Podophyllotoxin extraction real-time monitoring system based on intelligent sensor

Abstract

The invention discloses a podophyllotoxin extraction real-time monitoring system based on an intelligent sensor, and particularly relates to the field of podophyllotoxin extraction, and the podophyllotoxin extraction real-time monitoring system comprises a data batch division module, a data acquisition module, a data analysis module, a data comprehensive evaluation module and a real-time feedback early warning module. The data acquisition module comprises a raw material data acquisition unit and a feedback data acquisition unit and is used for acquiring target data in real time and transmitting the acquired data to the data analysis module; the data analysis module comprises a raw material data analysis unit and a feedback data analysis unit and is used for analyzing the data transmitted by the data acquisition module; the data comprehensive evaluation module comprises an intelligent sensor podophyllotoxin extraction real-time monitoring data analysis unit and is used for comprehensively analyzing the data transmitted by the data analysis module; according to the method, various data in the podophyllotoxin extraction process are divided into different acquisition batches, so that the monitoring accuracy and timeliness are remarkably improved.

Description

Technical Field

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

[0002] Podophyllotoxin is an important medicinal ingredient and is of key significance in the pharmaceutical field. The traditional podophyllotoxin extraction process faces many challenges, and it is often difficult to achieve ideal control of extraction efficiency and quality. With the rapid advancement of sensor technology and intelligent control technology, new opportunities and changes have been created for the real-time monitoring system of podophyllotoxin extraction. With the organic integration of intelligent sensors and intelligent control, key information can be accurately captured in 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] The existing podophyllotoxin extraction monitoring system usually includes 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, and environmental parameters of the extract solution and the reaction vessel; the collected data is transmitted to the data processing center through the data transmission line. The data processing center organizes, analyzes, and performs in-depth calculations on the data obtained from each monitoring point, and then generates guiding results, which are intuitively displayed through the monitoring feedback module, so as to timely detect abnormal fluctuations in 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 collected data dimension relatively narrow, destroys the comprehensiveness of the data system, causes deviations in data processing results, and weakens the accuracy of the results, which is not conducive to the efficient implementation and sustainable development of podophyllotoxin extraction monitoring.

[0005] Therefore, a real-time monitoring system for podophyllotoxin extraction based on intelligent sensors is urgently needed to resolve 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, the embodiments of the present invention provide a real-time monitoring system for podophyllotoxin extraction based on an intelligent sensor, and solve the problems raised in the above-mentioned background technology through the following scheme.

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

[0008] 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;

[0009] Data acquisition module: including 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 status monitoring data;

[0010] 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;

[0011] 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;

[0012] 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.

[0013] Preferably, the raw material cell microbial community scale data include 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 include the surface area of ​​the cell membrane system Is and the number of cell vacuoles Vn; the raw material cell microenvironment data include the mass of cell polysaccharide secretion Ps, the length of cell protein fibers Pl and the concentration of cell small molecule signal substances Pe.

[0014] Preferably, 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 amount of active group consumption Ag of the extractant, the absolute value of the pH change of the extract Ph and the residual mass of the buffer substance in 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.

[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, 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, and 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 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.

[0018] Preferably, the cell structure characteristic data analysis node is used to establish a cell structure characteristic data calculation model, and the cell structure characteristic data transmitted by the data acquisition module is imported into the cell structure characteristic data calculation model to obtain the cell structure podophyllotoxin extraction barrier coefficient value, and the cell structure characteristic data calculation model is specifically expressed as:

[0019] ,

[0020] 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.

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

[0022] ,

[0023] 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 irepresents 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.

[0024] Preferably, 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:

[0025] ,

[0026] 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.

[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] Among them, ℓ i represents the chemical extraction environmental balance coefficient value 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.

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

[0031] ,

[0032] 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.

[0033] Preferably, 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 imported 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:

[0034] ,

[0035] 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 It 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.

