Plant allelochemical intelligent separation and extraction system and method

Abstract

The application provides a plant allelochemical intelligent separation and extraction system and method, time series data of dissolved oxygen concentration in an extraction liquid is collected through an intelligent dissolved oxygen electrode; when the dissolved oxygen concentration exceeds a threshold value, a controller opens a nitrogen valve and adjusts ultrasonic power, and a full-process anaerobic ultrasonic extraction liquid is obtained; dynamic adsorption saturation of a current column bed to juglone is determined according to a response intensity of an intelligent ultraviolet sensor at 334 nanometers; when the dynamic adsorption saturation of the first-stage column reaches a switching threshold value, the controller switches to a second-stage column and starts elution of the first-stage column, and an eluent rich in juglone is obtained; before the eluent enters a concentration and crystallization kettle, a cumulative rate of a current oxidation risk is determined, and when the cumulative rate reaches a threshold value, the controller adds an antioxidant to the eluent, and high-purity juglone crystals are obtained through concentration and crystallization. By adopting the scheme of the application, juglone oxidation degradation caused by repeated over-standard dissolved oxygen due to cavitation disturbance can be inhibited.

Description

Technical Field

[0001] This application relates to the field of allelopathic component extraction technology, and more specifically, to an intelligent separation and extraction system and method for plant allelopathic components. Background Technology

[0002] Allelochemical extraction refers to the process of separating secondary metabolites or microbial metabolites released by plants into the environment from complex media and converting them into monomeric compounds with definite chemical structures and biological activities through a series of systematic separation and purification techniques such as solvent extraction, chromatography, and spectroscopic identification.

[0003] In the existing intelligent separation and extraction process of juglone from walnut green husk, nitrogen protection is often only provided briefly at the initial stage of extraction. However, it is impossible to monitor dissolved oxygen fluctuations in real time and dynamically adjust the ultrasonic power under continuous ultrasonic cavitation disturbance, resulting in repeated exceedances of dissolved oxygen throughout the extraction process, which in turn leads to a large amount of oxidative degradation of juglone. Therefore, how to suppress the oxidative degradation of juglone caused by repeated exceedances of dissolved oxygen due to cavitation disturbance has become a difficult problem for the industry. Summary of the Invention

[0004] This application provides a smart separation and extraction system and method for plant allelochemicals, which can suppress the oxidative degradation of juglone caused by repeated exceedances of dissolved oxygen due to cavitation disturbances.

[0005] In a first aspect, this application provides a smart extraction method for juglone from walnut husk, which is applied to a plant allelochemical intelligent separation and extraction system for the intelligent extraction of juglone from walnut husk. The method includes the following steps: Time-series data of dissolved oxygen concentration in walnut green peel extract were collected using a smart dissolved oxygen electrode. The dissolved oxygen concentration time series data is input into the controller. When the dissolved oxygen concentration exceeds the threshold, the controller opens the nitrogen valve and increases the ultrasonic power. If the dissolved oxygen continues to rise and the power has been adjusted to the preset maximum value but is still ineffective, a leak is detected and an alarm is triggered, resulting in a fully oxygen-free ultrasonic extract. The fully anaerobic ultrasonic extraction solution was pumped into a series of solid-phase extraction columns, and the dynamic adsorption saturation of juglone in the current column bed was determined based on the response intensity of the intelligent ultraviolet sensor at 334 nm. When the dynamic adsorption saturation of the first-stage column reaches the switching threshold, the controller switches to the second-stage column and starts the elution of the first-stage column. At the same time, based on the cumulative adsorption amount corresponding to the dynamic adsorption saturation and combined with the pre-calibrated elution parameter model, the elution flow rate and elution volume are determined to obtain the eluent enriched with juglone. Before the eluent enters the concentration and crystallization vessel, the current accumulation rate of oxidation risk is determined based on the real-time dissolved oxygen concentration monitored by the intelligent dissolved oxygen electrode and the real-time juglone concentration monitored by the intelligent ultraviolet sensor. When the accumulation rate reaches a threshold, the controller adds an antioxidant to the eluent, and high-purity juglone crystals are obtained through concentration and crystallization.

[0006] In some embodiments, the dissolved oxygen concentration time-series data is input to the controller. When the dissolved oxygen concentration exceeds a threshold, the controller opens the nitrogen valve and increases the ultrasonic power. If the dissolved oxygen continues to rise and the power has been adjusted to the preset maximum value but is still ineffective, a leak is detected and an alarm is triggered. The obtained fully anaerobic ultrasonic extraction solution specifically includes: The controller analyzes the dissolved oxygen concentration time-series data in real time, extracts the current dissolved oxygen concentration value, and calculates the dissolved oxygen change rate. The current dissolved oxygen concentration is compared with a preset threshold. If the threshold is exceeded, the controller opens the nitrogen valve and dynamically increases the ultrasonic power according to the rate of change of dissolved oxygen. If the ultrasonic power has been adjusted to the preset maximum value and the dissolved oxygen concentration continues to rise and the rate of rise exceeds the set rate threshold, then the system is determined to be leaking and an alarm signal is issued. Once the dissolved oxygen concentration drops below the threshold and stabilizes, it is confirmed that the extraction process is in a completely anaerobic state, and the completely anaerobic ultrasonic extract is output.

[0007] In some embodiments, the process of pumping the fully anaerobic ultrasonic extraction solution into a series of solid-phase extraction columns, and determining the dynamic adsorption saturation of juglone on the current column bed based on the response intensity of the intelligent ultraviolet sensor at 334 nm, specifically includes: The absorbance value of the effluent at 334 nm by the intelligent ultraviolet sensor is collected, and the absorbance value is converted into the corresponding real-time effluent concentration of juglone. The static maximum adsorption capacity of the porous chitosan solid-phase extraction column for juglone was obtained, and the theoretical saturated adsorption capacity of the column bed was established based on the static maximum adsorption capacity and the feed concentration. Based on the difference between the real-time effluent concentration and the feed concentration of juglone, the cumulative adsorption amount of juglone by the column bed at the current time is obtained by cumulative integration over time. The dynamic adsorption saturation of juglone in the current column bed is determined by comparing the cumulative adsorption amount with the theoretical saturation adsorption amount.

[0008] In some embodiments, when the dynamic adsorption saturation of the first-stage column reaches the switching threshold, the controller switches to the second-stage column and starts elution of the first-stage column. Simultaneously, based on the cumulative adsorption amount corresponding to the dynamic adsorption saturation and combined with a pre-calibrated elution parameter model, the elution flow rate and elution volume are determined to obtain an eluent enriched with juglone. Specifically, this includes: When the dynamic adsorption saturation of the first-stage column reaches the switching threshold, the controller performs a column switching operation, switches the feed liquid to the second-stage column, and causes the second-stage column to start adsorption. Determine the cumulative adsorption amount of the first-stage column throughout the entire adsorption cycle; Based on the cumulative adsorption amount and the pre-calibrated elution parameter model, the elution flow rate and elution volume of the first-stage column are determined. According to the determined elution flow rate and elution volume, start the elution program of the first-stage column and collect the effluent as the eluent for enriching juglone.

[0009] In some embodiments, determining the current rate of accumulation of oxidation risk based on the real-time dissolved oxygen concentration monitored by the intelligent dissolved oxygen electrode and the real-time juglone concentration monitored by the intelligent ultraviolet sensor before the eluent enters the concentration crystallization vessel specifically includes: The real-time dissolved oxygen concentration is collected using an organic solvent-resistant smart fluorescent dissolved oxygen electrode, and the real-time juglone concentration is collected using an online ultraviolet sensor. Based on a preset oxidation risk model, the real-time dissolved oxygen concentration and real-time juglone concentration are converted into the cumulative rate of current oxidation risk.

