Real-time Monitoring System for Podophyllotoxin Extraction Based on Intelligent Sensors

Abstract

The present invention discloses a real-time monitoring system for the extraction of podophyllotoxin based on intelligent sensors, specifically relating to the field of podophyllotoxin extraction, including a data batch division module, a data acquisition module, a data analysis module, a data comprehensive evaluation module, and a real-time feedback warning module. The data acquisition module includes a raw material data acquisition unit and a feedback data acquisition unit, which are used to collect target data in real time and transmit the collected data to the data analysis module; the data analysis module includes a raw material data analysis unit and a feedback data analysis unit, which are used to analyze the data transmitted by the data acquisition module; the data comprehensive evaluation module includes a real-time monitoring data analysis unit for the extraction of podophyllotoxin by intelligent sensors, which is used to comprehensively analyze the data transmitted by the data analysis module; by dividing various types of data in the process of podophyllotoxin extraction into different acquisition batches, the present invention significantly improves the accuracy and timeliness of monitoring.

Description

Technical Field

[0001] The present invention relates to the technical field of podophyllotoxin extraction, and more specifically, to a real-time monitoring system for podophyllotoxin extraction based on intelligent sensors. Background Art

[0002] Podophyllotoxin is an important medicinal ingredient and has crucial significance in the pharmaceutical field. Traditional podophyllotoxin extraction processes face many challenges, and it is often difficult to achieve ideal states in terms of extraction efficiency and quality control. With the rapid progress of sensor technology and intelligent control technology, it has created new opportunities and changes for the real-time monitoring system of podophyllotoxin extraction. By means of the organic integration of intelligent sensors and intelligent control, key information can be accurately captured during the complex podophyllotoxin extraction process, which helps to optimize the extraction process and ensure product quality, thereby improving the stability and accuracy of the entire extraction process.

[0003] Existing podophyllotoxin extraction monitoring systems usually include a data perception module, a data transmission line, a data processing center, and a monitoring feedback module. The data perception module is responsible for collecting data such as the concentration, temperature, pressure of the extraction solution, and environmental parameters inside the reaction vessel; the collected data is transmitted to the data processing center through the data transmission line, and the data processing center sorts, analyzes, and deeply calculates the data obtained from each monitoring point, and then generates guiding results, which are intuitively displayed through the monitoring feedback module, so as to promptly detect abnormal fluctuations during the extraction process, reduce the probability of unqualified products, and ensure the efficiency and compliance of podophyllotoxin extraction.

[0004] However, the current monitoring system still has defects. For example, in the data perception link, only a limited number of key parameter data are obtained, which makes the dimension of the collected data relatively narrow, destroys the comprehensiveness of the data system, leads to deviations in the data processing results, weakens the accuracy of the results, and is not conducive to the efficient implementation and sustainable development of podophyllotoxin extraction monitoring.

[0005] Therefore, there is an urgent need for a real-time monitoring system for podophyllotoxin extraction based on intelligent sensors to solve the problems of missing data collection and inaccurate data processing results in the existing monitoring system. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a real-time monitoring system for podophyllotoxin extraction based on intelligent sensors, through the following solutions, to solve the problems raised in the above background art.

[0007] To achieve the above object, the present invention provides the following technical solution: A real-time monitoring system for podophyllotoxin extraction based on intelligent sensors, comprising:

[0008] Data batch division module: It is used to determine the data to be collected as target data, divide the target data into different batches in an equal-time division manner, and sequentially label them as 1, 2, ……, n;

[0009] Data acquisition module: It includes a raw material data acquisition unit and a feedback data acquisition unit, which are used to collect the target data in real time and transmit the collected data to the data analysis module; the raw material data acquisition unit is used to collect the raw material cell microbial community scale data, cell structure characteristic data, and raw material cell microenvironment data; the feedback data acquisition unit is used to collect the physical assistance condition data, chemical environment dynamic data, and product state monitoring data;

[0010] Data analysis module: It includes a raw material data analysis unit and a feedback data analysis unit, which are used to analyze the data transmitted by the data acquisition module and transmit the analysis results to the data comprehensive evaluation module; the raw material data analysis unit includes a raw material cell microbial community scale data analysis node, a cell structure characteristic data analysis node, and a raw material cell microenvironment data analysis node; the feedback data analysis unit includes a physical assistance condition data analysis node, a chemical environment dynamic data analysis node, and a product state monitoring data analysis node;

[0011] Data comprehensive evaluation module: It includes an intelligent sensor real-time monitoring data analysis unit for podophyllotoxin extraction, which is used to comprehensively analyze the data transmitted by the data analysis module and transmit the analysis results to the real-time feedback warning module;

[0012] Real-time feedback warning module: It is used to establish a preset value of the podophyllotoxin extraction monitoring rationality index, judge the podophyllotoxin extraction monitoring rationality index value according to the preset value of the podophyllotoxin extraction monitoring rationality index, and send out corresponding signals according to the judgment results.

[0013] Preferably, the raw material cell microbial community scale data includes the number of microbial individuals Ms, the total volume of microbial cells Mv, and the concentration of microbial metabolites Mc; the raw material cell structure characteristic data includes the surface area of the inner membrane system Is and the number of cell vacuoles Vn; the raw material cell microenvironment data includes the mass of cell polysaccharide secretions Ps, the length of cell protein fibers Pl, and the concentration of cell small molecule signaling substances Pe.

[0014] Preferably, the physical assistance condition data includes the average diameter Ud of ultrasonic cavitation bubbles, the microwave penetration depth Md, and the magnitude of stirring shear force Sf; the chemical environment dynamic data includes the number of consumed active groups Ag of the extractant, the absolute value of the change in the pH of the extract Ph, and the remaining mass Bs of the buffer substance in the extract; the product state monitoring data includes the average particle size Cg of podophyllotoxin crystal particles, the turbidity Pt of the podophyllotoxin solution, and the hydration radius Hr of podophyllotoxin molecules.

[0015] Preferably, the raw material cell microbial community scale data analysis node is used to establish a raw material cell microbial community scale data calculation model, import the raw material cell microbial community scale data transmitted by the data acquisition module into the raw material cell microbial community scale data calculation model, and obtain the potential energy coefficient value of podophyllotoxin action on the microbial community. The raw material cell microbial community scale data calculation model is specifically expressed as:

[0016]

[0017] Among them, α i represents the potential energy coefficient value of podophyllotoxin action on the microbial community calculated for the i-th time, Ms i represents the number of individual cell microorganisms collected for the i-th time, Mv i represents the total volume of cell microorganisms collected for the i-th time, Mc i represents the concentration of cell microbial metabolites collected for the i-th time.

