Device and method for extracting anti-wrinkle components of peach trees

Abstract

The extraction method comprises the following steps: S1, selecting and cleaning leaves, fruits and barks of peach trees, and treating the leaves, the fruits and the barks of the peach trees by using low-temperature plasma in a low-temperature environment of-80 DEG C; s2, freeze-drying the treated raw materials in a vacuum freeze-drying machine, and crushing until the particle size is 1-10 microns; s3, mixing the crushed raw materials with an ionic liquid-supercritical carbon dioxide mixed solvent according to a volume ratio of 80: 20, wherein the ionic liquid-supercritical carbon dioxide mixed solvent is prepared according to a solid-to-liquid ratio of 1: 25, and extracting by a high-frequency pulsed electric field; s4, carrying out multi-stage nano-filtration through a micro-fluidic chip; s5, performing multi-stage concentration in an efficient vacuum centrifugal concentrator; s6, separating and purifying through a bionic nanofiber membrane; s7, carrying out molecular structure identification and quantitative analysis by combining high-resolution ultra-high performance liquid chromatography with a high-precision mass spectrometry technology; and S8, evaluating the anti-wrinkle effect through the intelligent bionic skin model in combination with a photoacoustic imaging technology. According to the method, the extraction efficiency is improved, and the stability and purity of the active ingredients are ensured.

Description

Technical Field

[0001] The invention relates to the technical field of plant extraction, in particular to an extraction device and an extraction method of peach anti-wrinkle components. Background Art

[0002] The main defects include the following aspects

[0003] 1. Extraction efficiency and maintenance of active ingredients: In traditional extraction methods, many active ingredients are prone to degradation or inactivation during the extraction process, resulting in low extraction efficiency and unstable product quality. Under high temperature, high pressure or strong mechanical force, the structure of the active ingredients is easily destroyed, affecting their biological activity.

[0004] 2. Environmental pollution and safety issues: The organic solvents used in the solvent extraction method pollute the environment and are potentially harmful to the health of operators. Although the supercritical fluid extraction method solves the problem of solvent residue, its high equipment cost and complex operation process limit its large-scale application.

[0005] 3. Cost and economic issues: The existing efficient extraction methods, supercritical fluid extraction and enzymatic hydrolysis, have high extraction efficiency, but they require large equipment investment and high operating costs, making them difficult to promote and apply in small and medium-sized enterprises. In addition, the enzymatic hydrolysis method requires a large amount of enzymes, which are expensive, further increasing the extraction cost.

[0006] 4. Process control and parameter optimization issues: In traditional extraction methods, the parameters of the extraction process often need to be explored through a large number of experiments. The lack of a systematic optimization method leads to an unstable extraction process and difficulty in ensuring product quality.

[0007] Therefore, how to provide a device and method for extracting the anti-wrinkle components of peach is an urgent problem to be solved by those skilled in the art. Summary of the invention

[0008] One object of the present invention is to provide an extraction device and an extraction method for peach anti-wrinkle components. The present invention provides a novel extraction device and an extraction method for peach anti-wrinkle components. Through low-temperature plasma treatment, vacuum freeze drying, nanomechanical ball milling, ionic liquid-supercritical carbon dioxide mixed solvent extraction, microfluidic chip nanofiltration, high-efficiency vacuum centrifugal concentration, bionic nanofiber membrane separation, high-resolution analysis and intelligent bionic skin model evaluation and other steps, combined with AI algorithm optimization and real-time monitoring, the extraction efficiency, the retention rate of active ingredients and the quality stability of the product are comprehensively improved, and multiple technical problems in traditional extraction methods are solved.

[0009] According to an embodiment of the present invention, a device and method for extracting anti-wrinkle components from peach trees include the following steps:

[0010] S1. Select the leaves, fruits and bark of peach trees as raw materials, wash them, and treat them by low-temperature plasma in a low-temperature environment of 80°C. Use a strong electric field >10kV / cm to further destroy the cell wall while retaining the active ingredients. The low-temperature plasma system monitors the temperature and electric field strength during the treatment process in real time.