[0010] In some embodiments, when the accumulation rate reaches a threshold, the controller adds an antioxidant to the eluent, and the concentration and crystallization to obtain high-purity juglone crystals specifically includes: The current rate of accumulation of oxidation risk is compared with a preset risk threshold. If the accumulation rate reaches the threshold, the controller generates an addition command and determines the addition dose. According to the addition instruction, the addition execution mechanism is started, and the controller adds antioxidant to the eluent. After the residual antioxidant is removed by activated carbon adsorption pretreatment, it is sent to the concentration and crystallization kettle. After pretreatment, the concentration and crystallization process continues to obtain high-purity juglone crystals.

[0011] In some embodiments, 334 nm is a specific characteristic ultraviolet absorption wavelength for juglone concentration, at which juglone exhibits a strong characteristic absorption peak, and matrix impurities in the extract do not significantly interfere.

[0012] Secondly, this application provides a smart separation and extraction system for plant allelochemicals, including a smart extraction unit, wherein the smart extraction unit includes: The data acquisition module is used to collect time-series data on dissolved oxygen concentration in walnut green peel extract via an intelligent dissolved oxygen electrode. The processing module is used to input the dissolved oxygen concentration time-series data into the controller. When the dissolved oxygen concentration exceeds the threshold, the controller opens the nitrogen valve and increases the ultrasonic power. If the dissolved oxygen continues to rise and the power has been adjusted to the preset maximum value but is still ineffective, a leak is detected and an alarm is triggered, thus obtaining a fully oxygen-free ultrasonic extract. The processing module is also used to pump the fully anaerobic ultrasonic extraction liquid into a series solid-phase extraction column, and determine the dynamic adsorption saturation of juglone on the current column bed based on the response intensity of the intelligent ultraviolet sensor at 334 nm. The processing module is also used to switch the controller to the second column and start the first column elution when the dynamic adsorption saturation of the first column reaches the switching threshold. At the same time, based on the cumulative adsorption amount corresponding to the dynamic adsorption saturation and combined with the pre-calibrated elution parameter model, the elution flow rate and elution volume are determined to obtain the eluent enriched with juglone. The execution module is used to determine the current rate of accumulation of oxidation risk based on the real-time dissolved oxygen concentration monitored by the intelligent dissolved oxygen electrode and the real-time juglone concentration monitored by the intelligent ultraviolet sensor before the eluent enters the concentration and crystallization vessel. When the accumulation rate reaches a threshold, the controller adds an antioxidant to the eluent and concentrates and crystallizes to obtain high-purity juglone crystals.

[0013] Thirdly, this application provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described intelligent extraction method for juglone from walnut green skin.

[0014] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described intelligent extraction method for juglone from walnut husk.

[0015] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects: The intelligent separation and extraction system and method for phytoallergenic components provided in this application firstly transforms the adsorption state of juglone on the porous chitosan solid-phase extraction column from the difficult-to-observe column bed loading degree to a quantifiable dynamic adsorption saturation mathematical characterization by using the response intensity of an intelligent ultraviolet sensor at 334 nm. This provides a direct detection tool and accurate data basis for identifying the column bed saturation state from a physical perspective. Subsequently, based on the real-time criterion that the dynamic adsorption saturation reaches the switching threshold, the controller automatically switches to the second-stage column and starts the first-stage column elution. At the same time, the elution flow rate is accurately determined based on the cumulative adsorption amount and the pre-calibrated elution parameter model. By controlling the volume, it enables instantaneous switching and efficient elution of the adsorption-saturated column bed. Coupled with the dynamic decision-making of the cumulative adsorption amount during the adsorption process, it avoids residual loss of juglone or solvent waste caused by fixed-volume elution, thereby efficiently enriching the target component in the extract. This provides a high concentration of juglone precursor for the subsequent crystallization process, indirectly reducing the additional oxidation risk introduced by repeated concentration operations. Furthermore, during the process of the eluent entering the concentration and crystallization vessel, the current oxidation risk is determined based on the real-time dissolved oxygen concentration monitored by the organic solvent-resistant intelligent fluorescent dissolved oxygen electrode and the real-time juglone concentration monitored by the online ultraviolet sensor. The cumulative rate process transforms the dynamic and unpredictable threat of dissolved oxygen intrusion within the pre-concentration system from a vague environmental disturbance into a real-time quantifiable mathematical threshold. By establishing a clear criterion that the cumulative rate reaches the threshold, it provides a precise decision-making basis for identifying the optimal intervention time for antioxidants at the chemical level. Finally, when the cumulative rate reaches the threshold, the controller immediately adds an ethanol-pre-dissolved ascorbate palmitate solution to the eluent before concentration via a premixing pipeline. This process applies the decision instructions based on dynamic oxidation risk assessment to the antioxidant intervention in the pre-concentration system, achieving immediate and precise intervention of antioxidants when the dissolved oxygen threat reaches a critical point. The addition of pretreatment to remove residual antioxidants before concentration and crystallization avoids the impact of exogenous impurities on product purity, thus effectively inhibiting the oxidative degradation of juglone caused by continuous dissolved oxygen intrusion. This results in juglone crystals that are not merely a result of yield pursuit, but rather a high-purity product with a complete structure whose chemical structure remains in a controlled, low-oxidation-risk environment throughout the extraction, enrichment, and crystallization process, strictly adhering to antioxidant protection rules. This effectively avoids the loss of inherent biological activity of juglone due to oxidative degradation. In summary, this method can inhibit the oxidative degradation of juglone caused by repeated exceedances of dissolved oxygen due to cavitation disturbances. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a method for intelligent extraction of juglone from walnut husk according to some embodiments of this application; Figure 2This is a schematic diagram of the process for obtaining a fully anaerobic ultrasonic extract according to some embodiments of this application; Figure 3 This is a schematic flowchart illustrating the process of determining the cumulative adsorption amount according to some embodiments of this application; Figure 4 This is a schematic diagram of the structure of the intelligent extraction unit shown in some embodiments of this application; Figure 5 This is an internal structural diagram of a computer device for implementing a smart extraction method for juglone from walnut husks, according to some embodiments of this application. Detailed Implementation

[0017] To better understand the technical solutions in this embodiment, the technical solutions in this embodiment will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0018] refer to Figure 1 The figure is a flowchart illustrating a method for intelligent extraction of juglone from walnut husk according to some embodiments of this application. The method for intelligent extraction of juglone from walnut husk mainly includes the following steps: In step 101, time-series data of dissolved oxygen concentration in walnut green peel extract are collected using a smart dissolved oxygen electrode.

[0019] In practice, the raw material of green walnut peel is first dried, crushed, and sieved, preferably to a particle size range of 20-60 mesh. An extraction solvent is added at a preset material-to-liquid ratio (e.g., 1:5 to 1:20, g / mL), wherein the extraction solvent is an ethanol-water mixture with an ethanol volume fraction ≤50%. The mixture is placed in a sealed ultrasonic container equipped with a nitrogen inlet, an exhaust valve, a dissolved oxygen electrode port, and an ultrasonic generator. Nitrogen purging is initiated to purge the air from the container, and then the system is sealed. An organic solvent-resistant intelligent fluorescent dissolved oxygen electrode is used to continuously collect the dissolved oxygen concentration signal in the extract at a preset sampling frequency. The analog signal output by the electrode is conditioned and converted from analog to digital to generate a time-series digital signal of dissolved oxygen concentration, which is transmitted to the controller in real time via a data bus. To ensure measurement accuracy, the temperature of the extract is monitored simultaneously by a temperature sensor during the acquisition process. The time-series dissolved oxygen concentration data is cached in the controller and used for subsequent closed-loop control logic operations.