[0036] Technical effects and advantages of the present invention:

[0037] 1. The present invention significantly improves the accuracy and timeliness of monitoring by dividing various types of data in the podophyllotoxin extraction process into different collection batches. With the help of intelligent sensors, data on the scale of raw cell microbial communities, cell structure characteristics, raw cell microenvironment, physical auxiliary conditions, chemical environment dynamics, and product status monitoring data are collected through multiple channels. This multi-faceted data collection mode breaks through the limitations of previous monitoring methods and builds a more complete and reliable data foundation for subsequent data analysis;

[0038] 2. Use data analysis to conduct in-depth analysis of the collected data, so as to calculate the potential energy coefficient of podophyllotoxin in the microbial community, the barrier coefficient of podophyllotoxin extraction in the cell structure, the regulation coefficient of podophyllotoxin extraction in the extracellular environment, the synergistic efficiency coefficient of physical extraction, the environmental balance coefficient of chemical extraction, and the optimization coefficient of extraction product quality, 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;

[0039] 3. Through continuous monitoring and uninterrupted tracking, once abnormal fluctuations are found, an alarm signal will be issued immediately. 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 operating procedures, so as to achieve efficient and accurate podophyllotoxin extraction and scientific and reasonable production decisions. Provide strong guarantees. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a schematic diagram of the overall structure of the present invention. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] As attached Figure 1 The real-time monitoring system for podophyllotoxin extraction based on intelligent sensors shown in the figure includes a system operation database, a system central processor and a user information terminal, as well as 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.

[0043] 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 control the information text instructions output by each module, and the user information terminal is an information output device for receiving the real-time monitoring system for podophyllotoxin extraction based on intelligent sensors.

[0044] 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 mark them as 1, 2, ..., n in sequence.

[0045] In this embodiment, it is specifically necessary to explain that: the method of dividing by equal time is to divide the database according to the characteristics of each target data through the background system running the database. According to the real-time requirements of each target data, it is collected once at an equal interval and divided into different collection times.

[0046] 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 raw material data acquisition 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.

[0047] In this embodiment, it is specifically necessary to explain 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 microorganism metabolites Mc; the raw material cell structural characteristic data includes the surface area of ​​the cell 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; the physical auxiliary condition data includes the average diameter of ultrasonic cavitation bubbles Ud, the microwave penetration depth Md and the stirring shear force Sf; the chemical environment dynamic data includes the amount of active group consumption of the extractant Ag, the absolute value of the pH change of the extract Ph and the residual mass of the extract buffer substance Bs; the product status monitoring data includes the average particle size Cg of podophyllotoxin crystal particles, the turbidity Pt of podophyllotoxin solution and the hydration radius Hr of podophyllotoxin molecules.

[0048] The number of individual microorganisms in the cell directly affects the intensity of its group metabolic activity. More individual microorganisms may consume more intracellular resources, change the composition of intracellular substances and the microenvironment, and thus affect the synthesis, storage and stability of podophyllotoxin. For example, some microorganisms may participate in the metabolism of precursor substances of podophyllotoxin, and changes in their number will change the flux of the podophyllotoxin synthesis pathway; or the accumulation of metabolic waste produced by microbial metabolism may cause fluctuations in intracellular pH, threatening the stability of the chemical structure of podophyllotoxin. The collection method is as follows: first, the raw plant tissue from which podophyllotoxin is extracted is finely dissected to obtain fresh and representative cell samples. Then, a special cell lysis solution is used to gently break the cells and release the microorganisms therein. The lysis solution containing microorganisms is gradiently diluted so that a single dispersed microbial colony can be obtained in the subsequent culture process. The diluted lysis solution is evenly spread on a specially designed solid culture medium plate suitable for the growth of such microorganisms, and cultured for a period of time under a suitable temperature, humidity and gas environment. After the culture is completed, the microbial colonies grown on the plate are counted with the help of a colony counter, and the number of microbial individuals in the original cell is calculated based on the dilution multiple.

