample chitosan dissolution parameters was tested, which was marked as the sample oxygen contact parameter set; Using the sample chitosan dissolution parameter set and the sample oxygen contact parameter set to train an oxygen contact analyzer; Using the oxygen contact analyzer, respectively performing enzyme and oxygen contact analysis on the multiple initial chitosan dissolution parameters to obtain multiple initial oxygen contact parameters; Among them, the iterative optimization of the fermentation control parameters is continued. During the optimization process, the comprehensive contact parameters are calculated according to the chitosan contact parameters and the oxygen contact parameters. The fermentation control parameters are selected and exchanged according to the comprehensive contact parameters until the optimization converges to obtain the optimal fermentation control parameters, including: Select the initial fermentation control parameter with the largest initial fermentation fitness as the target fermentation control parameter; Taking the target fermentation control parameter as the target, adjusting other multiple initial fermentation control parameters to obtain multiple updated fermentation control parameters; According to the multiple initial chitosan contact parameters and the multiple initial oxygen contact parameters, a multiple initial comprehensive contact parameters are obtained by weighted calculation, and a multiple initial exchange probabilities are obtained by allocation; Processing the multiple updated chitosan contact parameters and the multiple updated oxygen contact parameters obtained from the multiple updated fermentation control parameters, performing weighted calculation to obtain multiple updated fermentation contact parameters, and allocating to obtain multiple updated exchange probabilities; According to the multiple initial exchange probabilities and the multiple updated exchange probabilities, randomly selecting a preset number of initial fermentation control parameters and updated fermentation control parameters from the multiple initial fermentation control parameters and the multiple updated fermentation control parameters to perform random parameter exchange to obtain multiple variant fermentation control parameters; Continue to randomly generate, update and exchange the fermentation control parameters in the fermentation control parameter space until the iterative optimization converges, and output the fermentation control parameters with the maximum fermentation fitness as the optimal fermentation control parameters.

2. The chitosan oligosaccharide fermentation control method according to claim 1, characterized in that: Obtain the fermentation control parameter space for producing chitooligosaccharides by fermentation based on chitosan, including: Obtaining the chitosan concentration range, pH range and fermentation time range for producing chitooligosaccharides by fermentation based on chitosan; Based on the chitosan concentration range, pH range and fermentation time range, a fermentation control parameter space is generated.

