A preparation method of corn superoxide dismutase

Abstract

The present application discloses a method for preparing corn superoxide dismutase, which relates to the technical field of organic matter separation and extraction, including: S1. corn pretreatment; S2. enzymolysis: S21. adding corn slurry to a drum screen, and immersing the lower half of the drum in an enzymolysis mixture; starting the drum screen to make the corn material roll in the drum while keeping it immersed in the enzymolysis mixture; S22. regularly extracting the enzymolysis mixture for centrifugal separation to remove starch particles and other impurities; S23. pouring the clarified liquid after centrifugation back into the drum screen and cyclically performing enzymolysis; S24. stirring the enzymolyzed corn slurry evenly and then filtering to collect the filtrate; S3. extraction and post-processing; the viscosity problem caused by the high starch content of corn as a raw material is solved, the enzymolysis efficiency is significantly improved, the activity of SOD is effectively protected, and the product quality is stable and reliable. At the same time, the technical solution is easy to achieve large-scale production and reduce production costs.

Description

Technical Field

[0001] The invention relates to the technical field of organic matter separation and extraction, and in particular to a method for preparing corn superoxide dismutase. Background Art

[0002] Superoxide dismutase (SOD) is an antioxidant metalloenzyme present in organisms. It can catalyze the dismutation of superoxide anion radicals to produce oxygen and hydrogen peroxide. It plays a vital role in the body's oxidation and antioxidant balance and is closely related to the occurrence and development of many diseases.

[0003] SOD can be extracted from microorganisms such as yeast, bacteria, fungi, and bioengineered bacteria, as well as plant roots, leaves, seeds, or other fruits. Currently, extracting SOD from plants is a common method, mostly from garlic, corn, tomato, mulberry leaves, sea buckthorn, cactus, and other plants.

[0004] For example, the Chinese patent application number CN202011634220.1 provides an industrial production method for extracting superoxide dismutase from Shenzhou grass. This invention provides an industrial production method for extracting superoxide dismutase from Shenzhou grass, which belongs to the technical field of separation and extraction of organic matter. The method comprises: S1. After evenly mixing the Shenzhou grass raw material with phosphate buffer, adding porridge enzyme and surfactant for enzymatic hydrolysis; S2. After enzymatic hydrolysis, ultrasonic extraction and solid-liquid separation are performed to obtain a liquid; S3. After adding any one or more of an activator, a protective agent and a stabilizer to the liquid, the Shenzhou grass superoxide dismutase is collected by filtration. This invention aims to be suitable for industrial production. By optimizing the various process steps of extracting superoxide dismutase from Shenzhou grass, an industrial production method for extracting superoxide dismutase from Shenzhou grass is finally obtained, which has good practical application value.

[0005] Compared to Chinese grass, corn raw materials are easier to obtain. There are many existing methods for preparing superoxide dismutase complex enzymes from corn, but there is a problem of using chemical disinfectants such as bleaching powder and sodium hypochlorite in the preparation process. Since chemical disinfectants are easily residual and pollute the environment during production, the quality of the superoxide dismutase complex enzyme prepared is also affected to a certain extent. At the same time, in the process of drying the product, the existing methods use freeze drying or spraying. The former is more expensive, and the latter has a large loss of enzyme activity, both of which are not suitable for the needs of large-scale production. The existing methods also have technical problems such as low germination rate, low enzyme yield, and small production scale. Since corn is germinated in the box of a germination device, there is a problem of low ventilation. The corn growth environment is narrow, which easily causes a biofilm to form on the corn surface, causing corruption, resulting in a reduction in germination rate, affecting the quality of the superoxide dismutase obtained, and easily causing residues, which is not easy to clean, increasing the labor intensity of workers.

[0006] In addition, the high starch content in corn causes the liquid to become viscous during the enzymatic hydrolysis process, hindering the contact between the enzyme and the cell wall, reducing the enzymatic hydrolysis efficiency, and affecting the activity and extraction amount of SOD. Summary of the Invention

[0007] The embodiments of the present application provide a method for preparing corn superoxide dismutase, which solves the viscosity problem caused by the high starch content when corn is used as a raw material to produce SOD. The enzymatic hydrolysis efficiency is significantly improved, the activity of SOD is effectively protected, and the product quality is stable and reliable. At the same time, this technical solution is easy to achieve large-scale production, reducing production costs.

[0008] The present invention provides a method for preparing corn superoxide dismutase, which specifically comprises the following steps:

[0009] S1 pretreatment: The germinated corn was crushed to 80-120 mesh, the crushed germinated corn was added in a ratio of 1:2-4 pH = 7.8, 0.05mol / L phosphate buffer, mixed and ground into corn pulp, ultrasonic cell disruption;

[0010] S2. Enzymatic hydrolysis:

[0011] S21. The corn slurry after ultrasonic crushing is added to the drum screen, and the lower half of the drum is immersed in the enzymatic mixture; start the drum screen, so that the corn material tumbles in the drum while remaining immersed in the enzymatic mixture;

[0012] S22. Every 10-15 minutes, the enzymatic mixture was extracted and centrifuged to remove suspended starch granules and other impurities;

[0013] S23. The clarified liquid after centrifugation is poured back into the drum screen and the enzymatic hydrolysis cycle is repeated 2-3 times;

[0014] S24. The enzymatic corn syrup was stirred and filtered, the filtrate was collected, and 0.5%-1.5% of the weight of the filtrate was added to the filtrate;

[0015] S3. Extraction and post-processing:

[0016] S31. The filtrate is ultrasonically obtained to obtain a liquid, and any one or more activators, protective agents and stabilizers are added to the liquid;

[0017] S32. Concentration and drying: placing the filtrate into a low-temperature vacuum concentrator and evaporating it at 22-25°C for 8-15 hours to obtain a corn superoxide dismutase multi-enzyme liquid; mixing the corn superoxide dismutase multi-enzyme liquid with 1% by weight of silicon dioxide and placing it into a low-temperature vacuum drying device, freeze-drying it, and obtaining a corn superoxide dismutase multi-enzyme powder.

[0018] Furthermore, the axis of the drum screen is arranged horizontally, the diameter of the drum screen hole is smaller than the diameter of the crushed corn particles, one end is open for feeding, and the other end is provided with a discharge port.

[0019] Furthermore, the amount of corn slurry added in S21 is 40%-60% of the volume of the drum screen; the enzymatic hydrolysis mixture includes a complex enzyme and a surfactant, the complex enzyme is a mixture of pectinase, cellulase, hemicellulase and protease, the addition amount of the complex enzyme is 0.5-2% of the mass of the corn slurry, and the surfactant is sodium dodecyl sulfate, the addition amount is 0.5-0.8% of the mass of the rice slurry; the enzymatic hydrolysis temperature is 45-55°C, the pH value is 7.0-8.0, and the enzymatic hydrolysis time is 40-80 minutes.