[0049] The total volume of the cell microbial cell reflects the size of the physical space it occupies in the cell. A larger total volume means that the storage space of podophyllotoxin may be squeezed, or a physical barrier may be formed in the cell to hinder the transport and diffusion path of podophyllotoxin. In addition, the microbial cell volume is large, and its cell membrane surface area is relatively large, which may cause non-specific adsorption or specific binding with podophyllotoxin, reducing the amount of podophyllotoxin that can be extracted. The collection method is: collect fresh raw plant tissue, prepare cell slices using frozen sectioning technology, and the slice thickness must be accurately controlled at the micron level to ensure that the internal structure of the cell can be clearly observed. Place the slice under an electron microscope, adjust the appropriate magnification, and image the microorganisms in the cell. With the help of image analysis software, outline the outline of each microbial cell, and the software automatically calculates the two-dimensional area of ​​the microbial cell according to the outline, and then combines the slice thickness to obtain the volume of a single microbial cell through the volume calculation formula, and finally add up all the microbial cell volumes to obtain the total volume of the microbial cell in the cell.

[0050] 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 then change its solubility and stability; enzymes may catalyze the structural modification or degradation reaction of podophyllotoxin, reducing its activity and extraction efficiency. The collection method is: after obtaining the raw plant cell sample, use a mild physical crushing method to crush the cells to release the microbial metabolites therein. Centrifugation technology is used to separate the cell fragments and the supernatant, and the supernatant is the crude extract containing microbial metabolites. The crude extract is analyzed using high performance liquid chromatography technology. First, select a suitable chromatographic column, set the mobile phase composition and flow rate, and after injection, compare and calculate the concentration of organic acid metabolites in the sample based on the retention time and peak area of ​​the organic acid standard.

[0051] The surface area of ​​the cell endomembrane system affects the reaction sites and reaction areas of podophyllotoxin synthesis and modification, but on the other hand, during the extraction process, podophyllotoxin may be closely combined with the endomembrane system or be wrapped therein, which increases the difficulty and complexity of extraction, and requires stronger extraction conditions to dissociate it from the endomembrane system. The collection method is: take fresh raw plant tissue and fix it with a fixative such as glutaraldehyde to maintain the integrity of the cell structure. The fixed tissue is dehydrated with gradient alcohol and then embedded with embedding agents such as epoxy resin. Use an ultrathin slicer to cut the embedded tissue into ultrathin slices. The slices are placed under a transmission electron microscope for observation. Under high magnification, the endomembrane system presents a clear membranous structure. With the help of image analysis software, the contours of each membrane structure of the endomembrane system are outlined, and the software automatically calculates the surface area of ​​each membrane structure, and finally the surface area of ​​the cell endomembrane system is accumulated.

[0052] The number of cell vacuoles affects the distribution of podophyllotoxin and the difficulty of podophyllotoxin being released from the vacuole. At the same time, the membrane structure and composition of the vacuole may also interact with podophyllotoxin, affecting its extraction efficiency and stability. The collection method is: the raw plant tissue is made into temporary slices, which can be sliced ​​by hand or paraffin. For freehand slicing, fresh tissue is cut into thin slices and placed directly on a glass slide; paraffin slicing requires a series of steps such as fixation, dehydration, transparency, wax immersion, embedding, and slicing. After the slices are made, the slices are stained with a specific vacuolar stain to make the vacuole appear in a distinct color. The stained slices are observed under an optical microscope, and the number of cell vacuoles is counted with the help of image analysis software.

[0053] The quality of the cell polysaccharide secretion 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, wrap podophyllotoxin therein, making it difficult to extract, or be extracted together with podophyllotoxin during the extraction process, increasing the difficulty of subsequent separation and purification. The collection method is: collect the culture fluid or extracellular fluid containing raw plant cells, use ultrafiltration centrifugation technology, select an ultrafiltration membrane with a suitable molecular weight cutoff, and separate the macromolecular polysaccharide from the small molecule substance. Collect the polysaccharide concentrate after ultrafiltration, and use freeze-drying technology to dry the polysaccharide into a solid powder. Use a precision balance to weigh a certain amount of dry polysaccharide powder, and then combine the statistical results of the number of cells in the culture fluid or extracellular fluid to calculate the quality of the cell polysaccharide secretion.