3. A chitosan oligosaccharide fermentation control system, characterized in that: The system comprises: An initial dissolution analysis module is used to obtain a fermentation control parameter space for producing chitosan oligosaccharides by fermentation based on chitosan, randomly generate multiple initial fermentation control parameters in the fermentation control parameter space, perform chitosan dissolution analysis according to the initial pH and initial chitosan concentration in each initial fermentation control parameter, and obtain multiple initial chitosan dissolution parameters, wherein the fermentation control parameters include chitosan concentration, pH and fermentation time, the fermentation control parameter space includes a chitosan concentration range, a pH range and a fermentation time range, and the initial chitosan dissolution parameters include chitosan viscosity; A contact analysis module, for performing a contact analysis between the enzyme and chitosan according to the multiple initial chitosan dissolution parameters to obtain multiple initial chitosan contact parameters, and performing a contact analysis between the enzyme and oxygen to obtain multiple initial oxygen contact parameters, wherein the initial chitosan contact parameters include chitosan degradation rate, and the initial oxygen contact parameters include dissolved oxygen concentration; A fitness acquisition module, for predicting chitosan oligosaccharide fermentation according to the multiple initial chitosan contact parameters and the multiple initial oxygen contact parameters, respectively in combination with multiple initial fermentation times, obtaining multiple fermentation yield parameters and multiple overdecomposition parameters, and calculating multiple initial fermentation fitnesses; A fermentation optimization module is used to continue iterative optimization of fermentation control parameters. During the optimization process, comprehensive contact parameters are calculated according to chitosan contact parameters and oxygen contact parameters. Fermentation control parameters are selected and exchanged according to the comprehensive contact parameters until the optimization converges to obtain optimal fermentation control parameters and perform chitosan oligosaccharide fermentation control. The comprehensive contact parameters are obtained by weighted calculation of chitosan contact parameters and oxygen contact parameters. According to the multiple initial chitosan contact parameters and the multiple initial oxygen contact parameters, the chitosan oligosaccharide fermentation prediction is performed in combination with the multiple initial fermentation times to obtain multiple fermentation yield parameters and multiple over-decomposition parameters, including: According to the historical chitosan oligosaccharide fermentation data, the sample chitosan contact parameter set, the sample oxygen contact parameter set and the sample fermentation time set were collected, and according to the chitosan oligosaccharide yield after fermentation and the content of over-degraded chitosan oligosaccharide, the sample fermentation yield parameter set and the sample over-decomposition parameter set were annotated; The sample chitosan contact parameter set, the sample oxygen contact parameter set and the sample fermentation time set are used to train a fermentation predictor in combination with the sample fermentation yield parameter set and the sample overdecomposition parameter set; The fermentation predictor is used to predict the fermentation of chitosan oligosaccharides based on the multiple initial chitosan contact parameters, the multiple initial oxygen contact parameters and the multiple initial fermentation times, so as to obtain multiple fermentation yield parameters and multiple overdecomposition parameters; Calculate multiple initial fermentation fitness as follows: Among them, IFF is the fermentation fitness, w1 and w2 are weights, CTS r is the fermentation yield parameter, G r For over-decomposition parameters, CTS y is the preset fermentation yield parameter corresponding to the chitosan concentration; Wherein, a plurality of initial fermentation control parameters are randomly generated in the fermentation control parameter space, and chitosan dissolution analysis is performed according to the initial pH and initial chitosan concentration in each initial fermentation control parameter, including: Randomly generate a plurality of initial fermentation control parameters in the fermentation control parameter space, each of which includes an initial chitosan concentration, an initial pH and an initial fermentation time; According to the historical chitosan oligosaccharide fermentation data, the sample chitosan concentration set and sample pH set were collected, and the viscosity of the chitosan solution at different sample chitosan concentrations and sample pH was collected, and the sample chitosan dissolution parameter set was obtained by annotation; Using the sample chitosan concentration set, the sample pH set and the sample chitosan dissolution parameter set, constructing a chitosan dissolution classifier; Using the chitosan dissolution classifier, the initial pH and initial chitosan concentration in each initial fermentation control parameter are classified into chitosan dissolution classes to obtain a plurality of initial chitosan dissolution parameters; Wherein, according to the multiple initial chitosan dissolution parameters, performing contact analysis between enzyme and chitosan comprises: According to the historical chitosan oligosaccharide fermentation data, the sample chitosan dissolution parameter set is collected, and the sample chitosan contact parameter set is obtained by annotating the chitosan degradation rate of different sample chitosan dissolution parameters under the preset fermentation conditions; Using the sample chitosan dissolution parameter set and the sample chitosan contact parameter set to train a chitosan contact analyzer; Using the chitosan contact analyzer, respectively performing enzyme and chitosan contact analysis on the multiple initial chitosan dissolution parameters to obtain multiple initial chitosan contact parameters; Among them, the contact analysis of enzyme and oxygen is carried out to obtain multiple initial oxygen contact parameters, including: According to the historical chitosan oligosaccharide fermentation data, the sample chitosan dissolution parameter set was collected, and the dissolved oxygen concentration under different sample chitosan dissolution parameters was tested, which was marked as the sample oxygen contact parameter set; Using the sample chitosan dissolution parameter set and the sample oxygen contact parameter set to train an oxygen contact analyzer; Using the oxygen contact analyzer, respectively performing enzyme and oxygen contact analysis on the multiple initial chitosan dissolution parameters to obtain multiple initial oxygen contact parameters; Among them, the iterative optimization of the fermentation control parameters is continued. During the optimization process, the comprehensive contact parameters are calculated according to the chitosan contact parameters and the oxygen contact parameters. The fermentation control parameters are selected and exchanged according to the comprehensive contact parameters until the optimization converges to obtain the optimal fermentation control parameters, including: Select the initial fermentation control parameter with the largest initial fermentation fitness as the target fermentation control parameter; Taking the target fermentation control parameter as the target, adjusting other multiple initial fermentation control parameters to obtain multiple updated fermentation control parameters; According to the multiple initial chitosan contact parameters and the multiple initial oxygen contact parameters, a multiple initial comprehensive contact parameters are obtained by weighted calculation, and a multiple initial exchange probabilities are obtained by allocation; Processing the multiple updated chitosan contact parameters and the multiple updated oxygen contact parameters obtained from the multiple updated fermentation control parameters, performing weighted calculation to obtain multiple updated fermentation contact parameters, and allocating to obtain multiple updated exchange probabilities; According to the multiple initial exchange probabilities and the multiple updated exchange probabilities, randomly selecting a preset number of initial fermentation control parameters and updated fermentation control parameters from the multiple initial fermentation control parameters and the multiple updated fermentation control parameters to perform random parameter exchange to obtain multiple variant fermentation control parameters; Continue to randomly generate, update and exchange the fermentation control parameters in the fermentation control parameter space until the iterative optimization converges, and output the fermentation control parameters with the maximum fermentation fitness as the optimal fermentation control parameters.

4. An electronic device, characterized in that: include: Memory for storing computer software programs; A processor is used to read and execute the computer software program, thereby implementing the chitosan oligosaccharide fermentation control method according to any one of claims 1 to 2.

5. A computer-readable storage medium, characterized in that: The storage medium stores a computer software program, and when the computer software program is executed by the processor, the chitosan oligosaccharide fermentation control method according to any one of claims 1 to 2 is implemented.

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