[0020] Furthermore, multiple sets of rotating blades are installed in the drum screen; the object dynamic model is used to simulate the flow of objects during the stirring process to ensure comprehensive and uniform stirring; specifically, multiple blades are installed in the drum screen, and the spiral leaf shape is initially selected. The blade width accounts for 10%-20% of the drum screen diameter, the blade length is slightly less than half the length of the drum screen, and the blades are arranged in a staggered manner with a blade angle of 30-60°.

[0021] Furthermore, a transmittance sensor is installed on the storage tank of the enzymatic hydrolysis mixture to establish a mapping relationship model between transmittance and starch concentration; specifically:

[0022] The mapping relationship model between transmittance and starch concentration is quantified by historical data and experimental calibration, and the analysis and fitting of the relevant quantitative data are determined by the actual situation;

[0023] The camera below the drum screen captures the state of the material in the drum screen and performs feature extraction and recognition, and calculates the immersion ratio of starch particles in the mixed liquid to infer the enzymatic hydrolysis process;

[0024] Perform grayscale histogram analysis on the collected original image;

[0025] Then, filtering and denoising preprocessing operations are performed to extract starch granule features;

[0026] Morphological operations were applied to further clean the image, remove noise, connect adjacent starch granule regions, and extract the contour edges of starch granules;

[0027] Through the connected region labeling algorithm, all starch granule regions in the image are identified, and the area and shape characteristics of each region are calculated;

[0028] Classify the extracted features to distinguish starch granules from other impurities;

[0029] The number of contact pixels between the starch granule area and the mixed solution background area was calculated to approximate the immersion ratio;

[0030] A threshold is set according to the acquired total starch amount data, and step S221 is performed to start the centrifugal separation device when the starch concentration exceeds the set threshold;

[0031] After step S221 is completed, step S231 is further performed: the above operations are repeatedly performed until the extraction and separation of superoxide dismutase is completed.

[0032] Furthermore, after starting the centrifugal separation equipment in step S221, solid precipitate and supernatant are separated; the solid precipitate is mainly undissolved starch granules.

[0033] Furthermore, the solid precipitate obtained after centrifugation was collected, dried, and weighed using a precision balance to record the mass of the precipitate, specifically:

[0034] S2211. Calculate the initial amount of corn flour and starch content, and calculate the theoretical amount of starch that should be obtained;

[0035] S2212. By comparing the actual amount of starch in the precipitate with the theoretical amount of starch, the completion of the enzymatic hydrolysis process is calculated to obtain the percentage completion of the enzymatic hydrolysis process;

[0036] Among them, the degree of completion of the enzymatic hydrolysis process Ma is the actual amount of starch measured by weighing after drying;

[0037] S2213. Analyze the above steps and evaluate the impact of enzymatic hydrolysis conditions such as temperature, pH value, and enzyme dosage on the process completion.

[0038] Furthermore, after recording and analyzing the quality of the precipitate, sensors and data recording systems are set up to obtain a continuous and dynamic data set, including the changes in various parameters during the enzymatic hydrolysis process, and to monitor and record the enzymatic hydrolysis progress and overall time data of the same batch of materials in real time.

[0039] Furthermore, before enzymatic hydrolysis of each batch of material, data from the first three batches were collected, the average value was calculated, and a baseline standard for the enzymatic hydrolysis operation was established; wherein, the baseline value formula for the enzymatic hydrolysis operation is:

[0040]

[0041] n represents the number of data points to be averaged. In this implementation scenario, it refers to the number of data points in the first three batches. batch_i Represents the data value of the i-th batch, Represents the sum of all data values ​​from the first batch to the nth batch; the formula means that the average value of these data is calculated by adding the data values ​​of the first three batches and dividing it by the number of batches, and the average value is used as the baseline value.

[0042] Furthermore, according to the real-time progress of starch filtration through the drum screen, the drum screen speed and the mixing time interval of the mixed liquid are dynamically adjusted to achieve the best enzymatic hydrolysis effect;

[0043] Combined with the single filtration amount and the overall cumulative amount of starch, the distribution and concentration of starch in the mixed liquid are analyzed, and the drainage and flushing frequency of the centrifuge are automatically adjusted;

[0044] When stirring stops, the camera captures the image of the upper part of the mixed liquid in the drum screen and converts it into a grayscale image for analyzing the distribution and concentration of starch granules;

[0045] By using image processing algorithms, the grayscale value changes in different areas of the grayscale image are analyzed to determine the progress and quality of starch filtration and obtain the real-time progress and estimated amount of starch filtration;

[0046] Comprehensively analyze data such as drum screen speed, stirring time interval, centrifugation frequency, and image recognition results to evaluate the effectiveness of current enzymatic hydrolysis parameters;

[0047] Adjust the enzymatic hydrolysis control parameters based on the evaluation results.

[0048] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0049] First, the enzymatic hydrolysis process is arranged on a drum screen, and the lower half of the drum is immersed in the enzymatic hydrolysis mixture, so that the material is always immersed in the enzymatic hydrolysis mixture. At the same time, the diameter of the drum screen hole is smaller than the corn crushing particle size, and the starch particles can pass through the screen hole, which is convenient for starch filtration. The setting of the drum screen can achieve effective filtration of starch particles, and at the same time ensure that the enzymatic hydrolysis mixture can fully contact and enzymatically hydrolyze the corn cell wall. Through the dynamic rolling of the drum screen and the circulation and renewal of the enzymatic hydrolysis mixture, the enzymatic hydrolysis efficiency is improved, and the interference of starch on the enzymatic hydrolysis process is reduced. This effectively solves the viscosity problem caused by the high starch content when corn is used as a raw material to produce SOD, the enzymatic hydrolysis efficiency is significantly improved, the activity of SOD is effectively protected, and the product quality is stable and reliable. At the same time, this technical solution is easy to achieve large-scale production, reduce production costs, and improve economic benefits.

[0050] Secondly, a stirring system is set up to ensure that starch granules are evenly dispersed in the enzymatic hydrolysis mixture, avoiding viscosity problems caused by local excessive concentration and improving the contact efficiency between the enzyme and corn cells. The transmittance data of the real-time transmittance monitoring system promptly reflects the release and dispersion of starch in the mixture, providing a basis for adjusting the stirring parameters. Through image analysis and starch immersion calculation, non-invasive, real-time monitoring of the enzymatic hydrolysis process is achieved, providing accurate data support for process adjustment. Through the total amount of starch in the mixture and the centrifugal separation process, excess starch in the mixture is effectively removed, the viscosity is reduced, and starch resources are recovered, improving the economic efficiency of the overall process.