[0054] The length of the cell protein fiber affects the density of the network. Longer protein fibers will make the network denser, hinder the diffusion and penetration of the extractant outside the cell, and limit the speed and amount of the extractant reaching the cell surface; and the protein fibers may bind specifically or nonspecifically to podophyllotoxin, affecting the release and extraction of podophyllotoxin. The collection method is: extracting extracellular protein fibers from raw plant tissues, which can be extracted using a mild protein extraction buffer. After appropriate dilution, the extracted protein fiber solution is dripped on a specially treated glass slide to evenly disperse the protein fibers. The protein fibers on the glass slide are scanned using an atomic force microscope. When the probe of the atomic force microscope scans the sample surface, 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, the length of the protein fibers is measured in a three-dimensional image, and the length of multiple protein fibers is measured and the average value is taken as the length of the extracellular protein fibers.

[0055] The concentration of the cell small molecule signal substance is involved in regulating the physiological activities of the cell, including the synthesis and transport of podophyllotoxin. Changes in the concentration of certain signal substances may induce or inhibit the expression of genes related to podophyllotoxin synthesis, thereby changing the content of podophyllotoxin in the cell; or affect the activity of the intracellular transport system, so that the distribution and transport direction of podophyllotoxin in the cell change, indirectly affecting its extraction efficiency. The collection method is: collect the extracellular fluid around the raw material plant cells, and use solid phase extraction technology to enrich and purify the small molecule signal substances in the extracellular fluid. The enriched sample is derivatized to improve its response signal in the detection instrument. Then ultra-high performance liquid chromatography-tandem mass spectrometry is used for analysis. First, a suitable chromatographic column and mobile phase are selected, and then qualitative and quantitative analysis is performed according to the characteristic ion pairs of the signal molecules and their fragmentation rules in the mass spectrometry to determine their concentration in the extracellular fluid.

[0056] The average diameter of the ultrasonic cavitation bubbles affects the plant cell structure and the release of podophyllotoxin. The appropriate average diameter of the bubbles can produce 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 when it ruptures is too concentrated and strong, which may destroy the chemical bonds in the podophyllotoxin molecules and reduce its activity; if the bubble diameter is too small, the impact force generated is insufficient, and the cell structure cannot be fully destroyed, affecting the release efficiency of podophyllotoxin. The collection method is: in the ultrasonic extraction device, an extract containing podophyllotoxin raw materials is added, and a small amount of tiny tracer particles are evenly mixed in the extract. These tracer particles will move with the movement of the liquid in the ultrasonic field, and their movement trajectory is affected by the ultrasonic cavitation bubbles. During the ultrasonic extraction process, a high-speed camera is used to shoot a specific area in the extract, and a special lighting technology is used during shooting to clearly capture the images of the tracer particles and cavitation bubbles. After shooting, the video images were analyzed frame by frame using image analysis software to identify the outline of the cavitation bubbles, calculate the diameter of each bubble, and then count the diameters of multiple bubbles and take the average value to obtain the average diameter of the ultrasonic cavitation bubbles.

[0057] The microwave penetration depth determines the distribution of microwave energy inside the raw material. When the penetration depth is sufficient, microwaves can evenly heat the inside of the raw material, so that podophyllotoxin can be dissolved from the cells into the extract more quickly at a suitable temperature; if the penetration depth is insufficient, a temperature gradient will appear inside the raw material. The temperature of the part close to the microwave source is too high, which may cause podophyllotoxin degradation, while the temperature of the part far from the microwave source is too low, resulting in low extraction efficiency, affecting the uniformity and efficiency of podophyllotoxin extraction. The collection method is as follows: a container containing podophyllotoxin raw materials is placed in a microwave extraction device, and a high-precision microwave field intensity sensor is inserted at different depths in the container. Turn on the microwave source, run it for a period of time at the set microwave power and frequency, and the sensor monitors the microwave field intensity at each depth in real time. According to the attenuation law of microwave propagation in the medium, the microwave penetration depth is calculated by comparing the field intensity data at different depths.