[0011] S2. Place the raw material after low-temperature plasma treatment in a vacuum freeze dryer for freeze drying. Real-time monitoring of the temperature and pressure during the drying process shows that when the moisture content of the raw material drops below 1%, take out the dried raw material, crush it into particles of 1-10 microns using a nanomechanical ball mill, and optimize the crushing parameters using an optimization model based on topological data analysis and high-performance long-term coherence.

[0012] S3. Mix the crushed raw material powder with ionic liquid supercritical carbon dioxide configured at a solid-liquid ratio of 1:25, and the solvent volume ratio is 80:20, and extract it in a high-frequency pulse electric field. The extraction frequency is set to 50kHz, the electric field strength is 20kV / cm, the extraction temperature is 10-15°C, and the extraction time is 10-15 minutes; the high-frequency pulse electric field is combined with ionic liquid and supercritical carbon dioxide to optimize the efficiency of cell disruption and active ingredient release. During the extraction process, an AI algorithm model based on Hamiltonian path optimization and fractal geometry is used to adjust the electric field parameters in real time to optimize the extraction efficiency;

[0013] S4. The extracted extract is subjected to multi-stage nanofiltration through a microfluidic chip, and an ultrafiltration membrane with a pore size of 0.001 micron is used for preliminary separation to remove macromolecular impurities, and a nanofiltration membrane with a pore size of 0.0001 micron is used for deep purification to remove small molecular impurities. The microfluidic chip system is combined with an AI optimization algorithm model based on quantum state transfer and chaotic dynamics to monitor and optimize the flow rate and pressure during the filtration process in real time;

[0014] S5. The purified extract is concentrated in multiple stages in a high-efficiency vacuum centrifugal concentrator at a low temperature of <25°C, and the extract is concentrated to 1 / 100 of the original volume by using rotary evaporation technology. During the concentration process, the temperature and vacuum parameters are optimized by using an AI optimization algorithm based on adaptive control algorithm and chaotic dynamics. The concentrated extract contains a high concentration of anti-wrinkle active ingredients.

[0015] S6, separating and purifying the concentrated extract through a bionic nanofiber membrane, using ethyl acetate and water in a volume ratio of 4:6 to further purify the extract components;

[0016] S7. Use high-resolution ultra-high performance liquid chromatography combined with high-precision mass spectrometry technology to conduct multi-dimensional molecular structure identification and quantitative analysis of the extracted anti-wrinkle active ingredients. Optimize the identification process through big data analysis, optimize the purity and effectiveness of the ingredients, and record and analyze data in real time during the analysis process;

[0017] S8. The absorption and anti-wrinkle effects of anti-wrinkle active ingredients in simulated human skin were evaluated by combining an intelligent bionic skin model with photoacoustic imaging technology. Cell activity analysis and gene expression profile analysis were used to verify their role in promoting skin collagen synthesis. The test process was optimized using AI algorithms to test the reliability and accuracy of experimental data.

[0018] Optionally, the S2 specifically includes:

[0019] S21, placing the raw material treated with low temperature plasma in a vacuum freeze dryer for freeze drying, wherein the temperature during freeze drying is 50° C. to 80° C., and the pressure is 10 -2 Up to 10 -3 pa, real-time monitoring of temperature and pressure during freeze drying, when the moisture content of the raw material drops below 1%, take out the dried raw material;

[0020] S22, using a nanomechanical ball mill to grind the dried raw material to a particle size of 1-10 microns, the rotation speed of the nanomechanical ball mill is 500-1000 rpm, the grinding time is 2-5 hours, collecting powder samples at different time points during the grinding process, and using a dynamic light scattering instrument to measure the particle size distribution P(d) of each sample to obtain particle size distribution data;

[0021] S23, the particle size distribution data P(d) is input into the optimization model based on topological data analysis and high-performance persistent coherence, and the topological feature vector T(d) is established by calculating the persistent coherence characteristics of the sample data:

[0022]

[0023] Among them, H i is the i-th permanent homology group, C(d) is the Simpson complex covering the sample space;

[0024] S24. Analyze and process the topological feature vector T(d) obtained from the topological data analysis using a high-dimensional geometric deep learning model:

[0025]

[0026] Among them, Tk(d) is the topological feature vector of the kth sample, is the output of the deep learning model, θ is the model parameter set, and λ is the regularization parameter;

[0027] S25. Combined with the optimized high-dimensional features obtained from the geometric deep learning model, the high-dimensional features are further optimized using quantum Monte Carlo simulation in quantum many-body systems:

[0028]

[0029] in, is the quantum state in the Hamiltonian The expected value under m is the target energy value, and the optimized quantum features are used for the final fusion model optimization;

[0030] S26. Input the optimized high-dimensional features into the optimization model based on the combination of geometric deep learning and quantum Monte Carlo simulation, and minimize the optimization objective function of the fusion model by iteratively optimizing the crushing parameters:

[0031]

[0032] Among them, γ is the adjustment coefficient, and the optimization of this objective function is used to update the adaptive gradient descent algorithm;

[0033] S27, based on the optimization objective function The feedback of is used to update the crushing parameters using the adaptive gradient descent algorithm:

[0034]

[0035] Among them, η is the learning rate, G t is the sum of squared gradients in the past, ∈ is the smoothing parameter, and the updated crushing parameters are used to monitor and adjust the operating parameters in real time;

[0036] S28. After each iteration, the particle size distribution P(d) is monitored in real time, and the operating parameters, rotation speed and crushing time of the nanomechanical ball mill are adjusted according to the feedback of the optimization model until the objective function is optimized. Converge to the preset threshold and obtain the final optimized crushing parameters.

[0037] Optionally, the S3 specifically includes:

[0038] S31, mixing the crushed raw material powder with an ionic liquid supercritical carbon dioxide mixed solvent configured at a solid-liquid ratio of 1:25 in a volume ratio of 80:20 to obtain a mixed slurry;

[0039] S32, placing the mixed slurry in a high-frequency pulse electric field reactor, setting the extraction frequency to 50kHz, the electric field strength to 20kV / cm, extracting in the high-frequency pulse electric field reactor, controlling the extraction temperature at 10-15°C, and setting the extraction time to 10-15 minutes;

[0040] S33, during the extraction process, the electric field intensity E in the high-frequency pulse electric field reactor is monitored in real time by real-time monitoring of the electric field intensity and extraction time. i and extraction time t j , using electric field strength sensors and time recorders to record data;

[0041] S34, real-time monitoring data E i and t j The input is fed into the AI ​​algorithm model based on Hamiltonian path optimization and fractal geometry, which uses the fusion objective function for optimization:

[0042]

[0043] in, represents the Hamiltonian path length, E i is the electric field strength, t j is the extraction time, t opt To optimize the extraction time, N is the number of electric field intensity samples, M is the number of time samples, and β is the regularization parameter. The electric field parameters are adjusted through this optimization objective function;

[0044] S35. According to the fusion objective function The electric field strength and extraction time of the high-frequency pulse electric field reactor are adjusted in real time through the feedback loop according to the monitored electric field strength E i and extraction time t j , the system automatically adjusts these parameters for optimization;

[0045] S36. During the adjustment process, the optimization parameters are updated using an adaptive gradient descent algorithm based on Adamak surface optimization:

[0046]

[0047] Among them, θ is the optimization parameter set, η is the learning rate, γ is the high-order derivative adjustment coefficient, is the gradient of the objective function, Δ Had is the Laplace operator of the Adamak surface, h(θ) is the metric tensor, and the electric field intensity and extraction time are optimized by adjusting the optimization parameter θ;

[0048] S37, after each extraction process is completed, record and analyze the data of electric field strength and extraction time, and use these data to update the optimization algorithm model;

[0049] S38, repeating the above steps until the optimization parameters θ of the electric field intensity and extraction time in the extraction process converge to a preset threshold, and continuously optimizing the extraction efficiency and the stability of the active ingredient through continuous cycles and adjustments;

[0050] S39, after the extraction is completed, the extract is taken out from the high-frequency pulse electric field reactor, and is initially separated using a centrifugal separation device to separate the liquid portion as the extract;

[0051] S310, cooling the extract to reduce the temperature to below 5°C to stabilize the active ingredients. The cooled extract is used for subsequent filtration and purification steps.