[0051] Third, by further optimizing the starch amount analysis step after centrifugal separation, a quantitative assessment of the completion of the enzymatic hydrolysis process was achieved. By comparing the difference between the actual starch amount and the theoretical starch amount, the efficiency of the enzymatic hydrolysis reaction can be intuitively reflected, and key data support can be provided for process optimization, thereby improving the controllability and predictability of the production process, thereby improving product quality and production efficiency. Through the optimization of the stirring system, real-time transmittance monitoring, image analysis and starch immersion amount calculation, total starch amount control of the mixed liquid and centrifugal separation measures, the enzymatic hydrolysis efficiency in the SOD extraction process of corn raw materials was significantly improved; ensuring sufficient contact between the enzyme and corn cells, shortening the enzymatic hydrolysis time, and increasing the SOD yield; through real-time monitoring and data analysis, precise control of the enzymatic hydrolysis process was achieved, reducing human intervention errors; effectively recycling starch resources, reducing waste generation, and improving the economy and environmental protection of the process;

[0052] Fourthly, by introducing advanced technical means such as continuous data monitoring, baseline establishment, active control, and image recognition, intelligent management and optimization of the enzymatic hydrolysis process are achieved; through real-time data collection and analysis, combined with image recognition technology, the starch filtration progress can be accurately judged, and the enzymatic hydrolysis control parameters can be dynamically adjusted accordingly; this closed-loop feedback mechanism not only improves the enzymatic hydrolysis efficiency, but also ensures the stability and controllability of the production process; it can significantly shorten the enzymatic hydrolysis time, improve product activity, and at the same time reduce production costs and energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 Schematic diagram of a drum screen according to an embodiment of the present invention;

[0054] Figure 2 The material state in the drum screen is photographed and features are extracted and identified. The immersion ratio of starch granules in the mixed liquid is calculated to deduce the enzymatic hydrolysis process flow chart. DETAILED DESCRIPTION

[0055] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this invention pertains; the terms used herein in the specification of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention; the term "and / or" used herein includes any and all combinations of one or more of the associated listed items.

[0056] Example 1: A method for preparing corn superoxide dismutase, comprising the following steps:

[0057] S1. Preprocessing

[0058] S11 cracked yeast fermentation broth: Inoculate yeast into culture medium and ferment at 28-32°C and pH 4.5-5.5 for 48-72 hours. Then add snail enzyme and react for 1-2 hours to obtain cracked yeast fermentation broth.

[0059] The yeast inoculation amount is 5%-10% of the culture medium volume, and the snail enzyme addition ratio is 50-100 mg per liter of fermentation liquid;

[0060] S12 Preparation: Prepare an appropriate amount of raw corn, remove impurities from the corn, and set aside;

[0061] S13 Germination: Place the corn in a fully automatic seed cleaning, soaking, and germination device, clean and soak for 8-12 hours, and germinate at 25-30°C for 48-60 hours until the sprouts are 3-5 mm long;

[0062] The soaking liquid contains fermentation liquid of cracked yeast, the addition amount of which is 1%-5% of the weight of the corn, and also contains 5-10 mg / L of iron, 0.1-0.5 mg / L of selenium, 1-2 mg / L of copper, 5-10 mg / L of manganese, and 5-10 mg / L of zinc;

[0063] S14: Grinding the germinated corn into 80-120 mesh, adding 0.05 mol / L phosphate buffer (PBS) with a pH of 7.8 to the ground germinated corn in a ratio of 1:2-4, mixing and grinding to form corn pulp, and ultrasonically disrupting the cells;

[0064] S2. Enzymatic Hydrolysis

[0065] like Figure 1 As shown, a drum screen is set and installed, with the drum axis arranged horizontally, one end open for feeding, and the other end with a discharge port;

[0066] Among them, the diameter of the drum screen hole is smaller than the corn crushing particle size;

[0067] S21. The corn slurry after ultrasonic crushing S14 was added to the drum screen, and the lower half of the drum was immersed in the enzymatic mixture; the drum screen was started, and the corn material was tumbled in the drum while remaining immersed in the enzymatic mixture;

[0068] The amount of corn steep liquor added is 40%-60% of the volume of the drum screen; the enzymatic hydrolysis mixture comprises a complex enzyme and a surfactant, wherein the complex enzyme is a mixture of pectinase, cellulase, hemicellulase and protease, the added amount of the complex enzyme is 0.5-2% of the mass of the corn steep liquor, and the surfactant is sodium lauryl sulfate, the added amount of which is 0.5-0.8% of the mass of the rice slurry; the enzymatic hydrolysis temperature is 45-55° C., the pH value is 7.0-8.0, and the enzymatic hydrolysis time is 40-80 minutes;

[0069] S22. Every 10-15 minutes, the enzymatic mixture was extracted and centrifuged to remove suspended starch granules and other impurities;

[0070] S23. The clarified liquid after centrifugation is poured back into the drum screen and the enzymatic hydrolysis cycle is repeated 2-3 times;

[0071] S24. The enzymatic corn syrup was stirred and filtered, the filtrate was collected, and 0.5%-1.5% of the weight of the filtrate was added to the filtrate;

[0072] S3. Extraction and post-processing

[0073] S31. The filtrate is ultrasonically obtained to obtain a liquid, and any one or more activators, protective agents and stabilizers are added to the liquid;

[0074] The ultrasonic frequency is 20-30kHz, the power is 10-20W, the ultrasonic working time is 15-20s with an interval of 5-10s, the total ultrasonic time is 10-20min, and the extraction process temperature is 30-60°C; the activators are manganese chloride and ferrous chloride; the protective agent is a protein disulfide bond protective agent; and the stabilizer is trehalose or burdock oligosaccharide.

[0075] S32 concentration and drying: the filtrate was placed in a low-temperature vacuum concentrator and evaporated at 22-25 ℃ for 8-15 hours to obtain a corn superoxide dismutase multi-enzyme liquid;

[0076] The corn superoxide dismutase multi-enzyme liquid and 1% of silicon dioxide by weight are evenly mixed and then placed in a low-temperature vacuum drying device for freeze drying to obtain the corn superoxide dismutase multi-enzyme powder.

[0077] The technical solutions in the above embodiments of the present application have at least the following technical effects or advantages:

[0078] The starch content in corn is approximately 48-73%. When corn is used as a raw material to produce SOD, especially in industrial production, the starch granules are released during the enzymatic hydrolysis process, causing the liquid to become viscous, hindering the contact between the enzyme and the cell wall, resulting in uneven enzyme distribution, reduced enzymatic efficiency, increased impurity release, and affected SOD activity and extraction yield.

[0079] The enzymatic hydrolysis process is arranged on a drum screen, and the lower half of the drum is immersed in the enzymatic hydrolysis mixture, so that the material is always immersed in the enzymatic hydrolysis mixture. At the same time, the diameter of the drum screen holes is smaller than the crushed corn particle size, and the starch particles can pass through the screen holes, which is convenient for starch filtration. The setting of the drum screen can effectively filter out the starch particles, and at the same time ensure that the enzymatic hydrolysis mixture can fully contact and enzymatically hydrolyze the corn cell walls. The dynamic rolling of the drum screen and the circulation and renewal of the enzymatic hydrolysis mixture improve the enzymatic hydrolysis efficiency, reduce the interference of starch on the enzymatic hydrolysis process, effectively solve the viscosity problem caused by the high starch content when corn is used as a raw material to produce SOD, significantly improve the enzymatic hydrolysis efficiency, effectively protect the activity of SOD, and ensure stable and reliable product quality. At the same time, the technical solution is easy to achieve large-scale production, reduce production costs, and improve economic benefits.