[0058] The magnitude of the stirring shear force affects the dispersion degree of the raw material particles in the extract and the contact area of ​​the raw material extractant. At the same time, the shear force helps to destroy cell aggregates, making the cells more susceptible to penetration and action by the extractant, and promoting the dissolution of podophyllotoxin. However, when the stirring shear force is too large, mechanical shear damage may be caused to the podophyllotoxin molecules, reducing their activity and purity. The collection method is: a micro force sensor is installed on the stirring blade of the stirring extraction device, and the sensor is connected to the data acquisition system. During the extraction process, as the stirring paddle rotates, the force sensor measures the resistance of the stirring paddle in real time, and the resistance is the stirring shear force. The data acquisition system records the shear force data under different stirring speeds, and takes the average value after multiple measurements as the stirring shear force size under specific extraction conditions.

[0059] The amount of active group consumption of the extractant reflects the degree of reaction between the extractant and podophyllotoxin and other components in the raw material. As the extraction process proceeds, the active groups continue to combine with podophyllotoxin or participate in other chemical reactions, the number of active groups decreases, and the extraction capacity of the extractant gradually decreases; when the active groups are consumed too much, the extractant may not be able to continue to effectively extract podophyllotoxin, and the extractant needs to be supplemented or replaced to ensure the continuation of the extraction process and the extraction efficiency. The collection method is: before the start of the extraction process, accurately determine the initial content of the active group in the extractant. For extractants containing hydroxyl groups, chemical titration can be used, such as reacting with an acylating agent, and the content of hydroxyl groups is calculated by titrating the remaining acylating agent; 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 extract is taken out at intervals, and the remaining amount of active groups in the extractant is determined by the same method as the initial content determination, and the amount of active group consumption is calculated by the difference between the initial amount and the remaining amount.

[0060] The absolute value of the change in pH value of the extract has an important influence on the chemical stability and ionization state of podophyllotoxin. Different podophyllotoxin molecules have different solubility and activity at different pH values. Excessive changes in pH value may cause acid-base catalytic reactions in podophyllotoxin molecules, such as hydrolysis, isomerization, etc., which will change the structure of podophyllotoxin and reduce or lose its activity; in addition, changes in pH value 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, affecting the extraction efficiency and product quality. The collection method is: a high-precision pH electrode is installed in the extraction container, and the electrode is connected to a pH meter, and the pH meter can display the pH value of the extract in real time. Before the extraction process begins, the initial pH value is recorded. As the extraction proceeds, 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 pH value of the extract.

[0061] The residual mass of the buffer substance in the extract affects the stability of the pH of the extract. A sufficient residual amount of 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 a suitable range for podophyllotoxin extraction, and ensure the stability and repeatability of the extraction process; when the residual amount of buffer substance is insufficient, the pH value of the extract is prone to fluctuations, which may exceed the pH interval in which podophyllotoxin exists stably, resulting in degradation of podophyllotoxin or decreased extraction efficiency. The collection method is: before extraction, accurately weigh and record the mass of the buffer substance added to the extract. During the extraction process, a certain amount of extract is taken out regularly, and the content of the buffer substance is determined by chemical analysis. For example, for phosphate buffer, the residual amount of buffer substance can be determined by measuring the phosphate ion concentration in the solution. The specific method can be ion chromatography, the extract is injected into an ion chromatograph, the phosphate ions are separated by an ion exchange column, and the concentration is calculated by comparing the response signal of the phosphate ions on the detector with the standard curve, and then the residual mass of the buffer substance is calculated.