[0018] Preferably, the cell structure feature data analysis node is used to establish a cell structure feature data calculation model, import the cell structure feature data transmitted by the data acquisition module into the cell structure feature data calculation model, and obtain the extraction hindrance coefficient value of podophyllotoxin by the cell structure. The cell structure feature data calculation model is specifically expressed as:

[0019]

[0020] Among them, β i represents the extraction hindrance coefficient value of podophyllotoxin by the cell structure calculated for the i-th time, Is i represents the surface area of the endomembrane system of the cells collected for the i-th time, σ represents the standard deviation of the surface area of the endomembrane system of the collected cells, μ represents the mean value of the surface area of the endomembrane system of the collected cells, Vn i represents the number of vacuoles of the cells collected for the i-th time.

[0021] Preferably, the raw material cell microenvironment data analysis node is used to establish a raw material cell microenvironment data calculation model, import the raw material cell microenvironment data transmitted by the data acquisition module into the raw material cell microenvironment data calculation model, and obtain the extraction regulation coefficient value of podophyllotoxin by the extracellular environment. The raw material cell microenvironment data calculation model is specifically expressed as:

[0022]

[0023] Among them, γ i represents the extraction regulation coefficient value of podophyllotoxin by the extracellular environment calculated for the i-th time, Ps i represents the mass of cell polysaccharide secretions collected for the i-th time, Pl iRepresents the length of the cellular protein fibers collected at the i-th collection, Pe i Represents the concentration of the small molecule signaling substances in the cells collected at the i-th collection, Pe def Represents the initial concentration of the small molecule signaling substances in the cells.

[0024] Preferably, the physical assistance condition data analysis node is used to establish a physical assistance condition data calculation model, import the physical assistance condition data transmitted by the data acquisition module into the physical assistance condition data calculation model, and obtain the physical extraction synergy efficiency coefficient value. The physical assistance condition data calculation model is specifically expressed as:

[0025]

[0026] Wherein, Represents the physical extraction synergy efficiency coefficient value calculated at the i-th time, Ud i Represents the average diameter of the ultrasonic cavitation bubbles collected at the i-th collection, Md i Represents the microwave penetration depth collected at the i-th collection, Sf i Represents the magnitude of the stirring shear force collected at the i-th collection.

[0027] Preferably, the chemical environment dynamic data analysis node is used to establish a chemical environment dynamic data calculation model, import the chemical environment dynamic data transmitted by the data acquisition module into the chemical environment dynamic data calculation model, and obtain the chemical extraction environment balance coefficient value. The chemical environment dynamic data calculation model is specifically expressed as:

[0028]

[0029] Wherein, l i Represents the chemical extraction environment balance coefficient value calculated at the i-th time, Ag i Represents the number of consumed active groups of the extractant collected at the i-th collection, Ag def Represents the initial number of active groups of the extractant, Ph i Represents the absolute value of the change in the acidity and alkalinity of the extract collected at the i-th collection, Bs i Represents the remaining mass of the buffer substance in the extract collected at the i-th collection, Bs def Represents the initial concentration of the buffer substance in the extract.

[0030] Preferably, the product state monitoring data analysis node is used to establish a product state monitoring data calculation model, import the product state monitoring data transmitted by the data acquisition module into the product state monitoring data calculation model, and obtain the extraction product quality optimization coefficient value. The product state monitoring data calculation model is specifically expressed as:

[0031]

[0032] Wherein, χi It represents the optimization coefficient value of the mass of the extracted product for the i-th calculation, Cg i It represents the average particle size of the podophyllotoxin crystal particles collected for the i-th time, Pt i It represents the turbidity of the podophyllotoxin solution collected for the i-th time, Hr i It represents the hydration radius of the podophyllotoxin molecule collected for the i-th time.

[0033] Preferably, the real-time monitoring data analysis unit for podophyllotoxin extraction by the intelligent sensor is used to establish a real-time monitoring data calculation model for podophyllotoxin extraction by the intelligent sensor, and import the potential energy coefficient value of the action of podophyllotoxin on the microbial community, the extraction hindrance coefficient value of podophyllotoxin by the cell structure, the extraction regulation coefficient value of podophyllotoxin by the extracellular environment, the physical extraction synergy efficiency coefficient value, the chemical extraction environment balance coefficient value, and the optimization coefficient value of the mass of the extracted product transmitted by the data analysis module into the real-time monitoring data calculation model for podophyllotoxin extraction by the intelligent sensor to obtain the rationality index value of podophyllotoxin extraction monitoring; the real-time monitoring data calculation model for podophyllotoxin extraction by the intelligent sensor is specifically expressed as:

[0034]

[0035] Among them, RM represents the rationality index value of the calculated podophyllotoxin extraction monitoring,

[0036]

[0037] α i It represents the potential energy coefficient value of the action of podophyllotoxin on the microbial community calculated for the i-th time, β i It represents the extraction hindrance coefficient value of podophyllotoxin by the cell structure calculated for the i-th time, γ i It represents the extraction regulation coefficient value of podophyllotoxin by the extracellular environment calculated for the i-th time, It represents the physical extraction synergy efficiency coefficient value calculated for the i-th time, l i It represents the chemical extraction environment balance coefficient value calculated for the i-th time, χ i It represents the optimization coefficient value of the mass of the extracted product calculated for the i-th time, i represents starting from the i-th number, and n represents ending at the n-th number.

[0038] The technical effects and advantages of the present invention:

[0039] 1. By dividing various types of data in the podophyllotoxin extraction process into different acquisition batches, the present invention significantly improves the accuracy and timeliness of monitoring. With the help of intelligent sensors, data on the scale of the microbial community of raw material cells, data on the cell structure characteristics, data on the microenvironment of raw material cells, data on physical assistance conditions, data on the dynamic chemical environment, and data on the monitoring of the product state are collected through multiple channels. This multi-faceted data acquisition mode breaks through the limitations of previous monitoring methods and constructs a more complete and reliable data foundation for subsequent data analysis;

[0040] 2. Use data analysis to deeply analyze the collected data, thereby calculating the podophyllotoxin action potential coefficient value of the microbial community, the podophyllotoxin extraction hindrance coefficient value of the cell structure, the podophyllotoxin extraction regulation coefficient value of the extracellular environment, the physical extraction synergy efficiency coefficient value, the chemical extraction environment balance coefficient value, and the extraction product quality optimization coefficient value, and accurately locate the links where problems may occur. By comprehensively evaluating and deeply integrating the data processing results, the reliability and accuracy of the monitoring results are greatly improved;

[0041] 3. Through continuous monitoring and uninterrupted tracking, once abnormal fluctuations are detected, an alarm signal is immediately issued, and relevant technical personnel and operators can timely grasp the real-time situation and potential hidden dangers of podophyllotoxin extraction, and quickly adjust and optimize the extraction process or operation flow, providing strong guarantee for achieving efficient and accurate podophyllotoxin extraction and scientific and reasonable production decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a schematic diagram of the overall structure of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0044] As shown in the attached Figure 1 The real-time monitoring system for podophyllotoxin extraction based on intelligent sensors includes a system operation database, a system central processor, and a user information terminal, and also includes a data batch division module, a data acquisition module, a data analysis module, a data comprehensive evaluation module, and a real-time feedback warning module.