[0080] The preparation of superoxide dismutase according to the scheme of this embodiment can effectively extract SOD from corn and improve the extraction efficiency. The adjustment of the process parameters in this embodiment can protect the activity of SOD, reduce losses during the extraction process, and improve the purity and activity of the product. By optimizing the pretreatment, enzymatic hydrolysis, extraction and post-treatment steps, the material consumption and energy consumption in the production process are reduced, thereby reducing production costs. By optimizing the extraction and purification process, the high purity and high activity of the SOD product are ensured, meeting the demand for SOD products in the fields of food, cosmetics, health products and agriculture.

[0081] Example 2: The above-mentioned Example 1 improves the enzymatic hydrolysis efficiency and reduces the interference of starch on the enzymatic hydrolysis process through the dynamic tumbling of the drum screen and the circulation renewal of the enzymatic hydrolysis mixture, effectively solving the viscosity problem caused by the high starch content when corn is used as a raw material for producing SOD. The enzymatic hydrolysis efficiency is significantly improved and the activity of SOD is effectively protected. In order to further improve the enzymatic hydrolysis efficiency and the activity of SOD, further improvements are made on the basis of step S2 of Example 1.

[0082] S211. A plurality of rotating blades are also installed in the drum screen; and an object dynamic model is used to simulate the flow of objects during the mixing process to ensure comprehensive and uniform mixing.

[0083] Specifically, multiple blades are installed within the drum screen, initially selecting a spiral blade shape. The blade width accounts for 10%-20% of the drum screen diameter, and the blade length is slightly less than half the drum screen length, ensuring coverage of the main mixing area without adding excessive resistance. The blades are arranged in a staggered pattern with a blade angle of 30-60°. Using CFD computational fluid dynamics, the geometric dimensions of the drum screen, the design parameters of the blades, the physical properties of the material such as density and viscosity, and conditions such as the mixing speed are input to simulate the flow trajectory and mixing effect of the material within the drum screen. Based on the simulation results, the number, shape, arrangement, and rotation speed of the blades are adjusted to achieve a comprehensive and uniform mixing effect. The optimized parameters are then used in the design of drum screens for actual production applications.

[0084] A transmittance sensor is installed on the storage tank of the enzymatic hydrolysis mixture to establish a mapping relationship model between transmittance and starch concentration.

[0085] Specifically:

[0086] The mapping relationship model between transmittance and starch concentration is quantified by historical data and experimental calibration. The analysis and fitting of the relevant quantitative data depends on the actual situation and will not be elaborated in this article.

[0087] For example, through experiments, mixed solution samples with different starch concentrations were collected and their transmittance values ​​were measured. Through data analysis and fitting, a quadratic polynomial regression model was obtained, which can be expressed as:

[0088] C=αT 2 +βT+γ

[0089] Where C is the starch concentration after mapping in g / L, T is the transmittance value in percentage, and α, β, and γ are coefficients obtained by data fitting. In this context, α = 0.001, β = 0.15, and γ = 5.0 are obtained. The mapping relationship model can be quantified as:

[0090] C=0.001T 2+0.15T+5.0

[0091] Suppose we construct a hypothetical dataset: 80% transmittance corresponds to a starch concentration of 12.5 g / L. This dataset contains starch concentration values ​​corresponding to different transmittance values. These data are obtained through experimental measurements and are assumed to have no or very low errors. The measured transmittance is 80%. Substituting this into the model to calculate the starch concentration, we obtain a mapped starch concentration C = 12.6 g / L. This corresponds to a starch concentration close to the actual measured value of 12.5 g / L, indicating a good model fit.

[0092] S212. The camera below the drum screen captures the state of the material in the drum screen and performs feature extraction and recognition, and calculates the immersion ratio of starch particles in the mixed solution to infer the enzymatic hydrolysis process.

[0093] During the mixing process, after stirring stopped, a 16320×9200 high-resolution camera was used to capture an image of the upper portion of the mixed liquid in the drum screen. Within 10 seconds after stirring stopped, a grayscale image of the upper portion of the mixed liquid in the drum screen was captured.

[0094] like Figure 2 As shown, photographing the material state in the drum screen and performing feature extraction and identification, calculating the immersion ratio of starch particles in the mixed solution and estimating the enzymatic hydrolysis process includes the following steps:

[0095] In some embodiments, the state of the material in the drum screen is photographed and feature extraction and identification are performed, and the immersion ratio of starch granules in the mixed solution is calculated to estimate the enzymatic hydrolysis process, specifically including:

[0096] Perform grayscale histogram analysis on the collected original image.

[0097] Specifically, the collected original color image is converted into a grayscale image. A histogram analysis is performed on the grayscale image, that is, the number of pixels of different grayscale levels in the image is counted. A histogram is a two-dimensional chart in which the horizontal axis represents the grayscale level and the vertical axis represents the number of pixels at that grayscale level. Due to the presence of starch granules, the grayscale histogram will have a significant peak near 255 in the higher grayscale value area. Because starch granules are usually brighter than the background, they appear as higher grayscale values ​​in grayscale images. Observe the histogram and look for a clear peak in the higher grayscale value area between 180-255. This peak should be significantly higher than the number of pixels at other grayscale levels, and the width should be relatively narrow, indicating that the pixels corresponding to these grayscale values ​​are more likely to be starch granules. According to the grayscale histogram, the valley value between the starch granule peak and the background peak in the histogram is selected as the threshold to distinguish the starch-enriched area from the mixed liquid background (assuming that the histogram shows a significant starch granule peak near the grayscale value of 200, and the background peak is mainly concentrated below 100. Then a threshold of 150 is selected to distinguish the starch-enriched area from the background).

[0098] Then, filtering and denoising preprocessing operations are performed to extract starch granule features.

[0099] Specifically, image feature extraction begins with color segmentation. Because starch granules differ in color from the background mixture, the image is segmented into K clusters based on the pixel's RGB color signature. Each cluster is assigned a unique label. Once assigned, each pixel is assigned a cluster label, indicating which cluster it belongs to. The color signature of each cluster is analyzed to identify the cluster with the color signature most similar to that of the starch granules, thereby separating the starch granules from the background.

[0100] Morphological operations were applied to further clean the image, remove noise, connect adjacent starch granule regions and extract the contour edges of starch granules.