[0020] It should be noted that the organic solvent-resistant intelligent fluorescent dissolved oxygen electrode described in this application refers to a dissolved oxygen measurement sensor that integrates temperature compensation function, can adapt to low-proportion organic phase systems, outputs standardized electrical signals in real time, and has a certain self-diagnostic capability. Its core sensing element is based on the optical principle, and the sensitive membrane is made of organic solvent-resistant modified materials. The optical dissolved oxygen electrode utilizes the red fluorescence generated by a specific fluorescent substance under blue light excitation. Oxygen molecules quench the fluorescence intensity by colliding with the excited-state fluorescent substance, and the change in fluorescence lifetime or intensity is quantitatively related to the oxygen concentration. The dissolved oxygen concentration time series data refers to the set of dissolved oxygen concentration values ​​continuously collected at fixed time intervals and arranged in chronological order. Its physical significance lies in reflecting the dissolved oxygen level and its dynamic change trend in the extract in real time, which is used to judge the extraction process. The basic data source for determining whether the process is conducted in an oxygen-free environment and the sealing status of the diagnostic system; the sealed ultrasonic container refers to an extraction container that is airtight, can withstand a certain positive or negative pressure, and integrates an ultrasonic transducer to achieve energy coupling and transfer. Its structural design must include a nitrogen inlet, an exhaust outlet, and a sensor installation interface to ensure a stable oxygen-free atmosphere after nitrogen purging; the preset sampling frequency is an optimal acquisition rate range that takes into account the dynamic change rate of dissolved oxygen and the computing load of the controller; the organic solvent-resistant intelligent fluorescent dissolved oxygen electrode needs to be calibrated at two points before use, namely, zero-point calibration using a saturated sodium sulfite solution prepared with the corresponding extraction solvent, and full-scale calibration using saturated humid air with the corresponding extraction solvent, to ensure the accuracy and reliability of the measurement data.

[0021] In step 102, the dissolved oxygen concentration time-series data is input into the controller. When the dissolved oxygen concentration exceeds the threshold, the controller opens the nitrogen valve and increases the ultrasonic power. If the dissolved oxygen continues to rise and the power has been adjusted to the preset maximum value but is still ineffective, a leak is detected and an alarm is triggered, resulting in a fully anaerobic ultrasonic extract.

[0022] In some embodiments, reference Figure 2 As shown in the figure, this is a schematic diagram of the process for obtaining a fully anaerobic ultrasonic extract in some embodiments of this application. The dissolved oxygen concentration time-series data is input into the controller. When the dissolved oxygen concentration exceeds the threshold, the controller opens the nitrogen valve and increases the ultrasonic power. If the dissolved oxygen continues to rise and the power has been adjusted to the preset maximum value but is still ineffective, a leak is detected and an alarm is triggered. The fully anaerobic ultrasonic extract can be obtained by the following steps: First, in step 1021, the controller parses the dissolved oxygen concentration time-series data in real time, extracts the current dissolved oxygen concentration value, and calculates the dissolved oxygen change rate. Then, in step 1022, the current dissolved oxygen concentration is compared with a preset threshold. If the threshold is exceeded, the controller opens the nitrogen valve and dynamically increases the ultrasonic power according to the dissolved oxygen change rate. Subsequently, in step 1023, if the ultrasonic power has been adjusted to the preset maximum value and the dissolved oxygen concentration continues to rise and the rate of rise exceeds the set rate threshold, then the system is determined to be leaking and an alarm signal is issued. Finally, in step 1024, once the dissolved oxygen concentration drops below the threshold and stabilizes, it is confirmed that the extraction process is in a completely anaerobic state, and the completely anaerobic ultrasonic extract is output.

[0023] In specific implementation, the controller analyzes the dissolved oxygen concentration time-series data in real time, extracts the current dissolved oxygen concentration value, and calculates the dissolved oxygen change rate. This can be achieved in the following way: the controller reads the latest set of dissolved oxygen concentration time-series data from the internal buffer at fixed time intervals. The dissolved oxygen concentration time-series data originates from the digital signal sequence collected by the organic solvent-resistant intelligent fluorescent dissolved oxygen electrode and corrected for temperature compensation. First, a sliding window averaging filter is applied to the read time-series data, with the window length set according to the sampling frequency, to eliminate high-frequency random noise and obtain a smoothed dissolved oxygen concentration sequence. The smoothed value at the latest moment is extracted from this sequence as the current dissolved oxygen concentration value. Simultaneously... To calculate the dissolved oxygen change rate, the controller selects smoothed concentration data within the most recent time window and uses a least-squares linear regression algorithm to fit the data points within that window. The slope of the fitted line is taken as the dissolved oxygen change rate at the current moment. The selection of the window length needs to take into account both the response sensitivity to rate changes and the calculation stability, and is usually calibrated experimentally based on the sampling frequency and the dynamic characteristics of the system. As a preferred embodiment, the ratio of the concentration difference between adjacent sampling points to the time interval can also be calculated using the first-order backward difference method as the instantaneous rate, and then the instantaneous rate sequence is filtered and smoothed to obtain a stable change rate. This application does not limit the specific algorithm for rate calculation.

[0024] It should be noted that the dissolved oxygen change rate mentioned in this application refers to a dynamic index used to characterize the rate of change of dissolved oxygen concentration in the extract over time, and is used to quantify the instantaneous fluctuation trend of dissolved oxygen level.

[0025] In specific implementation, the current dissolved oxygen concentration is compared with a preset threshold. If the threshold is exceeded, the controller opens the nitrogen valve and dynamically increases the ultrasonic power according to the dissolved oxygen change rate. This can be achieved in the following way: the controller reads the pre-stored dissolved oxygen concentration threshold, which is selected after pre-experimental determination of the degradation rate curves of juglone at different dissolved oxygen concentrations, and is set near the critical concentration before the oxidative degradation rate of juglone begins to increase significantly; when it is determined that the current dissolved oxygen concentration value is greater than the dissolved oxygen concentration threshold, the controller outputs a control signal to the nitrogen valve drive circuit to open the nitrogen valve, allowing nitrogen to enter the sealed ultrasonic chamber to purge dissolved oxygen; simultaneously, the controller, according to the... The current dissolved oxygen change rate is dynamically adjusted by ultrasonic power, specifically using a segmented proportional control strategy: a set of dissolved oxygen change rate intervals and ultrasonic power adjustment amounts are pre-calibrated through experiments. When the dissolved oxygen change rate is in different intervals, the controller generates a power adjustment command according to the correspondence, increasing the current ultrasonic power by the corresponding percentage, but not exceeding the preset maximum power limit. This command is sent to the ultrasonic generator via analog voltage or digital communication to adjust the ultrasonic output intensity in real time. The establishment of the correspondence is based on the correlation experiment between ultrasonic cavitation degassing effect and dissolved oxygen removal rate. The goal is to enhance the cavitation degassing effect and accelerate dissolved oxygen removal by increasing the ultrasonic intensity.

[0026] It should be noted that the controller described in this application refers to a programmable logic control unit, which is used to receive real-time monitoring data from various sensors, run preset control algorithms, and output control signals to various actuators, thereby realizing intelligent closed-loop control of the entire extraction, enrichment, and crystallization process; the ultrasonic power refers to the ultrasonic energy output intensity applied to the sealed ultrasonic tank, which is used to drive the cavitation effect to promote the dissolution of the target component. Its magnitude is dynamically adjusted by the controller according to the dissolved oxygen change rate to balance the needs of extraction efficiency and dissolved oxygen inhibition.

[0027] In practice, if the ultrasonic power has been adjusted to the preset maximum value and the dissolved oxygen concentration continues to rise at a rate exceeding a set threshold, a system leak can be detected and an alarm signal can be issued. This can be achieved in the following way: after opening the nitrogen valve and adjusting the power, the controller continuously acquires the current ultrasonic power value, dissolved oxygen concentration value, and their rate of change at a fixed interval. When it is detected that the ultrasonic power is already at the preset maximum value and cannot be further increased, a leak diagnosis timer is started. In subsequent consecutive time windows, the following condition is checked second by second: the current dissolved oxygen concentration value is always higher than the set threshold. The dissolved oxygen concentration exhibits a monotonically increasing trend, meaning that the concentration value at each sampling moment is greater than the value at the previous moment, or the rate of change of dissolved oxygen calculated by the sliding window is continuously greater than a preset rate threshold. The preset rate threshold is determined through a simulated leak experiment and represents an abnormal rate of increase that cannot be achieved during normal oxygen reduction. Preferably, the continuous time window can be set to 30 seconds. That is, if the above conditions are no longer met at any moment within 30 seconds, the timer is reset and the leak diagnosis is exited. If the conditions are continuously met within 30 seconds, it is determined that a physical leak has occurred in the system, and the controller immediately triggers the audible and visual alarm device.