[0045] The system operation database includes all data texts of the real-time monitoring system for podophyllotoxin extraction based on intelligent sensors, and collects information texts output by each module in real time. The system central processor is used to centrally control the information text instructions output by each module. The user information terminal is an information output device that receives the real-time monitoring system for podophyllotoxin extraction based on intelligent sensors.

[0046] The data batch division module is used to determine the data to be collected as target data, divide the target data into different batches in an equal-time division manner, and sequentially label them as 1, 2,..., n.

[0047] In this embodiment, it should be specifically noted that: the equal-time division method is divided by the background system operation database according to the characteristics of each target data. For the real-time requirements of each type of target data, it is collected once every equal period of time and divided into different collection times.

[0048] The data acquisition module includes a raw material data acquisition unit and a feedback data acquisition unit, which are used to acquire target data in real time and transmit the acquired data to the data analysis module; the raw material data acquisition unit is used to acquire raw material cell microbial community scale data, cell structure characteristic data, and raw material cell microenvironment data; the feedback data acquisition unit is used to acquire physical auxiliary condition data, chemical environment dynamic data, and product state monitoring data.

[0049] In this embodiment, it should be specifically noted that: the raw material cell microbial community scale data includes the number of microbial individuals Ms in the cell, the total volume Mv of microbial cells in the cell, and the concentration Mc of microbial metabolites in the cell; the raw material cell structure characteristic data includes the surface area Is of the inner membrane system in the cell and the number Vn of cell vacuoles; the raw material cell microenvironment data includes the mass Ps of cell polysaccharide secretions, the length Pl of cell protein fibers, and the concentration Pe of cell small molecule signaling substances; the physical auxiliary condition data includes the average diameter Ud of ultrasonic cavitation bubbles, the penetration depth Md of microwaves, and the magnitude Sf of stirring shear force; the chemical environment dynamic data includes the consumption quantity Ag of active groups of the extractant, the absolute value Ph of the change in the acidity and alkalinity of the extract solution, and the remaining mass Bs of the buffer substance in the extract solution; the product state monitoring data includes the average particle size Cg of podophyllotoxin crystal particles, the turbidity Pt of the podophyllotoxin solution, and the hydration radius Hr of podophyllotoxin molecules.

[0050] The number of individual cell microorganisms directly affects the intensity of their population metabolic activities. A larger number of microorganisms may consume more intracellular resources, change the intracellular material composition and microenvironment, and thus affect the synthesis, storage, and stability of podophyllotoxin. For example, certain microorganisms may participate in the metabolism of podophyllotoxin precursor substances, and changes in their numbers will alter the flux of the podophyllotoxin synthesis pathway; or the accumulation of metabolic wastes produced by microbial metabolism may lead to fluctuations in intracellular pH, threatening the chemical structure stability of podophyllotoxin. The collection method is as follows: First, finely dissect the raw plant tissue from which podophyllotoxin is extracted to obtain fresh and representative cell samples. Then, gently break the cells using a special cell lysate to release the microorganisms therein. Gradiently dilute the lysate containing microorganisms to obtain single, dispersed microbial colonies during subsequent cultivation. Uniformly spread the diluted lysate on a solid medium plate specifically designed for the growth of this type of microorganism and culture it for a period of time under suitable temperature, humidity, and gas environments. After the cultivation ends, use a colony counter to count the microbial colonies grown on the plate, and then calculate the number of individual microorganisms in the original cells by backtracking according to the dilution factor.

[0051] The total volume of the cell microorganisms reflects the physical space they occupy within the cell. A larger total volume means that it may squeeze the storage space of podophyllotoxin or form a physical barrier within the cell, hindering the transportation and diffusion paths of podophyllotoxin. In addition, when the microbial cell volume is large, its cell membrane surface area is also relatively large, which may undergo non-specific adsorption or specific binding with podophyllotoxin, reducing the amount of extractable podophyllotoxin. The collection method is as follows: Collect fresh raw plant tissue and use cryosectioning technology to prepare cell sections. The section thickness needs to be precisely controlled at the micron level to ensure clear observation of the internal cell structure. Place the sections under an electron microscope, adjust the appropriate magnification, and image the microorganisms within the cells. With the help of image analysis software, outline the contours of each microbial cell. The software automatically calculates the two-dimensional area of the microbial cells based on the contours, and then combines the section thickness to obtain the volume of a single microbial cell through the volume calculation formula. Finally, sum up the volumes of all microbial cells to obtain the total volume of the cell microorganisms within the cell.

[0052] The concentration of the cell microbial metabolites affects the chemical reactions of podophyllotoxin. Organic acids may change the intracellular pH value, affect the ionization state of podophyllotoxin, and thus change its solubility and stability; enzymes may catalyze the structural modification or degradation reactions of podophyllotoxin, reducing its activity and extraction efficiency. The collection method is as follows: After obtaining the raw material plant cell samples, use gentle physical crushing methods to break the cells and release the microbial metabolites therein. Centrifugation technology is used to separate the cell debris and the supernatant, and the supernatant is the crude extract containing the microbial metabolites. High-performance liquid chromatography technology is used to analyze the crude extract. First, select a suitable chromatographic column, set the composition and flow rate of the mobile phase. After injection, according to the retention time and peak area of the organic acid standard, calculate the concentration of the organic acid metabolites in the sample by comparison.

[0053] The surface area of the intracellular endomembrane system affects the reaction sites and reaction area of podophyllotoxin synthesis and modification. On the other hand, during the extraction process, podophyllotoxin may bind tightly to the endomembrane system or be encapsulated therein, increasing the difficulty and complexity of extraction, and stronger extraction conditions are required to dissociate it from the endomembrane system. The collection method is as follows: Take fresh raw material plant tissues and fix them with fixatives such as glutaraldehyde to maintain the integrity of the cell structure. The fixed tissues are dehydrated with gradient alcohol and then embedded with embedding agents such as epoxy resin. Use an ultramicrotome to cut the embedded tissues into ultra-thin sections. Place the sections under a transmission electron microscope for observation. At high magnification, the endomembrane system presents a clear membranous structure. With the help of image analysis software, outline the contours of each membrane structure of the endomembrane system, and the software automatically calculates the surface area of each membrane structure, and finally accumulates to obtain the surface area of the intracellular endomembrane system.