[0062] The average particle size of the podophyllotoxin crystal particles has a key influence on the subsequent separation, purification and product quality. A smaller particle size means a larger specific surface area of ​​the crystal, and a higher efficiency of separation from impurities in operations such as filtration and washing, which is conducive to improving product purity; while a larger particle size may cause impurities to be embedded inside the crystal, and during the separation process, it may not be fully separated from the impurities due to reasons such as the fast sedimentation rate of the particles, affecting the product quality. In addition, the particle size will also affect the dissolution rate of podophyllotoxin, thereby affecting its performance in subsequent preparations and other applications. The collection method is: after the extraction is completed, a solution sample containing podophyllotoxin crystals is obtained. The sample is placed in the sample pool of the laser particle size analyzer, and the laser particle size analyzer irradiates the sample by emitting a laser beam, and the crystal particles will scatter the laser. 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 the Mie scattering theory. The particle size distribution data is statistically analyzed to calculate the average particle size of all crystal particles, that is, the average particle size of the podophyllotoxin crystal particles is obtained.

[0063] The turbidity of the podophyllotoxin solution reflects the impurity content in the podophyllotoxin solution and the aggregation of podophyllotoxin itself. Higher turbidity usually indicates that there are more insoluble impurities, colloidal substances or podophyllotoxin molecules in the solution to form larger aggregates. The presence of impurities may interfere with the subsequent purification process of podophyllotoxin and reduce the purity of the product; podophyllotoxin aggregates may affect its activity and stability, and may cause precipitation, deterioration and other problems during storage or further processing. By monitoring the turbidity, the quality state of the solution can be judged in time so as to take corresponding treatment measures, such as further filtration, optimization of crystallization conditions, etc. The collection method is: take an appropriate amount of podophyllotoxin solution and inject it into the measuring cell of the turbidimeter. The turbidimeter transmits a light beam through the solution, detects the scattering and absorption of light by suspended particles in the solution, and converts it into a corresponding turbidity value. Before measurement, the turbidimeter needs to be calibrated with a standard turbidity solution to ensure the accuracy of the measurement. When measuring, bubbles should be avoided in the solution because bubbles will interfere with the propagation of light and affect the measurement results. At the same time, in order to ensure the repeatability of the measurement, multiple measurements are required under the same temperature, stirring state and other conditions, and the average value is taken as the turbidity value of the podophyllotoxin solution.

[0064] The hydration radius of the podophyllotoxin molecule reflects its actual existence state and size in the solution. The size of the hydration radius affects the interaction between podophyllotoxin and other substances and the behavior in the separation and purification process. For example, in the membrane separation process, the hydration radius determines whether the podophyllotoxin molecule can pass through the membrane of a specific pore size; in ion exchange chromatography, the hydration radius affects the binding and elution behavior of the podophyllotoxin molecule with the ion exchange resin. In addition, the hydration radius is also related to the solubility, stability and other properties of podophyllotoxin, which has important guiding significance for optimizing the extraction and purification process. The collection method is: first prepare a solution sample of podophyllotoxin to ensure that the solution concentration is within a suitable measurement range. Using dynamic light scattering technology, a laser beam is irradiated onto the solution sample, and the podophyllotoxin molecules in the solution and the hydration layer around them will cause the scattered light to produce a Doppler frequency shift. By detecting the frequency shift of the scattered light, the diffusion coefficient of the podophyllotoxin molecule is calculated using relevant theories such as the Stokes-Einstein equation. Then, combined with physical parameters such as the viscosity of the solution, the hydration radius of the podophyllotoxin molecule is calculated according to a specific calculation formula.

[0065] 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 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.

[0066] In this embodiment, it should be specifically explained 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, and the raw material cell microbial community scale data calculation model is specifically expressed as:

[0067] ,

[0068] 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.

[0069] In this embodiment, it should be specifically explained that: the cell structure feature data analysis node is used to establish a cell structure feature data calculation model, and the cell structure feature data transmitted by the data acquisition module is imported into the cell structure feature data calculation model to obtain the cell structure podophyllotoxin extraction barrier coefficient value, and the cell structure feature data calculation model is specifically expressed as:

[0070] ,

[0071] 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.

[0072] In this embodiment, it should be specifically explained that: the raw material cell microenvironment data analysis node is used to establish a raw material cell microenvironment data calculation model, and the raw material cell microenvironment data transmitted by the data acquisition module is imported into the raw material cell microenvironment data calculation model to obtain the extracellular environment podophyllotoxin extraction control coefficient value, and the raw material cell microenvironment data calculation model is specifically expressed as:

[0073] ,

[0074] Among them, γ i Ps represents the value of the podophyllotoxin extraction regulation coefficient calculated for the i-th time in the extracellular environment. irepresents 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.