[0028] In specific implementation, once the dissolved oxygen concentration drops below the threshold and stabilizes, it is confirmed that the extraction process is in a completely anaerobic state. Outputting the completely anaerobic ultrasonic extract can be achieved in the following way: For example, after oxygen reduction control or leak elimination, the controller continuously monitors the comparison between the current dissolved oxygen concentration value and the dissolved oxygen concentration threshold. When the current dissolved oxygen concentration value is detected to be less than or equal to the dissolved oxygen concentration threshold for the first time, a stability determination timer is started. During a subsequent preset stability observation period, the dissolved oxygen concentration is required to remain below the threshold, and the fluctuation range must not exceed a preset fluctuation limit. There is no need to trigger the nitrogen valve to open again or only a very small amount of intermittent nitrogen replenishment is required; if the dissolved oxygen concentration always meets the stable condition during the observation period, it is confirmed that the extraction system has established and maintained an anaerobic environment. At this time, the controller records the status of the current extraction batch as anaerobic throughout the process and marks the extract of this batch as the anaerobic ultrasonic extract. As a preferred embodiment, if the dissolved oxygen concentration exceeds the threshold again during the observation period, the controller re-enters the oxygen reduction control mode. After the standard is met again, the stability determination will start again until the confirmation condition of anaerobic throughout the process is met. This application does not limit the specific implementation of the stability determination logic.

[0029] It should be noted that the anaerobic state described in this application refers to a stable working condition in which the dissolved oxygen concentration in the extract is always controlled below a preset threshold throughout the entire extraction process, ensuring that juglone is not oxidized during extraction. The anaerobic ultrasonic extract refers to the extract obtained by ultrasonic-assisted extraction under the aforementioned anaerobic state, characterized by the maximum preservation of the original chemical form and inherent biological activity of juglone due to the low-oxygen environment throughout the process.

[0030] In step 103, the fully anaerobic ultrasonic extraction solution is pumped into a series of solid-phase extraction columns, and the dynamic adsorption saturation of juglone in the current column bed is determined based on the response intensity of the intelligent ultraviolet sensor at 334 nm.

[0031] In some embodiments, the fully anaerobic ultrasonic extraction solution is pumped into a series of solid-phase extraction columns, and the dynamic adsorption saturation of juglone in the current column bed is determined based on the response intensity of the intelligent ultraviolet sensor at 334 nm. This can be achieved by the following steps: The absorbance value of the effluent at 334 nm by the intelligent ultraviolet sensor is collected, and the absorbance value is converted into the corresponding real-time effluent concentration of juglone. The static maximum adsorption capacity of the porous chitosan solid-phase extraction column for juglone was obtained, and the theoretical saturated adsorption capacity of the column bed was established based on the static maximum adsorption capacity and the feed concentration. Based on the difference between the real-time effluent concentration and the feed concentration of juglone, the cumulative adsorption amount of juglone by the column bed at the current time is obtained by cumulative integration over time. The dynamic adsorption saturation of juglone in the current column bed is determined by comparing the cumulative adsorption amount with the theoretical saturation adsorption amount.

[0032] In specific implementation, the absorbance value of the effluent at 334 nm by the intelligent ultraviolet sensor and the conversion of the absorbance value into the corresponding real-time effluent concentration of juglone can be achieved in the following way: For example, a flow-through quartz cuvette is installed in the outlet flow path of the series-connected porous chitosan solid-phase extraction column. The intelligent ultraviolet sensor is connected to the cuvette via optical fiber and continuously collects the ultraviolet absorbance value of the effluent at a wavelength of 334 nm at a fixed frequency (e.g., 1 Hz). The analog signal output by the intelligent ultraviolet sensor is converted from analog to digital to obtain a digitized absorbance value sequence. The controller pre-stores a standard concentration-absorbance curve of juglone at 334 nm, which is obtained by preparing a series of juglone standards with known concentrations. The absorbance of the standard solution at 334 nm was measured in a cuvette with the same optical path, and then obtained by linear regression fitting, which conforms to the Lambert-Beer law. The controller substitutes the real-time collected absorbance value into the standard concentration-absorbance curve to calculate the corresponding real-time effluent concentration of juglone. The real-time effluent concentration of juglone reflects the content of unadsorbed juglone flowing out from the end of the extraction column at the current moment. As a preferred embodiment, if the complex composition of the extract causes background absorption interference, a dual-wavelength correction method can be used, that is, while measuring the absorbance at 334 nm, the absorbance at a non-characteristic absorption wavelength (such as 450 nm) is measured as background to deduct matrix interference. This application does not limit the specific conversion method of absorbance-concentration.

[0033] It should be noted that the 334 nm mentioned in this application is the characteristic ultraviolet absorption wavelength of juglone concentration, at which juglone has a characteristic absorption peak; the absorbance value of the effluent refers to the ultraviolet light absorption intensity of the liquid flowing through the outlet of the solid phase extraction column measured by the intelligent ultraviolet sensor at 248 nm, which is used to characterize the concentration level of juglone in the liquid; the real-time effluent concentration of juglone refers to the instantaneous content of juglone flowing out from the end of the solid phase extraction column at the current moment, calculated based on the absorbance value of the effluent, which is used to reflect the dynamic adsorption effect of the column bed on juglone.

[0034] In practice, obtaining the static maximum adsorption capacity of the porous chitosan solid-phase extraction column for juglone, and establishing the theoretical saturated adsorption capacity of the column bed based on the static maximum adsorption capacity and feed concentration, can be achieved in the following way: For example, before formal extraction, the static maximum adsorption capacity of the porous chitosan adsorbent material for juglone is determined by an offline static adsorption experiment. Specifically, a unit mass of chitosan adsorbent is weighed, placed in a certain volume of juglone solution, and shaken until saturation. The change in solution concentration before and after adsorption is measured, and the maximum adsorption capacity per unit mass of adsorbent is calculated. The static maximum adsorption capacity is used as... The basic characteristic parameters of the adsorption material are pre-stored in the controller. At the same time, the controller obtains the feed concentration of the current batch of extract. The feed concentration can be measured by an online ultraviolet sensor installed in the feed pipeline, or calculated according to the preset feed-to-solid ratio of the raw material feed amount and the extraction solvent volume in the aforementioned steps. The controller reads the column bed mass (or the product of the column bed volume and the packing density) of the porous chitosan solid phase extraction column currently in use, and multiplies the static maximum adsorption capacity by the column bed mass to obtain the theoretical saturated adsorption total of the column bed. In other embodiments, other methods can also be used to determine this, which are not limited here.

[0035] It should be noted that the static maximum adsorption capacity mentioned in this application refers to the maximum mass of juglone that a unit mass of porous chitosan adsorbent material can adsorb under static equilibrium conditions, and is used to characterize the theoretical adsorption capacity limit of the adsorbent material itself; the theoretical saturated total adsorption refers to the total amount of juglone that the currently used solid phase extraction column bed can theoretically adsorb under a given feed concentration, which is obtained by multiplying the static maximum adsorption capacity by the column bed mass, and is used as the denominator basis when calculating the dynamic adsorption saturation.