[0054] The number of cell vacuoles affects the distribution of podophyllotoxin and the difficulty of releasing podophyllotoxin from the vacuoles. At the same time, the membrane structure and components of the vacuoles may also interact with podophyllotoxin, affecting its extraction efficiency and stability. The collection method is as follows: Make temporary sections of the raw material plant tissues, which can be done by hand sectioning or paraffin sectioning. For hand sectioning, cut the fresh tissues into thin slices and place them directly on the glass slides; paraffin sectioning requires a series of steps such as fixation, dehydration, clearing, wax infiltration, embedding, and sectioning. After the section preparation is completed, stain the sections with a specific vacuole staining agent to make the vacuoles show obvious colors. Observe the stained sections under an optical microscope and count the number of cell vacuoles with the help of image analysis software.

[0055] The quality of the extracellular polysaccharide secretion of the cells affects the direct contact between the extractant and the cell surface and the extraction efficiency of the extractant for podophyllotoxin. At the same time, the polysaccharide secretion may adsorb podophyllotoxin, encapsulating it and making it difficult to be extracted, or being extracted together with podophyllotoxin during the extraction process, increasing the difficulty of subsequent separation and purification. The collection method is as follows: collect the culture solution or extracellular fluid containing the raw plant cells, and use the ultrafiltration centrifugation technique. Select an ultrafiltration membrane with an appropriate cut-off molecular weight to separate the macromolecular polysaccharides from the small molecules. Collect the concentrated polysaccharide solution after ultrafiltration, and use the freeze-drying technique to dry the polysaccharide into a solid powder. Weigh a certain amount of the dried polysaccharide powder with a precision balance, and then calculate the quality of the extracellular polysaccharide secretion of the cells in combination with the statistical results of the cell numbers in the previous culture solution or extracellular fluid.

[0056] The length of the extracellular protein fibers of the cells affects the density of the network. Longer protein fibers will make the network denser, hindering the diffusion and penetration of the extractant outside the cells and limiting the speed and amount of the extractant reaching the cell surface; and the protein fibers may specifically or non-specifically bind to podophyllotoxin, affecting the release and extraction of podophyllotoxin. The collection method is as follows: extract the extracellular protein fibers from the raw plant tissue, and a mild protein extraction buffer can be used for extraction. After the extracted protein fiber solution is appropriately diluted, it is dropped on a specially treated glass slide to evenly disperse the protein fibers. Use an atomic force microscope to scan the protein fibers on the glass slide. When the probe of the atomic force microscope scans the surface of the sample, the three-dimensional morphology information of the protein fibers is obtained by detecting the change in the interaction force between the probe and the sample surface. With the help of image analysis software, measure the length of the protein fibers in the three-dimensional image, and take the average value of the lengths of multiple protein fibers as the length of the extracellular protein fibers.

[0057] The concentration of the extracellular small molecule signaling substances of the cells participates in regulating the physiological activities of the cells, including the synthesis and transport of podophyllotoxin. Changes in the concentration of certain signaling substances may induce or inhibit the expression of genes related to podophyllotoxin synthesis, thereby changing the content of podophyllotoxin in the cells; or affecting the activity of the intracellular transport system, changing the distribution and transport direction of podophyllotoxin in the cells, and indirectly affecting its extraction efficiency. The collection method is as follows: collect the extracellular fluid around the raw plant cells, and use solid-phase extraction technology to enrich and purify the small molecule signaling substances in the extracellular fluid. Derivatize the enriched sample to improve its response signal in the detection instrument. Then use ultra-high performance liquid chromatography-tandem mass spectrometry technology for analysis. First, select an appropriate chromatographic column and mobile phase, and then perform qualitative and quantitative analysis according to the characteristic ion pairs of the signaling molecules and their fragmentation rules in the mass spectrometry to determine its concentration in the extracellular fluid.

[0058] The average diameter of the ultrasonic cavitation bubbles affects the plant cell structure and the release of podophyllotoxin. An appropriate average bubble diameter can generate a moderate impact force, which can effectively destroy the cells without damaging the molecular structure of podophyllotoxin due to excessive impact force. If the bubble diameter is too large, the impact force generated during rupture is too concentrated and strong, which may break the chemical bonds in the podophyllotoxin molecule and reduce its activity. If the bubble diameter is too small, the generated impact force is insufficient to fully destroy the cell structure and affects the release efficiency of podophyllotoxin. The collection method is as follows: In the ultrasonic extraction device, an extraction solution containing podophyllotoxin raw materials is added, and a small amount of tiny tracer particles are uniformly mixed in the extraction solution. These tracer particles will move with the movement of the liquid in the ultrasonic field, and their movement trajectories are affected by the ultrasonic cavitation bubbles. During the ultrasonic extraction process, a high-speed camera is used to photograph a specific area in the extraction solution, and a special lighting technique is used during the photographing to clearly capture the images of the tracer particles and cavitation bubbles. After the photographing is completed, the video images are analyzed frame by frame using image analysis software to identify the contours of the cavitation bubbles, calculate the diameter of each bubble, and take the average value after statistically analyzing multiple bubble diameters to obtain the average diameter of the ultrasonic cavitation bubbles.

[0059] The microwave penetration depth determines the distribution of microwave energy inside the raw materials. When the penetration depth is sufficient, the microwave can uniformly heat the inside of the raw materials, enabling podophyllotoxin to dissolve into the extraction solution from the cells faster at an appropriate temperature. If the penetration depth is insufficient, a temperature gradient will appear inside the raw materials. The part close to the microwave source may have too high a temperature, which may cause the degradation of podophyllotoxin, while the part far from the microwave source may have too low a temperature, resulting in low extraction efficiency and affecting the uniformity and efficiency of podophyllotoxin extraction. The collection method is as follows: In the microwave extraction device, a container containing podophyllotoxin raw materials is placed, and high-precision microwave field strength sensors are inserted at different depth positions inside the container. The microwave source is turned on and operated for a period of time at the set microwave power and frequency. The sensors continuously monitor the microwave field strength at each depth position. According to the attenuation law of microwave propagation in the medium, by comparing the field strength data at different depth positions, the microwave penetration depth is calculated.