[0101] Applied morphology includes erosion, dilation, opening, and closing operations. Erosion removes small noise points on the edges of starch granules and shrinks them inward; dilation fills small holes inside starch granules and expands their edges outward; opening further cleans up the image while maintaining the overall shape of the starch granules; and closing connects adjacent starch granule regions to form a complete, connected area.

[0102] Specifically, a circle is selected as the basic structuring element, and its size is adjusted according to the actual size of the starch granules. The structuring element is slid across the image. At each location, if all pixels within the structuring element belong to the starch granule cluster, the pixel at the center of the structuring element is retained; otherwise, the pixel is set to the background. Using the same structuring element as the erosion operation, the structuring element is slid across the image. At each location, if any pixel within the structuring element belongs to the starch granule cluster, the pixel at the center of the structuring element is set to the starch granule. The erosion operation "shrinks" the target area and removes small noise points at the edges. The opening operation is an erosion-then-dilation process. First, the image is eroded to remove small noise points and burrs. Then, the erosion result is dilated to restore the eroded area while maintaining the effect of removing noise and burrs. The closing operation is a dilation-then-erosion process. The image is dilated to fill small holes within the starch granules. Then, the dilation result is eroded to remove extra edges that may have been created during the dilation and connect adjacent granular regions to form a complete connected region. A single erosion or dilation operation may not achieve the desired cleaning effect. At this point, you can consider performing multiple iterative operations on the image, that is, repeatedly performing erosion, dilation, opening, or closing operations until the requirements are met. The contour edge extraction uses the Canny edge detection algorithm. The related operations refer to existing technologies and are not described in detail in this article.

[0103] Through the connected component labeling algorithm, all starch granule regions in the image are identified, and the area and shape characteristics of each region are calculated.

[0104] Among them, in the connected component analysis, the wo-Pass algorithm suitable for binary image processing is selected.

[0105] Specifically, create an output image that is the same size as the input image but has an integer data type (used to store labels). Typically, the labels of background pixels are set to 0, and the initial labels of foreground (i.e., starch granules) pixels are set to temporary values ​​(which will be replaced with unique labels later). Starting from the upper left corner of the image, scan the entire image pixel by pixel. For each foreground pixel (i.e., starch granule pixel), check the pixels in its 4-connected or 8-connected neighborhood. If there is a foreground pixel in the neighborhood and it has not been assigned a label, it is classified as the same connected area as the current pixel and is given the same temporary label. If there is a foreground pixel in the neighborhood and it has been assigned a different temporary label, these different labels are recorded for subsequent processing. At the end of the first scan, record the equivalence relationship between multiple temporary labels, that is, which temporary labels represent the same connected area.

[0106] Based on the equivalence relation recorded in the first pass, a unique identifier is assigned to each connected region. This is usually achieved by traversing all temporary labels and replacing them with the minimum label in their equivalence class. After completing the second pass, a labeled image is output in which each connected region is assigned a unique identifier. The area is calculated by counting the number of pixels within each connected region. Various shape features can be calculated, such as perimeter (calculated by traversing the boundary pixels of the connected region), circularity (estimated by the relationship between area and perimeter), aspect ratio (calculated by the length and width of the minimum enclosing rectangle), etc.

[0107] The extracted features are classified to distinguish starch granules from other impurities.

[0108] Specifically, shape features such as the area, perimeter, and circularity of each region are obtained from connected component analysis as input features. A set of image samples of known categories, including starch granules and other impurities, is collected. Connected component analysis is performed on each sample, and corresponding features are extracted. Because different features may have different dimensions and ranges, the features need to be normalized to ensure that each feature contributes equally to the classifier. A SVM classifier is trained using this normalized feature dataset. During training, the SVM finds a hyperplane that maximizes the separation between different classes. Connected component analysis is performed on new image samples, and corresponding features are extracted. The features are then processed using the same normalization method. The normalized features are input into the trained SVM classifier, which outputs a probability or decision value for each sample belonging to a starch granule or other impurity. Based on the classifier's output, the class of each sample can be determined. For the probability output, a threshold can be set to determine the final class assignment; for the decision value output, the class can be determined directly based on the sign (positive or negative). In the scenario of distinguishing starch granules from other impurities mentioned above, standardization processing specifically refers to a series of transformation operations on the shape features such as area, perimeter, and circularity of each region extracted from the connected region analysis. The relevant specific steps are referred to the existing technology and are not repeated in this article.

[0109] S213. Calculate the number of contact pixels between the starch granule region and the mixed liquid background region to approximately represent the immersion ratio.

[0110] Specifically, we traverse each starch granule region and count the number of edge pixels that are in contact with the mixed liquid background. Based on the pixel size and image resolution, we convert these pixel counts into actual surface area. We then calculate the total number of pixels in each starch granule region and convert this into actual surface area.

[0111] Among them, the immersion ratio is defined as the ratio of the surface area of ​​the starch granules in contact with the mixed liquid to the total surface area of ​​the starch granules, that is, the immersion ratio = the surface area corresponding to the number of contact pixels / the total surface area of ​​the starch granules. Before performing this step, it is necessary to control the experimental condition variables such as enzyme concentration, temperature, and pH value in the laboratory, take images of the starch mixture at different enzymatic hydrolysis time points, and perform the above-mentioned processing flow on these images to calculate the immersion ratio of the starch granules at each time point. Based on the experimental data, a relationship model between the immersion ratio of starch granules and the enzymatic hydrolysis time is established, and the established relationship model is applied. In the actual production process, images of the material status in the drum are collected in real time. The enzymatic hydrolysis process is inferred based on the currently calculated starch granule immersion ratio.

[0112] S221. Set a threshold value according to the acquired total starch amount data, and start the centrifugal separation device when the starch concentration exceeds the set threshold value.

[0113] Specifically, based on actual conditions, the first start-up device concentration reaches x%, starting the first extraction and separation of superoxide dismutase. The second start-up threshold is set to y% (y>x), the third to z% (z>y), and so on until the final extraction and separation of superoxide dismutase is completed. In other words, when the total starch content data obtained in real time exceeds this threshold, the starch concentration in the mixed solution is considered to have reached the standard that requires further purification and treatment.

[0114] For example, the initial superoxide dismutase concentration is 80%, and the target purification level is 99.9%. For the first purification run, a threshold is set to start the equipment when the concentration reaches 85%. The equipment starts, and the purification process begins. Purification stops when the concentration approaches, but does not exceed, 90%. Assume the final purified concentration is 88%. For the second purification run, a threshold is set to start the equipment when the concentration reaches 90%. The equipment starts, and purification continues. Purification stops when the concentration approaches, but does not exceed, 95%. Assume the final purified concentration is 92.5%. For the third purification run, a threshold is set to start the equipment when the concentration reaches 95%. The equipment starts, and the final purification process begins. Purification stops when the concentration approaches the target purity of 99.9%. Assume the final purified concentration is 99.8%.

[0115] S231, repeatedly performing the above operation until the extraction and separation of superoxide dismutase is completed.