[0036] For specific implementation, refer to Figure 3As shown in the figure, this is a schematic flowchart illustrating the determination of cumulative adsorption capacity in some embodiments of this application. Based on the difference between the real-time effluent concentration and the feed concentration of juglone, the cumulative adsorption capacity of the column bed for juglone at the current moment is obtained by performing a cumulative integration calculation over time. This can be achieved in the following manner: For example, the controller continuously acquires the real-time effluent concentration of juglone at a fixed sampling period, and simultaneously acquires the feed concentration at the current moment; for each sampling moment, the difference between the feed concentration and the real-time effluent concentration is calculated, and this difference represents the amount of juglone adsorbed per unit volume of extract flowing through the column bed; the controller uses a numerical integration method... The method involves multiplying the concentration difference at each moment by the instantaneous volumetric flow rate through the column bed and then by the sampling time interval to obtain the adsorption increment within that small time period. All adsorption increments from the start of adsorption to the current moment are then accumulated to obtain the cumulative adsorption amount of juglone on the column bed at the current moment. The instantaneous volumetric flow rate is obtained in real-time by measuring the speed of the feed pump or a flow meter. As a preferred embodiment, when the feed concentration remains constant, the cumulative adsorption amount can be obtained by directly integrating the difference between (feed concentration and real-time effluent concentration) over the cumulative volume flowing through the column bed. This application does not limit the choice of the integration variable.

[0037] It should be noted that the cumulative adsorption amount mentioned in this application refers to the cumulative mass of juglone actually adsorbed by the column bed in the extract flowing through the column bed from the start of adsorption to the current moment. It is obtained by integrating the difference between the feed concentration and the real-time effluent concentration and is used to quantify the amount of adsorption work completed by the column bed.

[0038] In specific implementation, the dynamic adsorption saturation of the current column bed for juglone can be determined by the cumulative adsorption amount and the theoretical saturated adsorption amount in the following way: For example, the controller divides the latest calculated cumulative adsorption amount by the pre-stored theoretical saturated adsorption amount in each calculation cycle to obtain a value between 0 and 1, which is the dynamic adsorption saturation of the column bed at the current moment; when the dynamic adsorption saturation is close to 1, it indicates that the column bed is close to the adsorption saturation state and breakthrough is about to occur; as a preferred embodiment, in order to avoid fluctuations in the saturation calculation value caused by single sampling noise, the saturation calculation results of multiple consecutive cycles can be subjected to moving average filtering to obtain a smoothed dynamic adsorption saturation for subsequent judgment. This application does not limit the filtering method.

[0039] It should be noted that the dynamic adsorption saturation mentioned in this application refers to the ratio of the cumulative adsorption amount of the column bed at the current moment to its theoretical saturation adsorption amount. It is a dimensionless index used to characterize the loading degree of the column bed in real time. Its value is between 0 and 1. The closer it is to 1, the closer the column bed is to saturation.

[0040] In step 104, when the dynamic adsorption saturation of the first-stage column reaches the switching threshold, the controller switches to the second-stage column and starts the elution of the first-stage column. At the same time, based on the cumulative adsorption amount corresponding to the dynamic adsorption saturation and combined with the pre-calibrated elution parameter model, the elution flow rate and elution volume are determined to obtain the eluent enriched with juglone.

[0041] In some embodiments, when the dynamic adsorption saturation of the first-stage column reaches the switching threshold, the controller switches to the second-stage column and starts elution of the first-stage column. Simultaneously, based on the cumulative adsorption amount corresponding to the dynamic adsorption saturation and combined with a pre-calibrated elution parameter model, the elution flow rate and elution volume are determined. Obtaining the eluent enriched with juglone can be achieved through the following steps: When the dynamic adsorption saturation of the first-stage column reaches the switching threshold, the controller performs a column switching operation, switches the feed liquid to the second-stage column, and causes the second-stage column to start adsorption. Determine the cumulative adsorption amount of the first-stage column throughout the entire adsorption cycle; Based on the cumulative adsorption amount and the pre-calibrated elution parameter model, the elution flow rate and elution volume of the first-stage column are determined. According to the determined elution flow rate and elution volume, start the elution program of the first-stage column and collect the effluent as the eluent for enriching juglone.

[0042] In specific implementation, when the dynamic adsorption saturation of the first-stage column reaches the switching threshold, the controller performs a column switching operation, switching the feed liquid to the second-stage column and initiating adsorption in the second-stage column. This can be achieved in the following way: the controller takes the dynamic adsorption saturation of the first-stage column at fixed intervals and compares it with the switching threshold pre-stored in the controller; the switching threshold is selected after pre-experimenting to determine the balance point between column efficiency and breakthrough risk at different saturations. For example, under the premise of ensuring that the second-stage column can seamlessly connect to the adsorption task, the critical saturation value of the first-stage column that is about to break through but has not yet leaked solute is selected; when it is determined that the first-stage column... When the dynamic adsorption saturation is greater than or equal to the switching threshold, the controller outputs a digital control signal to the multi-position switching valve in the feed pipeline, driving the switching valve to close the feed path originally flowing to the first-stage column and simultaneously open the path flowing to the second-stage column, thereby introducing all the anaerobic ultrasonic extract into the second-stage column for adsorption. After the switching is completed, the first-stage column is isolated from the feed path, and its inlet and outlet are switched to be connected to the elution system, and it is in a state of waiting to be eluted. The second-stage column begins to independently undertake the adsorption task of the subsequent extract, and its dynamic adsorption saturation starts to accumulate again from zero. The controller simultaneously begins to monitor and calculate the dynamic adsorption saturation of the second-stage column.

[0043] It should be noted that the first-stage column and the second-stage column in this application refer to two porous chitosan solid-phase extraction columns connected in series. The first-stage column undertakes the front-end adsorption task, and when it is close to saturation, it switches to the second-stage column to take over the adsorption. The two work alternately to achieve continuous enrichment operation.

[0044] In specific implementation, the cumulative adsorption amount of the first-stage column during the entire adsorption cycle can be determined in the following ways, for example: the controller records and stores the final value of the cumulative adsorption amount of the first-stage column from the start of adsorption to the moment when the switching threshold is reached at a fixed sampling period. This value is the total mass of juglone actually adsorbed by the column bed during the adsorption cycle. As a preferred embodiment, the cumulative adsorption amount can also be calculated by the difference between the total mass of the feed and the total mass of the effluent during the adsorption cycle. This application does not limit the final determination method of the cumulative adsorption amount.

[0045] It should be noted that the cumulative adsorption amount mentioned in this application refers to the total mass of juglone actually adsorbed by the first-stage column during the entire adsorption cycle, which is used to directly reflect the total load of the target substance on the column bed.

[0046] In practice, the elution program of the first-stage column is started according to the determined elution flow rate and elution volume. The effluent is collected as the eluent for enriching juglone. This can be achieved in the following ways: the controller pre-stores a pre-calibrated elution parameter model. This model is established through elution recovery experiments at different sample loading amounts, clarifying the correspondence between the cumulative adsorption amount and the optimal elution flow rate and the minimum complete elution volume. The optimal elution flow rate is determined through elution efficiency experiments at different flow rates, ensuring sufficient desorption while taking elution time into account. The minimum complete elution volume is determined by measuring the minimum elution dose required to completely elute juglone at different sample loading amounts, usually expressed as a multiple of the column bed volume. The controller substitutes the current cumulative adsorption amount of the first-stage column into the pre-calibrated elution parameter model to directly calculate the corresponding optimal elution flow rate and minimum complete elution volume. For example, the larger the cumulative adsorption amount, the larger the required elution volume, and the elution flow rate can be appropriately increased within the optimal range to shorten the elution time.

[0047] It should be noted that the elution flow rate and elution volume mentioned in this application refer to the eluent flow rate and total amount set when eluting a saturated column bed, which are used to completely desorb the adsorbed juglone from the column bed. Their values ​​are dynamically determined based on the cumulative adsorption amount and the pre-calibration model to ensure elution recovery rate and solvent utilization rate.

[0048] In practice, the elution program of the first-stage column is started according to the determined elution flow rate and elution volume. The effluent is collected as the eluent for enriching juglone. This can be achieved in the following way: the controller sends a control command to the elution pump connected to the inlet of the first-stage column, setting its output flow rate to the determined elution flow rate; simultaneously, the inlet valve between the eluent storage tank and the first-stage column is opened, allowing the eluent (such as a methanol-water or acetonitrile-water mixture) to flow through the first-stage column at the set flow rate; the controller monitors the flow rate through the column bed in real time via a flow meter or by accumulating the elution pump's operating time. The cumulative elution volume is calculated, and when the cumulative volume reaches the predetermined elution volume, the elution pump and inlet valve are automatically shut off, ending the elution process. Throughout the elution process, the liquid flowing out from the first-stage column outlet is introduced into a dedicated collection container via a pipeline. This liquid is the eluent enriched with a high concentration of juglone. As a preferred embodiment, the real-time absorbance of the elution at 334 nm can be monitored simultaneously using an ultraviolet sensor during the elution process. When the absorbance value rises and then falls to near the baseline level, elution can be terminated early to save solvent. This application does not limit the method for determining the termination of elution.