[0060] The magnitude of the stirring shear force affects the dispersion degree of the raw material particles in the extraction solution and the contact area between the raw materials and the extractant. At the same time, the shear force helps to break the cell aggregates, making the cells more easily penetrated and acted upon by the extractant, and promoting the dissolution of podophyllotoxin. However, when the stirring shear force is too large, it may cause mechanical shear damage to the podophyllotoxin molecule, reducing its activity and purity. The collection method is as follows: A micro force sensor is installed on the stirring paddle of the stirring extraction device, and the sensor is connected to a data acquisition system. During the extraction process, as the stirring paddle rotates, the force sensor continuously measures the resistance received by the stirring paddle, and this resistance is the stirring shear force. The data acquisition system records the shear force data at different stirring speeds, and the average value is taken after multiple measurements as the magnitude of the stirring shear force under specific extraction conditions.

[0061] The consumption quantity of the active groups of the extractant reflects the degree of reaction between the extractant and podophyllotoxin as well as other components in the raw material. As the extraction process progresses, the active groups continuously combine with podophyllotoxin or participate in other chemical reactions, resulting in a decrease in the number of active groups and a gradual decline in the extraction ability of the extractant. When too many active groups are consumed, the extractant may no longer be able to effectively extract podophyllotoxin, and it is necessary to supplement or replace the extractant to ensure the continuous progress of the extraction process and the extraction efficiency. The collection method is as follows: Before the start of the extraction process, accurately measure the initial content of the active groups in the extractant. For extractants containing hydroxyl groups, chemical titration methods can be used, such as reacting with acylating reagents and calculating the hydroxyl group content by titrating the remaining acylating reagents. For extractants containing amino groups, the number of amino groups can be determined by reacting with a specific acid and then back-titrating the excess acid with a base. During the extraction process, a certain amount of the extract is taken out at regular intervals, and the remaining amount of the active groups in the extractant is measured using the same method as for the initial content determination. The consumption quantity of the active groups is calculated by the difference between the initial quantity and the remaining quantity.

[0062] The absolute value of the change in the pH of the extract has an important impact on the chemical stability and ionization state of podophyllotoxin. Different podophyllotoxin molecules have different solubilities and activities at different pH values. Excessive changes in pH may cause acid-base catalyzed reactions of podophyllotoxin molecules, such as hydrolysis, isomerization, etc., resulting in changes in the structure of podophyllotoxin, a decrease or loss of activity. In addition, the change in pH may also affect the dissociation state of the active groups of the extractant, thereby changing the interaction mode and intensity between the extractant and podophyllotoxin, and affecting the extraction efficiency and product quality. The collection method is as follows: Install a high-precision pH electrode in the extraction container, connect the electrode to a pH meter, and the pH meter can display the pH value of the extract in real time. Before the start of the extraction process, record the initial pH value. As the extraction progresses, the pH meter automatically records the pH value at regular intervals, calculates the difference between each recorded value and the initial pH value, and takes the absolute value as the absolute value of the change in the pH of the extract.

[0063] The remaining mass of the buffer substance in the extract affects the stability of the extract in maintaining pH. A sufficient remaining amount of the buffer substance can resist the acid-base changes caused by the dissolution of raw material components or chemical reactions, keep the pH value of the extract within the range suitable for podophyllotoxin extraction, and ensure the stability and repeatability of the extraction process; when the remaining amount of the buffer substance is insufficient, the pH value of the extract is likely to fluctuate, possibly exceeding the pH range in which podophyllotoxin stably exists, resulting in the degradation of podophyllotoxin or a decrease in extraction efficiency. The collection method is as follows: Before extraction, accurately weigh and record the mass of the buffer substance added to the extract. During the extraction process, regularly take out a certain amount of the extract and determine the content of the buffer substance by chemical analysis methods. For example, for phosphate buffer solution, the remaining amount of the buffer substance can be determined by measuring the concentration of phosphate ions in the solution. The specific method can use ion chromatography. Inject the extract into the ion chromatograph, separate the phosphate ions using an ion exchange column, and calculate its concentration by comparing the response signal of the phosphate ions on the detector with the standard curve, and then calculate the remaining mass of the buffer substance.

[0064] The average particle size of the podophyllotoxin crystal particles has a crucial impact on its subsequent separation, purification, and product quality. A smaller particle size means a larger specific surface area of the crystal, higher efficiency in separating from impurities during operations such as filtration and washing, and is conducive to improving product purity; while a larger particle size may cause impurities to be embedded inside the crystal, and may not be fully separated from impurities due to reasons such as the fast sedimentation rate of the particles during the separation process, affecting product quality. In addition, the particle size also affects the dissolution rate of podophyllotoxin, and thus affects its performance in subsequent applications such as preparations. The collection method is as follows: After the extraction is completed, obtain a solution sample containing podophyllotoxin crystals. Place the sample in the sample cell of a laser particle size analyzer. The laser particle size analyzer irradiates the sample by emitting a laser beam, and the crystal particles will cause light scattering. The instrument calculates the particle size distribution of the crystal particles based on the angle and intensity distribution of the scattered light, using relevant algorithms such as Mie scattering theory. Conduct statistical analysis on the particle size distribution data and calculate the average value of the particle sizes of all crystal particles to obtain the average particle size of the podophyllotoxin crystal particles.

[0065] The turbidity of the podophyllotoxin solution reflects the impurity content in the podophyllotoxin solution and the aggregation of podophyllotoxin itself, etc. Higher turbidity usually indicates the presence of more insoluble impurities, colloidal substances in the solution, or larger aggregates formed by podophyllotoxin molecules. The presence of impurities may interfere with the subsequent purification process of podophyllotoxin and reduce the product purity; the podophyllotoxin aggregates may affect its activity and stability, and problems such as precipitation and deterioration may occur during storage or further processing. By monitoring the turbidity, the quality status of the solution can be judged in a timely manner so as to take corresponding treatment measures, such as further filtration, optimizing the crystallization conditions, etc. The collection method is as follows: Inject an appropriate amount of the podophyllotoxin solution into the measuring cell of the turbidimeter. The turbidimeter emits a light beam through the solution, detects the scattering and absorption of light by the suspended particles in the solution, and converts it into the corresponding turbidity value. Before measurement, the turbidimeter needs to be calibrated with a standard turbidity solution to ensure the accuracy of the measurement. During measurement, the presence of air bubbles in the solution should be avoided because air bubbles will interfere with the propagation of light and affect the measurement results. At the same time, to ensure the repeatability of the measurement, multiple measurements should be carried out under the same conditions such as temperature and stirring state, and the average value is taken as the turbidity value of the podophyllotoxin solution.