[0075] In this embodiment, it is specifically required to be explained that: the physical auxiliary condition data analysis node is used to establish a physical auxiliary condition data calculation model, and the physical auxiliary condition data transmitted by the data acquisition module is imported into the physical auxiliary condition data calculation model to obtain the physical extraction synergy efficiency coefficient value. The physical auxiliary condition data calculation model is specifically expressed as:

[0076] ,

[0077] 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.

[0078] In this embodiment, it is specifically required to be explained that: the chemical environment dynamic data analysis node is used to establish a chemical environment dynamic data calculation model, and the chemical environment dynamic data transmitted by the data acquisition module is imported into the chemical environment dynamic data calculation model to obtain the chemical extraction environment balance coefficient value. The chemical environment dynamic data calculation model is specifically expressed as:

[0079] ,

[0080] Among them, ℓ i represents the chemical extraction environmental balance coefficient value 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.

[0081] In this embodiment, it is specifically required to be explained that: the product state monitoring data analysis node is used to establish a product state monitoring data calculation model, and the product state monitoring data transmitted by the data acquisition module is imported into the product state monitoring data calculation model to obtain the extracted product quality optimization coefficient value. The product state monitoring data calculation model is specifically expressed as:

[0082] ,

[0083] 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.

[0084] The data comprehensive evaluation module includes 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.

[0085] In this embodiment, it is specifically required to be explained that: the intelligent sensor podophyllotoxin extraction real-time monitoring data analysis unit is used to establish an intelligent 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 imported into the intelligent sensor podophyllotoxin extraction real-time monitoring data calculation model to obtain the podophyllotoxin extraction monitoring rationality index value; the intelligent sensor podophyllotoxin extraction real-time monitoring data calculation model is specifically expressed as:

[0086] ,

[0087] 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 It 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.

[0088] The real-time feedback warning module 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 a corresponding signal according to the judgment result.

[0089] In this embodiment, it should be specifically noted that: the preset value of the podophyllotoxin extraction monitoring rationality index is denoted as RM def , when RM def <=RM, a normal signal is issued, which indicates that the preset value of the rationality index of podophyllotoxin extraction monitoring is less than or equal to the rationality index value of podophyllotoxin extraction monitoring, indicating that the podophyllotoxin extraction is in good condition; when RM def >RM, an early warning signal is issued to the relevant technical management personnel, which indicates that the preset value of the podophyllotoxin extraction monitoring rationality index is greater than the podophyllotoxin extraction monitoring rationality index value, indicating that the podophyllotoxin extraction situation is poor and the relevant technical management personnel need to make adjustments.

[0090] The present invention significantly improves the accuracy and timeliness of monitoring by dividing various types of data in the podophyllotoxin extraction process into different collection batches. With the help of intelligent sensors, raw material cell microbial community scale data, cell structure characteristic data, raw material cell microenvironment data, physical auxiliary condition data, chemical environment dynamic data and product status monitoring data are collected through multiple channels. This multi-faceted data collection mode breaks through the limitations of previous monitoring methods and builds a more complete and reliable data foundation for subsequent data analysis. The collected data is deeply analyzed using data analysis to calculate the microbial community podophyllotoxin action potential energy 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, accurately locating 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. Through continuous monitoring and uninterrupted tracking, once abnormal fluctuations are detected, an alarm signal will be issued immediately. Relevant technical personnel and operators can promptly grasp the real-time situation and potential hidden dangers of podophyllotoxin extraction, and quickly adjust and optimize the extraction process or operating procedures, providing strong guarantees for achieving efficient and accurate podophyllotoxin extraction and scientific and reasonable production decisions.

[0091] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0092] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in 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; 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.

10. The real-time monitoring system for podophyllotoxin extraction based on intelligent sensors according to claim 1, characterized in that: 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 It 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.

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