[0049] It should be noted that the eluent for enriching juglone mentioned in this application refers to the liquid product eluted from the solid-phase extraction column after adsorption has been completed.

[0050] In step 105, before the eluent enters the concentration and crystallization vessel, the current accumulation rate of oxidation risk is determined based on the real-time dissolved oxygen concentration monitored by the intelligent dissolved oxygen electrode and the real-time juglone concentration monitored by the intelligent ultraviolet sensor. When the accumulation rate reaches a threshold, the controller adds an antioxidant to the eluent, and the high-purity juglone crystals are obtained by concentration and crystallization.

[0051] In some embodiments, determining the current rate of accumulation of oxidation risk based on the real-time dissolved oxygen concentration monitored by the intelligent dissolved oxygen electrode and the real-time juglone concentration monitored by the intelligent ultraviolet sensor before the eluent enters the concentration crystallization vessel can be achieved by the following steps: The real-time dissolved oxygen concentration is collected using an organic solvent-resistant smart fluorescent dissolved oxygen electrode, and the real-time juglone concentration is collected using an online ultraviolet sensor. Based on a preset oxidation risk model, the real-time dissolved oxygen concentration and real-time juglone concentration are converted into the cumulative rate of current oxidation risk.

[0052] In practice, the real-time dissolved oxygen concentration value is collected by an organic solvent-resistant intelligent fluorescent dissolved oxygen electrode, and the real-time juglone concentration value is collected by an online ultraviolet sensor. This can be achieved in the following way: for example, the organic solvent-resistant intelligent fluorescent dissolved oxygen electrode and the online ultraviolet sensor are installed in the inlet premixing pipeline of the concentration crystallization vessel. The dissolved oxygen electrode and the ultraviolet sensor continuously collect the dissolved oxygen concentration signal and the ultraviolet absorbance signal at 334 nm in the eluent at a preset sampling frequency. Both signals are converted into digital values ​​by an analog-to-digital converter after temperature compensation correction. The controller reads the digital signal at the same frequency to obtain the real-time dissolved oxygen concentration value and the real-time juglone concentration value.

[0053] It should be noted that the real-time dissolved oxygen concentration value mentioned in this application refers to the instantaneous dissolved oxygen content at the current moment, continuously collected by an organic solvent-resistant intelligent fluorescent dissolved oxygen electrode before concentration; the real-time juglone concentration value refers to the instantaneous juglone content at the current moment, continuously collected by an online ultraviolet sensor before concentration.

[0054] In specific implementation, based on a preset oxidation risk model, the conversion of the real-time dissolved oxygen concentration and real-time juglone concentration into the current cumulative rate of oxidation risk can be achieved in the following way: For example, the preset oxidation risk model needs to be established in advance through experimental calibration. That is, before formal extraction, a series of standard solutions with different dissolved oxygen concentrations and different juglone concentrations are prepared. Each standard solution is placed in a sealed container under the same temperature conditions as the concentration process, and the rate of decrease of juglone concentration per unit time is measured. The juglone concentration can be measured at 334 nm by ultraviolet spectrophotometry. The series of measured dissolved oxygen concentration values, juglone concentration values ​​and their corresponding juglone oxidation rate values ​​are fitted together. Based on the second-order reaction kinetic equation of juglone oxidation degradation, the least squares method is used to fit the data to obtain the cumulative rate of oxidation risk. The oxidation rate function relating the dissolved oxygen concentration and juglone concentration is stored in the controller as an oxidation risk model. During actual operation, the controller substitutes the real-time dissolved oxygen concentration and real-time juglone concentration values ​​collected at the current moment into the function to calculate the cumulative oxidation risk rate corresponding to the current operating conditions. This cumulative rate is used to characterize the amount of juglone that may be oxidized per unit time under the current conditions. As a preferred embodiment, the oxidation risk model can also introduce a temperature correction coefficient. That is, during the above experimental calibration process, the oxidation rate at different temperatures is measured simultaneously to establish a multidimensional model including temperature variables. In actual calculation, the cumulative rate is corrected according to the real-time monitored material temperature. This application does not limit the specific functional form and calibration method of the oxidation risk model.

[0055] It should be noted that the oxidation risk model described in this application refers to a mathematical model established through pre-experiment calibration, which describes the functional relationship between dissolved oxygen concentration, juglone concentration, and juglone oxidation rate based on second-order reaction kinetics. This model is used to convert real-time monitored bivariate parameters into quantifiable oxidation risk indicators. The cumulative rate of oxidation risk refers to the amount of juglone that may be oxidized per unit time under the current operating conditions, calculated according to the oxidation risk model. This is used to quantify the degree of oxidation threat faced by juglone in the system before concentration and serves as the decision basis for triggering the addition of antioxidants.

[0056] In some embodiments, when the accumulation rate reaches a threshold, the controller adds an antioxidant to the eluent, and the concentration and crystallization to obtain high-purity juglone crystals can be achieved through the following steps: The current rate of accumulation of oxidation risk is compared with a preset risk threshold. If the accumulation rate reaches the threshold, the controller generates an addition command and determines the addition dose. According to the addition instruction, the addition execution mechanism is started, and the controller adds antioxidant to the eluent. After the residual antioxidant is removed by activated carbon adsorption pretreatment, it is sent to the concentration and crystallization kettle. After pretreatment, the concentration and crystallization process continues to obtain high-purity juglone crystals.

[0057] In specific implementation, the current cumulative rate of oxidation risk is compared with a preset risk threshold. If the cumulative rate reaches the threshold, the controller generates an addition command and determines the dosage. This can be achieved in the following ways: For example, the risk threshold can be preset through a pre-experiment. This pre-experiment involves conducting a concentration crystallization experiment under different oxidation risk cumulative rate conditions, measuring the yield and purity of the juglone crystals obtained under each condition, and selecting the critical risk value before the yield and purity begin to decrease significantly as the risk threshold. During operation, the controller compares the calculated current cumulative rate of oxidation risk with the risk threshold at fixed intervals. If the cumulative rate reaches the threshold, the controller generates an addition command and determines the dosage. If the cumulative rate is less than the risk threshold, the controller continues monitoring without triggering the addition procedure; if the cumulative rate is greater than or equal to the risk threshold, the controller's internal logic generates an addition instruction; simultaneously, the controller determines the addition dose according to a preset dosage calculation rule based on the degree to which the current cumulative rate exceeds the threshold. The dosage calculation rule can be a proportional relationship or a segmented correspondence, for example, the greater the exceedance of the threshold, the greater the addition dose, but not exceeding the preset maximum addition amount; as a preferred embodiment, the addition dose can also be a fixed dose, that is, the same volume of antioxidant solution is injected each time addition is triggered. This application does not limit the specific method of determining the addition dose.

[0058] In specific implementation, according to the addition command, the addition execution mechanism is activated, and the controller adds antioxidant to the eluent. After the residual antioxidant is removed by activated carbon adsorption pretreatment, it is sent to the concentration crystallization kettle. This can be achieved in the following way: After receiving the addition command, the controller outputs a control signal to the micro-injection pump connected to the ascorbate palmitate storage tank and starts the injection pump to run at a preset flow rate. The ascorbate palmitate is pre-prepared into a homogeneous solution with anhydrous ethanol and stored in the storage tank connected to the micro-injection pump. When the injection pump is running, it is injected into the premixing pipeline at the inlet of the concentration crystallization kettle through the pipeline. The turbulence generated by the flow in the pipeline achieves instantaneous and uniform mixing with the eluent. The mixed material flows through a pretreatment column filled with activated carbon, where the residual ascorbate palmitate and reaction byproducts are removed by activated carbon adsorption. The pretreated material is then sent to the concentration crystallization kettle. The injection pump continues to run until the preset addition dose is reached or a stop command is received.