[0066] The hydrated radius of the podophyllotoxin molecule reflects its actual existence state and size in the solution. The size of the hydrated radius affects the interaction of podophyllotoxin with other substances and its behavior during the separation and purification process. For example, in the membrane separation process, the hydrated radius determines whether the podophyllotoxin molecule can pass through a membrane with a specific pore size; in ion exchange chromatography, the hydrated radius will affect the binding and elution behavior of the podophyllotoxin molecule with the ion exchange resin. In addition, the hydrated radius is also related to the solubility, stability and other properties of podophyllotoxin, and has important guiding significance for optimizing the extraction and purification process. The collection method is as follows: First, prepare a solution sample of podophyllotoxin to ensure that the solution concentration is within a suitable measurement range. Using dynamic light scattering technology, irradiate the laser beam onto the solution sample. The podophyllotoxin molecules in the solution and the hydrated layer around them will cause a Doppler frequency shift of the scattered light. By detecting the frequency shift of the scattered light and using relevant theories such as the Stokes-Einstein equation, the diffusion coefficient of the podophyllotoxin molecule is calculated. Then, combined with physical parameters such as the viscosity of the solution, the hydrated radius of the podophyllotoxin molecule is calculated according to a specific calculation formula.

[0067] The data analysis module includes a raw material data analysis unit and a feedback data analysis unit, which are used to analyze the data transmitted by the data collection module and transmit the analysis results to the data comprehensive evaluation module; the raw material data analysis unit includes a raw material cell microbial community scale data analysis node, a cell structure characteristic data analysis node, and a raw material cell microenvironment data analysis node; the feedback data analysis unit includes a physical auxiliary condition data analysis node, a chemical environment dynamic data analysis node, and a product state monitoring data analysis node.

[0068] In this embodiment, it should be specifically noted that: the raw material cell microbial community scale data analysis node is used to establish a calculation model for the raw material cell microbial community scale data, import the raw material cell microbial community scale data transmitted by the data acquisition module into the calculation model for the raw material cell microbial community scale data, and obtain the microbial community podophyllotoxin action potential coefficient value. The calculation model for the raw material cell microbial community scale data is specifically expressed as:

[0069]

[0070] where α i represents the microbial community podophyllotoxin action potential coefficient value calculated for the i-th time, Ms i represents the number of individual cell microorganisms collected for the i-th time, Mv i represents the total volume of the cell microorganisms collected for the i-th time, Mc i represents the concentration of the metabolite of the cell microorganisms collected for the i-th time.

[0071] In this embodiment, it should be specifically noted that: the cell structure feature data analysis node is used to establish a calculation model for the cell structure feature data, import the cell structure feature data transmitted by the data acquisition module into the calculation model for the cell structure feature data, and obtain the cell structure podophyllotoxin extraction hindrance coefficient value. The calculation model for the cell structure feature data is specifically expressed as:

[0072]

[0073] where β i represents the cell structure podophyllotoxin extraction hindrance coefficient value calculated for the i-th time, Is i represents the surface area of the inner membrane system of the cells collected for the i-th time, σ represents the standard deviation of the surface area of the inner membrane system of the collected cells, μ represents the mean value of the surface area of the inner membrane system of the collected cells, Vn i represents the number of vacuoles of the cells collected for the i-th time.

[0074] In this embodiment, it should be specifically noted that: the raw material cell microenvironment data analysis node is used to establish a calculation model for the raw material cell microenvironment data, import the raw material cell microenvironment data transmitted by the data acquisition module into the calculation model for the raw material cell microenvironment data, and obtain the extracellular environment podophyllotoxin extraction regulation coefficient value. The calculation model for the raw material cell microenvironment data is specifically expressed as:

[0075]

[0076] where γ i represents the extracellular environment podophyllotoxin extraction regulation coefficient value calculated for the i-th time, Ps iRepresents the quality of the cell polysaccharide secretion collected in the i-th collection, Pl i Represents the length of the cell protein fiber collected in the i-th collection, Pe i Represents the concentration of the small molecule signaling substance in the cell collected in the i-th collection, Pe def Represents the initial concentration of the small molecule signaling substance in the cell.

[0077] In this embodiment, specifically, it should be noted that: the physical auxiliary condition data analysis node is used to establish a physical auxiliary condition data calculation model, import the physical auxiliary condition data transmitted by the data acquisition module into the physical auxiliary condition data calculation model, and obtain the physical extraction synergy efficiency coefficient value. The physical auxiliary condition data calculation model is specifically expressed as:

[0078]

[0079] Among them, Represents the physical extraction synergy efficiency coefficient value calculated in the i-th time, Ud i Represents the average diameter of the ultrasonic cavitation bubbles collected in the i-th collection, Md i Represents the microwave penetration depth collected in the i-th collection, Sf i Represents the magnitude of the stirring shear force collected in the i-th collection.

[0080] In this embodiment, specifically, it should be noted that: the chemical environment dynamic data analysis node is used to establish a chemical environment dynamic data calculation model, import the chemical environment dynamic data transmitted by the data acquisition module into the chemical environment dynamic data calculation model, and obtain the chemical extraction environment balance coefficient value. The chemical environment dynamic data calculation model is specifically expressed as:

[0081]

[0082] Among them, l i Represents the chemical extraction environment balance coefficient value calculated in the i-th time, Ag i Represents the number of consumed active groups of the extractant collected in the i-th collection, Ag def Represents the initial number of active groups of the extractant, Ph i Represents the absolute value of the change in the acidity and alkalinity of the extract collected in the i-th collection, Bs i Represents the remaining mass of the buffer substance in the extract collected in the i-th collection, Bs def Represents the initial concentration of the buffer substance in the extract.

[0083] In this embodiment, specifically, it should be noted that: the product state monitoring data analysis node is used to establish a product state monitoring data calculation model, import the product state monitoring data transmitted by the data acquisition module into the product state monitoring data calculation model, and obtain the extraction product quality optimization coefficient value. The product state monitoring data calculation model is specifically expressed as:

[0084]

[0085] Among them, χ i represents the value of the extraction product quality optimization coefficient for the i-th calculation, Cg i represents the average particle size of the podophyllotoxin crystal particles collected in the i-th time, Pt i represents the turbidity of the podophyllotoxin solution collected in the i-th time, Hr i represents the hydration radius of the podophyllotoxin molecule collected in the i-th time.

[0086] The data comprehensive evaluation module includes a real-time monitoring data analysis unit for intelligent sensor podophyllotoxin extraction, which is used to comprehensively analyze the data transmitted by the data analysis module and transmit the analysis results to the real-time feedback warning module.