[0052] Optionally, the S5 specifically includes:

[0053] S51, place the purified extract in a high-efficiency vacuum centrifugal concentrator and set the initial vacuum degree to 10 2 Up to 10 3 Pa, the temperature was controlled below 25°C, and the high-efficiency vacuum centrifugal concentrator was started for preliminary concentration. The extract was concentrated to 1 / 10 of the original volume under low temperature conditions using rotary evaporation technology, and the temperature and vacuum degree were monitored in real time during the process;

[0054] S52, the extract after preliminary concentration is transferred to the second stage vacuum centrifugal concentrator, and the vacuum degree is set to 10 4 Pa, continue to concentrate to 1 / 50 of the original volume;

[0055] S53. Using AI optimization algorithm model, real-time monitoring of vacuum degree P(t) and concentrated liquid volume V(t) is performed during the concentration process, and data is obtained using vacuum sensors and liquid level sensors;

[0056] S54. Input the real-time monitoring data P(t) and V(t) into the AI ​​optimization algorithm model based on quantum state transfer and chaotic dynamics:

[0057]

[0058] Among them, |ψ(P(t i ))| 2 represents the quantum state probability amplitude of the vacuum degree, represents the quantum state probability amplitude of the concentrated liquid volume, P(t) is the vacuum degree, V(t) is the concentrated liquid volume, α is the adjustment coefficient, V target is the target concentration volume, γ is the regularization parameter, T is the number of samples at the vacuum time point, and M is the number of samples at the volume time point;

[0059] S55. Calculate the gradient of the objective function using an adaptive control algorithm based on chaos mapping and fractal geometry The gradient calculation formula is:

[0060]

[0061] Among them, θ is the control parameter set, including vacuum degree and temperature control parameters;

[0062] S56, iteratively updating the control parameters through the adaptive control algorithm, the updating formula is:

[0063]

[0064] Among them, η is the learning rate, λ is the chaotic dynamics adjustment coefficient, Δ Fractal represents the Laplace operator of fractal geometry, F(θ) is the fractal metric tensor;

[0065] S57, during the concentration process, the vacuum degree and temperature parameters are adjusted in real time, and the objective function is optimized according to the feedback loop so that the volume of the concentrated liquid gradually reaches the target volume V target ;

[0066] S58. When optimizing the objective function When the vacuum and temperature control parameters converge to the preset threshold, the final vacuum and temperature control parameters are recorded and saved. The vacuum and temperature parameters are adjusted in real time through the feedback loop.

[0067] S59. When the volume of the extract reaches the target concentrated volume, stop the vacuum centrifugal concentrator to collect the concentrated high-concentration anti-wrinkle active ingredients.

[0068] Optionally, the S8 specifically includes:

[0069] S81, applying the extracted anti-wrinkle active ingredients to the surface of the intelligent bionic skin model, where the bionic skin model has similar structure and physiological properties to human skin;

[0070] S82. Use photoacoustic imaging technology to monitor the bionic skin model and obtain the absorption distribution data of the anti-wrinkle active ingredient in the skin in real time, wherein the absorption distribution data is represented by the photoacoustic signal intensity A(t, x, y, z), where t is time, and x, y, and z are spatial coordinates;

[0071] S83, input the photoacoustic signal intensity A(t, x, y, z) into a deep learning algorithm based on topological data analysis (TDA) and singular value decomposition (SVD) to extract the topological feature (T(A), the calculation formula of which is:

[0072]

[0073] Among them, σ k represents singular value, β k represents the Betti number of the k-th homology group;

[0074] S84. The activity of cells in the bionic skin model is detected using a cell activity analyzer. The cell activity is represented by the Fermi-Dirac distribution function f(E, t):

[0075]

[0076] Where E is energy, μ(t) is chemical potential, k is Boltzmann constant, and T is absolute temperature;

[0077] S85. Perform gene expression spectrum analysis, analyze gene expression levels through multi-body wave functions, and express gene expression levels with quantum multi-body states Ψ(g, t), where g is a gene identifier and t is time. The calculation formula of quantum multi-body states is:

[0078]

[0079] Among them, c i (t) is the time-dependent coefficient, is the ground state wave function of the gene;

[0080] S86. The topological features T(A), the Fermi-Dirac distribution of cell activity f(E, t) and the quantum multi-body state Ψ(g, t) of gene expression levels were input into a hybrid model based on high-dimensional geometric deep learning and variational quantum eigensolver to evaluate the effect of anti-wrinkle active ingredients on skin collagen synthesis:

[0081]

[0082] Among them, γ, λ and ν are adjustment coefficients, <Ψ k |H|Ψ k > is the expected value of the multi-body state, E k is the corresponding energy level, f target For the target Fermi-Dirac distribution, N and M are the number of time samples, respectively, and P is the number of gene samples;

[0083] S87. Based on the evaluation results, optimize the formulation of the anti-wrinkle active ingredients and optimize their absorption and anti-wrinkle effects in simulated human skin;

[0084] S88, loop through the above steps until the objective function is optimized. Converge to a preset threshold.

[0085] Optionally, the device specifically includes:

[0086] Low-temperature plasma treatment unit, including a low-temperature plasma generator and a strong electric field generator, is used to treat the raw materials in a low-temperature environment of 80°C to further destroy the cell wall and retain the active ingredients. The low-temperature plasma system monitors the temperature and electric field strength during the treatment process in real time;

[0087] The vacuum freeze drying unit includes a vacuum freeze dryer for freeze drying the raw material after low temperature plasma treatment. The temperature during freeze drying is 50°C to 80°C and the pressure is 10 -2 Up to 10 -3 Pa, real-time monitoring of temperature and pressure during freeze drying, when the moisture content of the raw material drops below 1%, take out the dried raw material;

[0088] A nanomechanical ball mill unit, comprising a nanomechanical ball mill, for crushing the dried raw material into a particle size of 1-10 microns, the rotation speed of the nanomechanical ball mill is 500-1000 rpm, the crushing time is 2-5 hours, the crushing parameters are optimized in combination with a machine learning algorithm, and the crushing process is controlled using the optimized crushing parameters to obtain a powder with uniform particle size distribution;

[0089] The high-frequency pulse electric field extraction unit includes a high-frequency pulse electric field reactor, which is used to mix and extract the crushed raw material powder with an ionic liquid supercritical carbon dioxide mixed solvent. The extraction frequency is set to 50kHz, the electric field strength is 20kV / cm, the extraction temperature is controlled at 10-15°C, and the extraction time is set to 10-15 minutes. The AI ​​algorithm adjusts the electric field strength and extraction time in real time to optimize the extraction efficiency;

[0090] The microfluidic chip filtration unit includes a microfluidic chip system for multi-stage nanofiltration of the extracted extract, with an ultrafiltration membrane with a pore size of 0.001 micron used for preliminary separation and a nanofiltration membrane with a pore size of 0.0001 micron used for deep purification. The microfluidic chip system is combined with an intelligent algorithm to monitor and optimize the flow rate and pressure during the filtration process in real time;

[0091] The high-efficiency vacuum centrifugal concentration unit includes a high-efficiency vacuum centrifugal concentrator for multi-stage concentration of the purified extract, with an initial vacuum degree of 10 -2 Up to 10 -3 Pa, the temperature is controlled below 25°C, the extract is concentrated to 1 / 100 of the original volume, and the AI ​​algorithm optimizes the temperature and vacuum parameters during the concentration process;