[0116] The technical solutions in the above embodiments of the present application have at least the following technical effects or advantages:

[0117] By setting up a stirring system, the starch granules are ensured to be evenly dispersed in the enzymatic hydrolysis mixture, avoiding the viscosity problem caused by local excessive concentration and improving the contact efficiency between the enzyme and corn cells; the transmittance data of the real-time transmittance monitoring system is used to timely reflect the release and dispersion of starch in the mixture, providing a basis for adjusting the stirring parameters; through image analysis and starch immersion amount calculation, non-invasive and real-time enzymatic hydrolysis process monitoring is achieved, providing accurate data support for process adjustment; through the total amount of starch in the mixed liquid control and centrifugal separation process, the excess starch in the mixed liquid is effectively removed, the viscosity is reduced, and the starch resources are recovered at the same time, improving the economic efficiency of the overall process.

[0118] Example 3: The above-mentioned Example 2 significantly improves the enzymatic hydrolysis efficiency in the SOD extraction process of corn raw materials by setting up a stirring system, real-time transmittance monitoring, image analysis and starch immersion amount calculation, mixed liquid starch total amount control and centrifugal separation. In order to further improve the enzymatic hydrolysis efficiency, step S221 is further improved on the basis of Example 2.

[0119] The enzymatically hydrolyzed mixture was centrifuged using a high-speed centrifuge to separate the solid precipitate and the supernatant.

[0120] Among them, the solid precipitate is mainly undissolved starch granules.

[0121] The solid precipitate obtained after centrifugation was collected, dried, weighed using a precision balance, and the mass of the precipitate was recorded.

[0122] Among them, the accuracy of the balance can reach at least 0.01 grams, or one hundredth of a gram.

[0123] Specifically:

[0124] S2211. Calculate the initial amount of corn flour and compare it with the starch content to calculate the theoretical amount of starch that should be obtained.

[0125] Specifically, the mass of the corn starch granule precipitate after separation is recorded as Mn. The known corn starch content percentage P can usually be obtained from product instructions or previous analysis. The theoretical starch amount Ms = Mn*P provides a reference standard for evaluating the completion of the enzymatic hydrolysis process.

[0126] S2212. Calculate the degree of completion of the enzymatic hydrolysis process by comparing the actual amount of starch in the precipitate with the theoretical amount of starch, and obtain the percentage completion of the enzymatic hydrolysis process.

[0127] Among them, the degree of completion of the enzymatic hydrolysis process Ma is the actual amount of starch measured by weighing after drying.

[0128] S2213. Analyze the above steps and evaluate the impact of enzymatic hydrolysis conditions such as temperature, pH value, and enzyme dosage on the process completion.

[0129] The technical solutions in the above embodiments of the present application have at least the following technical effects or advantages:

[0130] By further optimizing the starch analysis step after centrifugation, a quantitative assessment of the degree of completion of the enzymatic hydrolysis process was achieved. By comparing the difference between the actual starch amount and the theoretical starch amount, the efficiency of the enzymatic hydrolysis reaction can be intuitively reflected, providing key data support for process optimization, improving the controllability and predictability of the production process, and thus enhancing product quality and production efficiency.

[0131] The enzymatic hydrolysis efficiency of SOD extraction from corn raw materials was significantly improved through optimization of the stirring system, real-time transmittance monitoring, image analysis and calculation of starch infiltration, total starch content control in the mixed solution, and centrifugal separation.

[0132] Ensure sufficient contact between the enzyme and corn cells, shorten the enzymatic hydrolysis time, and increase the SOD yield; through real-time monitoring and data analysis, achieve precise control of the enzymatic hydrolysis process and reduce human intervention errors; effectively recycle starch resources, reduce waste generation, and improve the economy and environmental protection of the process.

[0133] Example 4: The above Example 3 achieves a quantitative assessment of the completion of the enzymatic hydrolysis process by further optimizing centrifugal separation and starch amount analysis, thereby improving the controllability and predictability of the production process, thereby improving product quality and production efficiency. In order to further improve the enzymatic hydrolysis efficiency, further improvements are made on the basis of Example 3.

[0134] Set up sensors and data logging systems to obtain a continuous, dynamic data set, including the changes in various parameters during the enzymatic hydrolysis process. Monitor and record the enzymatic hydrolysis progress and overall time data of the same batch of materials in real time.

[0135] Data from the first three batches were collected and averaged to establish a baseline standard for the enzymatic hydrolysis operation.

[0136] Among them, the baseline value formula for enzymatic hydrolysis operation is:

[0137]

[0138] n represents the number of data points to be averaged. In this case, it refers to the number of data points in the first three batches (i.e., n = 3, but the formula is written in a more general form that can be applied to any number of batches). batch_i Represents the data value of the i-th batch, Represents the sum of all data values ​​from the first batch to the nth batch. This formula means that by adding the data values ​​of the first three batches (or any specified number of batches), dividing by the number of batches, the average of these data is calculated, and this average is used as the baseline value.

[0139] According to the real-time progress of starch filtering out of the drum screen, the drum screen speed and the mixing time interval of the mixed liquid are dynamically adjusted to achieve the best enzymatic hydrolysis effect.

[0140] Specifically, based on factors such as the viscosity, water content, and gelatinization temperature of the starch raw material, the initial setting of the drum screen speed range can be between 200-600 rpm. According to the real-time progress of starch filtration, the drum screen speed is dynamically adjusted. Subsequent speed adjustments should not exceed 50 rpm each time and should be adjusted every 10-30 minutes. The initial stirring time should be no less than 5 minutes. In the early stage of enzymatic hydrolysis, the stirring time interval can be appropriately shortened to once every 5-10 minutes to promote sufficient contact and reaction between the enzyme and starch. In the middle stage of enzymatic hydrolysis, as the reaction proceeds, the stirring time interval can be appropriately extended to once every 15-20 minutes to reduce energy consumption and equipment wear. In the late stage of enzymatic hydrolysis, when approaching the end point of the reaction, the stirring time interval can be extended or stirring can be stopped to avoid the impact of excessive stirring on the starch structure.

[0141] Combined with the single filtration amount and the overall cumulative amount of starch, the distribution and concentration of starch in the mixed liquid are analyzed, and the drainage and flushing frequency of the centrifuge are automatically adjusted.

[0142] Specifically, a weighing device monitors the starch filtration rate during each centrifugation process in real time, and a data system is established to accumulate and record the total amount. The volume of the mixed liquor is estimated based on the centrifuge feed and discharge volumes, and the starch concentration is then calculated (C = M / V, where C is the concentration, M is the starch mass, and V is the volume of the mixed liquor). Concentration calculations are performed every 10 minutes, synchronized with the filtration rate monitoring. Initially, samples are collected at different locations for analysis every 0.5 hours, with an upper limit of 12% and a lower limit of 8%. If the concentration exceeds the upper limit, the centrifuge flushing frequency automatically increases by 20% until the concentration drops below the upper limit. If the concentration falls below the lower limit, the frequency automatically decreases by 10% until the concentration returns to above the lower limit. The initial flushing frequency is every 30 minutes. For example, if the monitored concentration continues to rise to 12.5%, the flushing frequency will automatically adjust to every 24 minutes. After adjustment, if the concentration drops to 10%, the current frequency will be maintained or fine-tuned as needed. If the concentration continues to fall below 8%, the frequency will automatically adjust to every 33 minutes, and so on.