[0087] In this embodiment, specifically, it should be noted that: the real-time monitoring data analysis unit for intelligent sensor podophyllotoxin extraction is used to establish a real-time monitoring data calculation model for intelligent sensor podophyllotoxin extraction, and import the podophyllotoxin action potential energy coefficient value of the microbial community, the podophyllotoxin extraction hindrance coefficient value of the cell structure, the podophyllotoxin extraction regulation coefficient value of the extracellular environment, the physical extraction synergy efficiency coefficient value, the chemical extraction environment balance coefficient value, and the extraction product quality optimization coefficient value transmitted by the data analysis module into the real-time monitoring data calculation model for intelligent sensor podophyllotoxin extraction to obtain the podophyllotoxin extraction monitoring rationality index value; the real-time monitoring data calculation model for intelligent sensor podophyllotoxin extraction is specifically expressed as:

[0088]

[0089] Among them, RM represents the calculated podophyllotoxin extraction monitoring rationality index value,

[0090] α i represents the value of the podophyllotoxin action potential energy coefficient for the i-th calculation of the microbial community, β i represents the value of the podophyllotoxin extraction hindrance coefficient for the i-th calculation of the cell structure, γ i represents the value of the podophyllotoxin extraction regulation coefficient for the i-th calculation of the extracellular environment, represents the value of the physical extraction synergy efficiency coefficient for the i-th calculation, l i represents the value of the chemical extraction environment balance coefficient for the i-th calculation, χ i represents the value of the extraction product quality optimization coefficient for the i-th calculation, i represents starting from the i-th number, and n represents ending at the n-th number.

[0091] The real-time feedback warning module is used to establish a preset value of the rationality index for the monitoring of podophyllotoxin extraction, judge the value of the rationality index for the monitoring of podophyllotoxin extraction according to the preset value of the rationality index for the monitoring of podophyllotoxin extraction, and send out corresponding signals according to the judgment results.

[0092] In this embodiment, it should be specifically noted that: the preset value of the rationality index for the monitoring of podophyllotoxin extraction is denoted as RM def , when RM def ≤RM, a normal signal is sent out, and this signal indicates that the preset value of the rationality index for the monitoring of podophyllotoxin extraction is less than or equal to the value of the rationality index for the monitoring of podophyllotoxin extraction, indicating that the situation of podophyllotoxin extraction is good; when RM def >RM, a warning signal is sent to relevant technical management personnel, and this signal indicates that the preset value of the rationality index for the monitoring of podophyllotoxin extraction is greater than the value of the rationality index for the monitoring of podophyllotoxin extraction, indicating that the situation of podophyllotoxin extraction is poor and relevant technical management personnel need to make adjustments.

[0093] In the present invention, various types of data in the process of podophyllotoxin extraction are divided into different acquisition batches, significantly improving the accuracy and timeliness of monitoring. By means of intelligent sensors, data such as the scale data of the microbial community of raw material cells, the cell structure characteristic data, the microenvironment data of raw material cells, the physical auxiliary condition data, the chemical environment dynamic data, and the product state monitoring data are collected through multiple channels. This multi-faceted data acquisition mode breaks through the limitations of previous monitoring methods and constructs a more complete and reliable data foundation for subsequent data analysis. Data analysis is used to deeply analyze the collected data, so as to calculate the potential energy coefficient value of podophyllotoxin action on the microbial community, the extraction hindrance coefficient value of podophyllotoxin in the cell structure, the extraction regulation coefficient value of podophyllotoxin in the extracellular environment, the physical extraction synergy efficiency coefficient value, the chemical extraction environment balance coefficient value, and the extraction product quality optimization coefficient value, accurately positioning the links that may have problems. Through comprehensive evaluation and deep integration of the data processing results, the reliability and accuracy of the monitoring results are greatly improved. Through continuous monitoring and uninterrupted tracking, once abnormal fluctuations are found, alarm signals are immediately sent out, and relevant technical personnel and operators can timely master the real-time situation and potential hidden dangers of podophyllotoxin extraction, and quickly adjust and optimize the extraction process or operation flow, providing strong guarantee for achieving efficient and accurate podophyllotoxin extraction and scientific and reasonable production decisions.

[0094] Secondly: In the attached drawings of the disclosed embodiments of the present invention, only the structures related to the disclosed embodiments of the present disclosure are involved, and other structures can refer to the general design. Without conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0095] Finally, the above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A real-time monitoring system for podophyllotoxin extraction based on intelligent sensors, characterized in that: include: Data batch division module: used to determine the data to be collected as target data, divide the target data into different batches according to equal time division, and mark them as 1, 2, ..., n in sequence; Data acquisition module: including raw material data acquisition unit and feedback data acquisition unit, used to collect target data in real time and transmit the collected data to the data analysis module; The raw material data collection unit is used to collect raw material cell microbial community scale data, cell structure characteristic data and raw material cell microenvironment data; The feedback data acquisition unit is used to collect physical auxiliary condition data, chemical environment dynamic data and product status monitoring data; Data analysis module: including a raw material data analysis unit and a feedback data analysis unit, used to analyze the data transmitted by the data acquisition module and transmit the analysis results to the data comprehensive evaluation module; the raw material data analysis unit includes a raw material cell microbial community scale data analysis node, a cell structure feature data analysis node and a raw material cell microenvironment data analysis node; the feedback data analysis unit includes a physical auxiliary condition data analysis node, a chemical environment dynamic data analysis node and a product status monitoring data analysis node; Data comprehensive evaluation module: including an intelligent sensor podophyllotoxin extraction real-time monitoring data analysis unit, which is used to comprehensively analyze the data transmitted by the data analysis module and transmit the analysis results to the real-time feedback warning module; The smart sensor podophyllotoxin extraction real-time monitoring data analysis unit is used to establish a smart sensor podophyllotoxin extraction real-time monitoring data calculation model, and the microbial community podophyllotoxin action potential coefficient value, cell structure podophyllotoxin extraction barrier coefficient value, extracellular environment podophyllotoxin extraction regulation coefficient value, physical extraction synergistic efficiency coefficient value, chemical extraction environmental balance coefficient value and extraction product quality optimization coefficient value transmitted by the data analysis module are introduced into the smart sensor podophyllotoxin extraction real-time monitoring data calculation model to obtain the podophyllotoxin extraction monitoring rationality index value; the smart sensor podophyllotoxin extraction real-time monitoring data calculation model is specifically expressed as: ， Among them, RM represents the calculated rationality index value of podophyllotoxin extraction monitoring, , , , , , , α i represents the potential energy coefficient of podophyllotoxin in the microbial community calculated for the i-th time, β i represents the cell structure podophyllotoxin extraction barrier value calculated for the i-th time, γ i represents the value of the podophyllotoxin extraction regulation coefficient of the extracellular environment calculated for the i-th time, ∂ i represents the value of the physical extraction synergistic efficiency coefficient calculated for the i-th time, ℓ i represents the value of the chemical extraction environmental balance coefficient calculated for the i-th time, χ i represents the optimization coefficient value of the extracted product quality calculated for the i-th time, i represents starting from the i-th number, and n represents ending at the n-th number; Real-time feedback warning module: used to establish a preset value of the podophyllotoxin extraction monitoring rationality index, judge the podophyllotoxin extraction monitoring rationality index value according to the preset value of the podophyllotoxin extraction monitoring rationality index, and send a corresponding signal according to the judgment result.