[0059] It should be noted that the ascorbate palmitate mentioned in this application refers to a fat-soluble vitamin C derivative, which is injected into the premixed pipeline after being pre-dissolved in ethanol to quickly remove dissolved oxygen in the system and inhibit oxidation reaction, thereby protecting the chemical stability of juglone before concentration; the activated carbon pretreatment step is used to completely remove residual antioxidants and avoid exogenous impurities from entering the crystallization system and affecting product purity.

[0060] In specific implementation, after pretreatment, the concentration and crystallization process continues to obtain high-purity juglone crystals. This can be achieved in the following ways: after completing antioxidant intervention and impurity pretreatment, the controller continues to operate according to preset crystallization process parameters. The crystallization process includes stages such as concentration, cooling crystallization, and crystal growth. Specifically, the eluent is concentrated to a supersaturated state by heating or vacuum evaporation, and then juglone crystallizes out by cooling at a controllable rate. The crystals are maintained at the crystallization temperature for a certain period of time to allow the crystals to grow fully. Throughout the crystallization process, the system is always in a low-oxygen environment protected by nitrogen to prevent juglone from undergoing further oxidative degradation. After crystallization, juglone crystals are obtained by filtration or centrifugation and can be vacuum-dried at low temperature as needed. The obtained crystals retain their complete chemical structure to the greatest extent due to multiple antioxidant protections during the entire extraction, enrichment, and concentration process, ultimately yielding high-purity juglone crystals. As a preferred embodiment, the controller continuously monitors the gas phase oxygen concentration in the reactor during the crystallization process. If the oxygen concentration exceeds the standard, nitrogen can be added for purging. This application does not limit the specific parameters of the crystallization process.

[0061] It should be noted that the high-purity juglone crystals mentioned in this application refer to the juglone solid product finally obtained by crystallization under the protection of the aforementioned steps. Its characteristics are that, due to the multiple antioxidant protections during the entire extraction, enrichment and crystallization process, the obtained crystals have no obvious oxidative degradation, high purity, complete chemical structure, and retain the inherent biological activity of juglone.

[0062] Furthermore, in another aspect of this application, in some embodiments, this application provides an intelligent separation and extraction system for phytoallergenic components, including an intelligent extraction unit, as referenced. Figure 4 The figure is a schematic diagram of the structure of an intelligent extraction unit according to some embodiments of this application. The intelligent extraction unit 200 includes: a data acquisition module 201, a processing module 202, and an execution module 203, which are described below: The acquisition module 201 in this application is mainly used to acquire time-series data of dissolved oxygen concentration in walnut green peel extract through intelligent dissolved oxygen electrode; Processing module 202, in this application, is mainly used to input the dissolved oxygen concentration time series data into the controller. When the dissolved oxygen concentration exceeds the threshold, the controller opens the nitrogen valve and increases the ultrasonic power. If the dissolved oxygen continues to rise and the power has been adjusted to the preset maximum value but is still ineffective, a leak is determined and an alarm is triggered, and a fully oxygen-free ultrasonic extract is obtained. In addition, the processing module 202 in this application is also used to pump the fully anaerobic ultrasonic extraction liquid into a series solid phase extraction column, and determine the dynamic adsorption saturation of juglone on the current column bed based on the response intensity of the intelligent ultraviolet sensor at 334 nm. In addition, the processing module 202 in this application is also used to switch the controller to the second column and start the elution of the first column when the dynamic adsorption saturation of the first column reaches the switching threshold. At the same time, based on the cumulative adsorption amount corresponding to the dynamic adsorption saturation and combined with the pre-calibrated elution parameter model, the elution flow rate and elution volume are determined to obtain the eluent enriched with juglone. The execution module 203 in this application is mainly used to determine the current accumulation rate of oxidation risk based on the real-time dissolved oxygen concentration monitored by the intelligent dissolved oxygen electrode and the real-time juglone concentration monitored by the intelligent ultraviolet sensor before the eluent enters the concentration crystallization kettle. When the accumulation rate reaches a threshold, the controller adds an antioxidant to the eluent and concentrates and crystallizes to obtain high-purity juglone crystals.

[0063] In addition, this application also provides a computer device, the computer device including a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the above-described intelligent extraction method for juglone from walnut green skin.

[0064] In some embodiments, reference Figure 5This figure is an internal structural diagram of a computer device for implementing a smart extraction method for juglone from walnut husks according to some embodiments of this application. The smart extraction method for juglone from walnut husks in the above embodiments can be achieved through… Figure 5 The computer device shown is used to implement this, and the computer device 300 includes at least one processor 301, a communication bus 302, a memory 303, and at least one communication interface 304.

[0065] The processor 301 may be a general-purpose central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more devices used to control the execution of the intelligent extraction method for juglone from the green husk of walnuts in this application.

[0066] The communication bus 302 is used to transmit information between the aforementioned components.

[0067] Memory 303 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CDROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile optical discs, Blu-ray discs, etc.), magnetic disks or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. Memory 303 may exist independently and be connected to processor 301 via communication bus 302. Memory 303 may also be integrated with processor 301.

[0068] The memory 303 stores program code for executing the scheme of this application, and its execution is controlled by the processor 301. The processor 301 executes the program code stored in the memory 303. The program code may include one or more software modules. The intelligent extraction method of juglone from walnut husk in the above embodiments can be implemented by the processor 301 and one or more software modules in the program code in the memory 303.

[0069] Communication interface 304 uses any transceiver-like device to communicate with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0070] In a specific implementation, as one example, a computer device may include multiple processors, each of which may be a single-core processor or a multi-core processor. Here, a processor may refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0071] The aforementioned computer device can be a general-purpose computer device or a special-purpose computer device. In specific implementations, the computer device may be a desktop computer, a portable computer, a network server, a handheld digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. This application does not limit the type of computer device.

[0072] In addition, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described intelligent extraction method for juglone from walnut green husk.

[0073] In summary, the intelligent separation and extraction system and method for plant allelochemicals disclosed in this application involves collecting time-series data of dissolved oxygen concentration in walnut peel extract using an intelligent dissolved oxygen electrode; inputting this data into a controller; when the dissolved oxygen concentration exceeds a threshold, the controller opens a nitrogen valve and increases the ultrasonic power; if the dissolved oxygen continues to rise and the power has been adjusted to the preset maximum value without effect, a leak is detected and an alarm is triggered, resulting in a fully anaerobic ultrasonic extract; the fully anaerobic ultrasonic extract is pumped into a series of solid-phase extraction columns, and the dynamic adsorption saturation of juglone on the current column bed is determined based on the response intensity of an intelligent ultraviolet sensor at 334 nm; when the dynamic adsorption saturation of the first-stage column reaches... When the switching threshold is reached, the controller switches to the second-stage column and starts elution of the first-stage column. Simultaneously, based on the cumulative adsorption amount corresponding to the dynamic adsorption saturation and combined with the pre-calibrated elution parameter model, the elution flow rate and elution volume are determined to obtain an eluent enriched with juglone. Before the eluent enters the concentration and crystallization vessel, the current accumulation rate of oxidation risk is determined based on the real-time dissolved oxygen concentration monitored by the intelligent dissolved oxygen electrode and the real-time juglone concentration monitored by the intelligent ultraviolet sensor. When the accumulation rate reaches the threshold, the controller adds an antioxidant to the eluent, and concentrates and crystallizes to obtain high-purity juglone crystals. This can suppress the oxidative degradation of juglone caused by repeated exceedances of dissolved oxygen due to cavitation disturbances.