[0143] When stirring stops, the camera captures the image of the upper part of the mixed liquid in the drum screen and converts it into a grayscale image for analyzing the distribution and concentration of starch granules.

[0144] Among them, the captured color image is converted into a grayscale image, and the grayscale image converts the color value of each pixel into a brightness value between 0-255.

[0145] Through image processing algorithms, the grayscale value changes in different areas of the grayscale image are analyzed to judge the progress and quality of starch filtration and obtain the real-time progress and estimated amount of starch filtration.

[0146] Specifically, during the starch filtration process, the grayscale image is first divided into multiple ROIs (regions of interest), and the grayscale values ​​of the pixels within each region are extracted. These grayscale values ​​directly reflect the presence and concentration of starch granules. By calculating the average grayscale value and grayscale value distribution of each ROI, the average concentration and distribution of starch granules can be determined. With continued filtration, the number of starch granules in the mixed solution decreases, resulting in a decrease in grayscale values. By comparing grayscale images and grayscale value changes at different time points, the trend and rate of starch filtration can be analyzed. Specifically, a continuous decrease in grayscale values ​​indicates that filtration is ongoing and effective; a gradual or stagnant decrease in grayscale values ​​indicates that filtration has reached a stable state or requires operational adjustments. To estimate the amount of starch filtration, a mathematical model is developed based on experimental data and experience to convert grayscale value changes into the amount of starch filtration. This typically involves establishing a linear or nonlinear relationship between grayscale value and starch concentration. By continuously capturing and analyzing images, real-time information on starch filtration progress is obtained, and the remaining starch filtration amount is estimated based on the current filtration progress and grayscale value trends. This estimation process requires reference to historical data and experience to make appropriate predictions and corrections.

[0147] Comprehensively analyze data such as drum screen speed, stirring time interval, centrifugation frequency, image recognition results, etc. to evaluate the effectiveness of current enzymatic hydrolysis parameters.

[0148] Among them, evaluating the effectiveness of the current enzymatic hydrolysis parameters includes: evaluating the enzymatic hydrolysis efficiency to determine whether the current enzymatic hydrolysis parameters can achieve the expected enzymatic hydrolysis efficiency, or whether there is a significant improvement compared with historical data;

[0149] Evaluate product quality to check whether the product quality meets the requirements, including purity, yield, structure, etc. Evaluate energy consumption: analyze whether the energy consumption under the current enzymatic hydrolysis parameters is reasonable and whether there is room for energy saving; evaluate operational stability to determine whether the enzymatic hydrolysis process can run stably without drastic fluctuations or abnormal situations.

[0150] Adjust the enzymatic hydrolysis control parameters based on the evaluation results.

[0151] Among them, the enzymatic hydrolysis control parameters include drum screen speed, stirring time interval, centrifugation frequency, etc.

[0152] For example, based on the above steps, an implementation scenario is simulated as follows:

[0153] The fourth batch of corn flour is now undergoing enzymatic hydrolysis, and the data for the first three batches have been collected and the baseline standards have been calculated. The baseline data for the first three batches are: enzymatic hydrolysis time baseline 120 minutes, drum screen speed baseline 300rpm, stirring time interval baseline 10 minutes, and centrifugation frequency baseline once every 30 minutes. The fourth batch of real-time monitoring data (hypothetical data), initial time 0 minutes, current time 60 minutes, current starch filtration volume 40%, image recognition results show that the starch granule concentration is medium to high. When the starch granule concentration exceeds a certain threshold, the stirring and centrifugation frequency is increased from once every 30 minutes to once every 25 minutes.

[0154] The system records the current enzymatic hydrolysis progress and time data in real time, comparing the current progress with the baseline. It finds that the current 40% starch extraction within 60 minutes is slightly faster than the baseline. Based on real-time monitoring data and image recognition results, the system determines that the current starch granule concentration is high and requires increased agitation to promote the enzymatic hydrolysis reaction. Because the starch extraction progress is faster than expected, the system decides to advance the next centrifugation operation, adjusting the original 30-minute centrifugation cycle to 25-minute cycles, while maintaining the same flushing volume. This ensures effective starch separation without excessive water waste. Each time agitation stops, an image of the mixed liquid within the drum screen is captured and converted to a grayscale image for processing. An image processing algorithm analyzes the grayscale image to confirm the starch extraction progress and compares it to a preset threshold. If the extraction volume approaches the preset upper limit, the system prepares for the next centrifugation operation. The system continuously monitors the enzymatic hydrolysis progress and dynamically adjusts control parameters based on real-time data and image recognition results. If the extraction volume approaches the preset upper limit, the system prepares for the next centrifugation operation.

[0155] The simulation results showed that due to active control and real-time monitoring, the final enzymatic hydrolysis time of the fourth batch was shortened to 105 minutes, which was 15 minutes earlier than the baseline time.

[0156] It should be noted that due to the more efficient enzymatic hydrolysis process, the activity of the product (e.g., glucose) is expected to increase. The specific value needs to be determined experimentally, but generally, the activity is proportional to the efficiency of the enzymatic hydrolysis.

[0157] The technical solutions in the above embodiments of the present application have at least the following technical effects or advantages:

[0158] By introducing advanced technologies such as continuous data monitoring, baseline establishment, active control, and image recognition, intelligent management and optimization of the enzymatic hydrolysis process have been achieved; through real-time data collection and analysis, combined with image recognition technology, the progress of starch filtration can be accurately judged, and the enzymatic hydrolysis control parameters can be dynamically adjusted accordingly; this closed-loop feedback mechanism not only improves the enzymatic hydrolysis efficiency, but also ensures the stability and controllability of the production process; it can significantly shorten the enzymatic hydrolysis time, increase product activity, and at the same time reduce production costs and energy consumption.