2. The real-time monitoring system for podophyllotoxin extraction based on intelligent sensors according to claim 1, characterized in that: The raw material cell microbial community scale data includes the number of cell microorganism individuals Ms, the total volume of cell microorganism cells Mv and the concentration of cell microbial metabolites Mc; the raw material cell structural characteristic data includes the surface area of ​​the cell intracellular membrane system Is and the number of cell vacuoles Vn; the raw material cell microenvironment data includes the mass of cell polysaccharide secretion Ps, the length of cell protein fibers Pl and the concentration of cell small molecule signal substances Pe.

3. The real-time monitoring system for podophyllotoxin extraction based on intelligent sensors according to claim 1, characterized in that: The physical auxiliary condition data include the average diameter of ultrasonic cavitation bubbles Ud, the microwave penetration depth Md and the stirring shear force Sf; the chemical environment dynamic data include the consumption amount of active groups of the extractant Ag, the absolute value of the pH change of the extract Ph and the residual mass of the buffer substance of the extract Bs; the product status monitoring data include the average particle size Cg of podophyllotoxin crystal particles, the turbidity Pt of podophyllotoxin solution and the hydration radius Hr of podophyllotoxin molecules.

4. The real-time monitoring system for podophyllotoxin extraction based on intelligent sensors according to claim 1, characterized in that: The raw material cell microbial community scale data analysis node is used to establish a raw material cell microbial community scale data calculation model, and the raw material cell microbial community scale data transmitted by the data acquisition module is imported into the raw material cell microbial community scale data calculation model to obtain the microbial community podophyllotoxin action potential energy coefficient value. The raw material cell microbial community scale data calculation model is specifically expressed as: ， Among them, α i represents the potential energy coefficient of podophyllotoxin in the microbial community calculated for the i-th time, Ms i Mv represents the number of individual microorganisms collected for the i-th time. i represents the total volume of microbial cells collected for the i-th time, Mc i Represents the concentration of cell microbial metabolites collected for the i-th time.

5. The real-time monitoring system for podophyllotoxin extraction based on intelligent sensors according to claim 1, characterized in that: The cell structure characteristic data analysis node is used to establish a cell structure characteristic data calculation model, import the cell structure characteristic data transmitted by the data acquisition module into the cell structure characteristic data calculation model, and obtain the cell structure podophyllotoxin extraction barrier coefficient value. The cell structure characteristic data calculation model is specifically expressed as: ， Among them, β i Is represents the cell structure podophyllotoxin extraction barrier coefficient value calculated for the i-th time, i represents the intracellular membrane system surface area collected for the i-th time, σ represents the standard deviation of the intracellular membrane system surface area collected, μ represents the mean of the intracellular membrane system surface area collected, and Vn i Represents the number of cell vacuoles collected for the i-th time.

6. The real-time monitoring system for podophyllotoxin extraction based on intelligent sensors according to claim 1, characterized in that: The raw material cell microenvironment data analysis node is used to establish a raw material cell microenvironment data calculation model, import the raw material cell microenvironment data transmitted by the data acquisition module into the raw material cell microenvironment data calculation model, and obtain the extracellular environment podophyllotoxin extraction control coefficient value. The raw material cell microenvironment data calculation model is specifically expressed as: ， Among them, γ i Ps represents the value of the podophyllotoxin extraction regulation coefficient calculated for the i-th time in the extracellular environment. i represents the mass of cell polysaccharide secretion collected for the i-th time, Pl i represents the length of the cell protein fiber collected for the i-th time, Pe i represents the concentration of small molecule signal substances collected for the i-th time, Pe def Represents the initial concentration of cellular small molecule signaling substances.

7. The real-time monitoring system for podophyllotoxin extraction based on intelligent sensors according to claim 1, characterized in that: The physical auxiliary condition data analysis node is used to establish a physical auxiliary condition data calculation model, import the physical auxiliary condition data transmitted by the data acquisition module into the physical auxiliary condition data calculation model, and obtain the physical extraction synergy efficiency coefficient value. The physical auxiliary condition data calculation model is specifically expressed as: ， Among them, ∂ i Indicates the value of the physical extraction synergistic efficiency coefficient calculated for the i-th time, Ud i Md represents the average diameter of ultrasonic cavitation bubbles collected for the i-th time. i represents the microwave penetration depth collected for the i-th time, Sf i Indicates the magnitude of the stirring shear force collected for the i-th time.

8. The real-time monitoring system for podophyllotoxin extraction based on intelligent sensors according to claim 1, characterized in that: The chemical environment dynamic data analysis node is used to establish a chemical environment dynamic data calculation model, import the chemical environment dynamic data transmitted by the data acquisition module into the chemical environment dynamic data calculation model, and obtain the chemical extraction environment balance coefficient value. The chemical environment dynamic data calculation model is specifically expressed as: ， Among them, ℓ i represents the value of the chemical extraction environmental balance coefficient calculated for the i-th time, Ag i represents the amount of active groups consumed in the extractant collected for the i-th time, Ag def represents the initial number of active groups in the extractant, Ph i Indicates the absolute value of the pH change of the extract collected for the i-th time, Bs i Indicates the remaining mass of the buffer substance in the extract collected for the i-th time, Bs def Indicates the initial concentration of the buffer substance in the extraction solution.

9. The real-time monitoring system for podophyllotoxin extraction based on intelligent sensors according to claim 1, characterized in that: The product state monitoring data analysis node is used to establish a product state monitoring data calculation model, import the product state monitoring data transmitted by the data acquisition module into the product state monitoring data calculation model, and obtain the extracted product quality optimization coefficient value. The product state monitoring data calculation model is specifically expressed as: ， Among them, χ i represents the optimization coefficient value of the extracted product quality calculated for the i-th time, Cg i represents the average particle size of the podophyllotoxin crystal particles collected for the i-th time, Pt i represents the turbidity of the podophyllotoxin solution collected for the i-th time, Hr i represents the hydration radius of the podophyllotoxin molecule collected for the i-th time.

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