[0074] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0075] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A smart extraction method for juglone from walnut green husk, applied to a plant allelochemical intelligent separation and extraction system for the intelligent extraction of juglone from walnut green husk, characterized in that, The method includes the following steps: Time-series data of dissolved oxygen concentration in walnut green peel extract were collected using a smart dissolved oxygen electrode. The dissolved oxygen concentration time series data is input into the controller. When the dissolved oxygen concentration exceeds the threshold, the controller opens the nitrogen valve and increases the ultrasonic power. If the dissolved oxygen continues to rise and the power has been adjusted to the preset maximum value but is still ineffective, a leak is detected and an alarm is triggered, resulting in a fully oxygen-free ultrasonic extract. The fully anaerobic ultrasonic extraction solution was pumped into a series of solid-phase extraction columns, and the dynamic adsorption saturation of juglone in the current column bed was determined based on the response intensity of the intelligent ultraviolet sensor at 334 nm. When the dynamic adsorption saturation of the first-stage column reaches the switching threshold, the controller switches to the second-stage column and starts the elution of the first-stage column. At the same time, based on the cumulative adsorption amount corresponding to the dynamic adsorption saturation and combined with the pre-calibrated elution parameter model, the elution flow rate and elution volume are determined to obtain the eluent enriched with juglone. Before the eluent enters the concentration and crystallization vessel, the current accumulation rate of oxidation risk is determined based on the real-time dissolved oxygen concentration monitored by the intelligent dissolved oxygen electrode and the real-time juglone concentration monitored by the intelligent ultraviolet sensor. When the accumulation rate reaches a threshold, the controller adds an antioxidant to the eluent, and high-purity juglone crystals are obtained through concentration and crystallization.

2. The method as described in claim 1, characterized in that, The dissolved oxygen concentration time-series data is input into the controller. When the dissolved oxygen concentration exceeds the threshold, the controller opens the nitrogen valve and increases the ultrasonic power. If the dissolved oxygen continues to rise and the power has been adjusted to the preset maximum value but is still ineffective, a leak is detected and an alarm is triggered. The resulting fully anaerobic ultrasonic extraction solution specifically includes: The controller analyzes the dissolved oxygen concentration time-series data in real time, extracts the current dissolved oxygen concentration value, and calculates the dissolved oxygen change rate. The current dissolved oxygen concentration is compared with a preset threshold. If the threshold is exceeded, the controller opens the nitrogen valve and dynamically increases the ultrasonic power according to the rate of change of dissolved oxygen. If the ultrasonic power has been adjusted to the preset maximum value and the dissolved oxygen concentration continues to rise and the rate of rise exceeds the set rate threshold, then the system is determined to be leaking and an alarm signal is issued. Once the dissolved oxygen concentration drops below the threshold and stabilizes, it is confirmed that the extraction process is in a completely anaerobic state, and the completely anaerobic ultrasonic extract is output.

3. The method as described in claim 1, characterized in that, The fully anaerobic ultrasonic extraction solution is pumped into a series of solid-phase extraction columns. The dynamic adsorption saturation of juglone in the current column bed is determined based on the response intensity of the intelligent ultraviolet sensor at 334 nm. Specifically, this includes: The absorbance value of the effluent at 334 nm by the intelligent ultraviolet sensor is collected, and the absorbance value is converted into the corresponding real-time effluent concentration of juglone. The static maximum adsorption capacity of the porous chitosan solid-phase extraction column for juglone was obtained, and the theoretical saturated adsorption capacity of the column bed was established based on the static maximum adsorption capacity and the feed concentration. Based on the difference between the real-time effluent concentration and the feed concentration of juglone, the cumulative adsorption amount of juglone by the column bed at the current time is obtained by cumulative integration over time. The dynamic adsorption saturation of juglone in the current column bed is determined by comparing the cumulative adsorption amount with the theoretical saturation adsorption amount.

4. The method as described in claim 1, characterized in that, When the dynamic adsorption saturation of the first-stage column reaches the switching threshold, the controller switches to the second-stage column and starts elution of the first-stage column. Simultaneously, based on the cumulative adsorption amount corresponding to the dynamic adsorption saturation and combined with a pre-calibrated elution parameter model, the elution flow rate and elution volume are determined to obtain the eluent enriched with juglone. Specifically, this eluent includes: When the dynamic adsorption saturation of the first-stage column reaches the switching threshold, the controller performs a column switching operation, switches the feed liquid to the second-stage column, and causes the second-stage column to start adsorption. Determine the cumulative adsorption amount of the first-stage column throughout the entire adsorption cycle; Based on the cumulative adsorption amount and the pre-calibrated elution parameter model, the elution flow rate and elution volume of the first-stage column are determined. According to the determined elution flow rate and elution volume, start the elution program of the first-stage column and collect the effluent as the eluent for enriching juglone.

5. The method as described in claim 1, characterized in that, Before the eluent enters the concentration and crystallization vessel, the current rate of accumulation of oxidation risk is determined based on the real-time dissolved oxygen concentration monitored by the intelligent dissolved oxygen electrode and the real-time juglone concentration monitored by the intelligent ultraviolet sensor. Specifically, this includes: The real-time dissolved oxygen concentration is collected using an organic solvent-resistant smart fluorescent dissolved oxygen electrode, and the real-time juglone concentration is collected using an online ultraviolet sensor. Based on a preset oxidation risk model, the real-time dissolved oxygen concentration and real-time juglone concentration are converted into the cumulative rate of current oxidation risk.

6. The method as described in claim 1, characterized in that, When the accumulation rate reaches a threshold, the controller adds an antioxidant to the eluent, and the concentrated crystallization yields high-purity juglone crystals, specifically including: The current rate of accumulation of oxidation risk is compared with a preset risk threshold. If the accumulation rate reaches the threshold, the controller generates an addition command and determines the addition dose. According to the addition instruction, the addition execution mechanism is started, and the controller adds antioxidant to the eluent. After the residual antioxidant is removed by activated carbon adsorption pretreatment, it is sent to the concentration and crystallization kettle. After pretreatment, the concentration and crystallization process continues to obtain high-purity juglone crystals.

7. The method as described in claim 1, characterized in that, The 334 nm wavelength is the specific characteristic ultraviolet absorption wavelength of juglone concentration. At this wavelength, juglone has a strong characteristic absorption peak, and there is no significant interference from matrix impurities in the extract.

8. A smart separation and extraction system for phytoallergenic components, comprising a smart extraction unit, characterized in that, The intelligent extraction unit includes: The data acquisition module is used to collect time-series data on dissolved oxygen concentration in walnut green peel extract via an intelligent dissolved oxygen electrode. The processing module is used to input the dissolved oxygen concentration time-series data into the controller. When the dissolved oxygen concentration exceeds the threshold, the controller opens the nitrogen valve and increases the ultrasonic power. If the dissolved oxygen continues to rise and the power has been adjusted to the preset maximum value but is still ineffective, a leak is detected and an alarm is triggered, thus obtaining a fully oxygen-free ultrasonic extract. The processing module is also used to pump the fully anaerobic ultrasonic extraction liquid into a series solid-phase extraction column, and determine the dynamic adsorption saturation of juglone on the current column bed based on the response intensity of the intelligent ultraviolet sensor at 334 nm. The processing module is also used to switch the controller to the second column and start the first column elution when the dynamic adsorption saturation of the first column reaches the switching threshold. At the same time, based on the cumulative adsorption amount corresponding to the dynamic adsorption saturation and combined with the pre-calibrated elution parameter model, the elution flow rate and elution volume are determined to obtain the eluent enriched with juglone. The execution module is used to determine the current rate of accumulation of oxidation risk based on the real-time dissolved oxygen concentration monitored by the intelligent dissolved oxygen electrode and the real-time juglone concentration monitored by the intelligent ultraviolet sensor before the eluent enters the concentration and crystallization vessel. When the accumulation rate reaches a threshold, the controller adds an antioxidant to the eluent and concentrates and crystallizes to obtain high-purity juglone crystals.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the intelligent extraction method for juglone from walnut husk as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the intelligent extraction method for juglone from walnut husk as described in any one of claims 1 to 7.

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