[0159] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Various modifications and variations are readily apparent to those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A method for preparing corn superoxide dismutase, characterized in that: The specific steps include: S1 pretreatment: The germinated corn was crushed to 80-120 mesh, the crushed germinated corn was added in a ratio of 1: (2-4) pH = 7.8, 0.05mol / L phosphate buffer, mixed and ground into corn pulp, ultrasonic cell disruption; S2. Enzymatic hydrolysis: S21. The corn pulp after ultrasonic crushing is added to the drum screen with the axis horizontally arranged, and the lower half of the drum is immersed in the enzymatic mixture; start the drum screen, so that the corn material tumbles in the drum while keeping it immersed in the enzymatic mixture; S22. Every 10-15 minutes, the enzymatic mixture was extracted and centrifuged to remove suspended starch granules and other impurities; S23. The clarified liquid after centrifugation is poured back into the drum screen and the enzymatic hydrolysis cycle is repeated 2-3 times; S24. The enzymatic corn syrup was stirred and filtered, the filtrate was collected, and 0.5%-1.5% of the weight of the filtrate was added to the filtrate; S3. Extraction and post-processing: S31. The filtrate is ultrasonically obtained as a liquid, and an activator, a protective agent and a stabilizer are added to the liquid; wherein the activator is manganese chloride and ferrous chloride; the protective agent is a protein disulfide bond protecting agent; the stabilizer is trehalose or burdock oligosaccharide; S32 concentration and drying: the filtrate was placed in a low-temperature vacuum concentrator, evaporated at 22-25 ℃ for 8-15 hours to obtain corn superoxide dismutase multi-enzyme liquid; corn superoxide dismutase multi-enzyme liquid and 1% by weight of silica were mixed and placed in a low-temperature vacuum drying device, freeze-dried to obtain corn superoxide dismutase multi-enzyme powder; A transmittance sensor is also installed on the storage tank of the enzymatic hydrolysis mixture to establish a mapping relationship model between transmittance and starch concentration; specifically: The mapping relationship model between transmittance and starch concentration is quantified by historical data and experimental calibration, and the analysis and fitting of the relevant quantitative data are determined by the actual situation; The camera below the drum screen captures the state of the material in the drum screen and performs feature extraction and recognition, and calculates the immersion ratio of starch particles in the mixed liquid to infer the enzymatic hydrolysis process; Perform grayscale histogram analysis on the collected original image; Then, filtering and denoising preprocessing operations are performed to extract starch granule features; Morphological operations were applied to further clean the image, remove noise, connect adjacent starch granule regions, and extract the contour edges of starch granules; Through the connected region labeling algorithm, all starch granule regions in the image are identified, and the area and shape characteristics of each region are calculated; Classify the extracted features to distinguish starch granules from other impurities; The number of contact pixels between the starch granule area and the mixed solution background area was calculated to approximate the immersion ratio; A threshold is set according to the acquired total starch amount data, and step S221 is performed to start the centrifugal separation device when the starch concentration exceeds the set threshold; After step S221 is completed, step S231 is further performed: the above operations are repeatedly performed until the extraction and separation of superoxide dismutase is completed.

2. The method for preparing corn superoxide dismutase according to claim 1, wherein The axis of the drum screen is arranged horizontally, the diameter of the drum screen hole is smaller than the diameter of the crushed corn particles, one end is open for feeding, and the other end is provided with a discharge port.

3. The method for preparing corn superoxide dismutase according to claim 1, wherein The amount of corn slurry added in S21 is 40%-60% of the volume of the drum screen; the enzymatic hydrolysis mixture includes a complex enzyme and a surfactant, the complex enzyme is a mixture of pectinase, cellulase, hemicellulase and protease, the addition amount of the complex enzyme is 0.5%-2% of the mass of the corn slurry, and the surfactant is sodium dodecyl sulfate, the addition amount of which is 0.5%-0.8% of the mass of the corn slurry; the enzymatic hydrolysis temperature is 45°C-55°C, the pH value is 7.0-8.0, and the enzymatic hydrolysis time is 40-80 minutes.

4. The method for preparing corn superoxide dismutase according to claim 1, wherein Multiple sets of rotating blades are also installed in the drum screen; the object dynamic model is used to simulate the flow of objects during the mixing process to ensure comprehensive and uniform mixing; multiple blades are installed in the drum screen, which are spiral blades. The blade width accounts for 10%-20% of the drum screen diameter, and the blade length is slightly less than half of the drum screen length. They are arranged in a staggered manner, with a blade angle of 30°-60°.

5. The method for preparing corn superoxide dismutase according to claim 1, wherein After the centrifugal separation device is started in step S221, the solid precipitate and the supernatant are separated; the solid precipitate is undissolved starch granules.

6. The method for preparing corn superoxide dismutase according to claim 5, wherein The solid precipitate obtained after centrifugation was collected, dried, and weighed using a precision balance and the mass of the precipitate was recorded, specifically: S2211. Calculate the initial amount of corn flour and starch content, and calculate the theoretical amount of starch Ms that should be obtained; S2212. By comparing the actual amount of starch in the precipitate with the theoretical amount of starch, the completion of the enzymatic hydrolysis process is calculated to obtain the percentage completion of the enzymatic hydrolysis process; Among them, the degree of completion of the enzymatic hydrolysis process Ma is the actual starch amount measured by weighing after drying, and Ms is the theoretical starch amount obtained in S2211; S2213. Evaluate the effects of enzymatic hydrolysis conditions such as temperature, pH, and enzyme dosage on process completion.

7. The method for preparing corn superoxide dismutase according to claim 6, wherein After recording and analyzing the quality of the precipitate, sensors and data recording systems are also set up to obtain continuous and dynamic data sets, including the changes in various parameters during the enzymatic hydrolysis process, and to monitor and record the enzymatic hydrolysis progress and overall time data of the same batch of materials in real time.

8. The method for preparing corn superoxide dismutase according to claim 7, wherein Before enzymatic hydrolysis of each batch of materials, collect data from the first three batches, calculate the average value, and establish the baseline standard for enzymatic hydrolysis operation; the baseline value formula for enzymatic hydrolysis operation is: n represents the number of data points to be averaged. In this implementation scenario, it refers to the number of data points in the first three batches. batch_i Represents the data value of the i-th batch, Represents the sum of all data values ​​from the first batch to the nth batch; the formula means that the average value of these data is calculated by adding the data values ​​of the first three batches and dividing it by the number of batches, and the average value is used as the baseline value.

9. The method for preparing corn superoxide dismutase according to claim 8, wherein According to the real-time progress of starch filtration through the drum screen, the drum screen speed and the mixing time interval are dynamically adjusted to achieve the best enzymatic hydrolysis effect; Combined with the single filtration amount and the overall cumulative amount of starch, the distribution and concentration of starch in the mixed liquid are analyzed, and the drainage and flushing frequency of the centrifuge are automatically adjusted; When stirring stops, the camera captures the image of the upper part of the mixed liquid in the drum screen and converts it into a grayscale image for analyzing the distribution and concentration of starch granules; By using image processing algorithms, the grayscale value changes in different areas of the grayscale image are analyzed to determine the progress and quality of starch filtration and obtain the real-time progress and estimated amount of starch filtration; Comprehensively analyze data such as drum screen speed, stirring time interval, centrifugation frequency, and image recognition results to evaluate the effectiveness of current enzymatic hydrolysis parameters; Adjust the enzymatic hydrolysis control parameters based on the evaluation results.

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