[0092] A biomimetic nanofiber membrane separation unit, including a biomimetic nanofiber membrane system, is used to separate and purify the concentrated extract, and further purify the target component using a solvent with a volume ratio of ethyl acetate to water of 4:6;

[0093] High-resolution analysis unit, including a high-resolution ultra-high-performance liquid chromatography and high-precision mass spectrometry system, for multi-dimensional molecular structure identification and quantitative analysis of extracted anti-wrinkle active ingredients, big data analysis to optimize the identification process, and real-time recording and analysis of data;

[0094] The intelligent bionic skin model evaluation unit includes an intelligent bionic skin model and a photoacoustic imaging system, which are used to evaluate the absorption and anti-wrinkle effects of anti-wrinkle active ingredients in simulated human skin. Cell activity analysis and gene expression profile analysis verify the promoting effect of anti-wrinkle active ingredients on skin collagen synthesis, and combine AI algorithms to optimize the test process.

[0095] Beneficial Effects

[0096] 1. Efficient extraction and preservation of active ingredients: Low-temperature plasma treatment and vacuum freeze-drying technology are used to extract under low temperature and low pressure environment, which maximizes the biological activity of active ingredients. At the same time, nano-mechanical ball milling and ionic liquid-supercritical carbon dioxide mixed solvent extraction technology improve the efficiency of cell wall fragmentation and the release efficiency of active ingredients.

[0097] 2. Environmental protection and safety: The entire extraction process avoids the use of organic solvents, adopts green solvents and low temperature and low pressure operations, reduces environmental pollution and operational risks, and meets the requirements of environmental protection and safe production.

[0098] 3. Cost control: By optimizing the extraction process and parameters, the equipment operating cost and energy consumption are reduced, and the economic benefits are improved. In particular, the process control and parameter optimization combined with AI algorithms achieve efficient and stable production.

[0099] 4. Intelligence and automation: Through real-time monitoring and AI algorithm optimization, key parameters in the extraction process are automatically adjusted to ensure the stability of extraction efficiency and product quality, greatly improving the intelligence and automation level of production. BRIEF DESCRIPTION OF THE DRAWINGS

[0100] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0101] Figure 1 A summary of the invention is provided for a device and method for extracting anti-wrinkle components from peach trees;

[0102] Figure 2 The figure of claim 3 of the device and method for extracting the anti-wrinkle component of peach tree proposed by the present invention;

[0103] Figure 3 The present invention provides an extraction device and a flowchart of an extraction method of peach anti-wrinkle components. Implementation

[0104] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, and therefore only show the components related to the present invention.

[0105] refer to Figure 1-3 , a device and method for extracting anti-wrinkle components from peach trees, comprising the following steps:

[0106] S1. Select the leaves, fruits and bark of peach trees as raw materials, wash them, and treat them by low-temperature plasma in a low-temperature environment of 80°C. Use a strong electric field >10kV / cm to further destroy the cell wall while retaining the active ingredients. The low-temperature plasma system monitors the temperature and electric field strength during the treatment process in real time.

[0107] S2. Place the raw material after low-temperature plasma treatment in a vacuum freeze dryer for freeze drying. Real-time monitoring of the temperature and pressure during the drying process shows that when the moisture content of the raw material drops below 1%, take out the dried raw material, crush it into particles of 1-10 microns using a nanomechanical ball mill, and optimize the crushing parameters using an optimization model based on topological data analysis and high-performance long-term coherence.

[0108] S3. Mix the crushed raw material powder with ionic liquid supercritical carbon dioxide configured at a solid-liquid ratio of 1:25, and the solvent volume ratio is 80:20, and extract it in a high-frequency pulse electric field. The extraction frequency is set to 50kHz, the electric field strength is 20kV / cm, the extraction temperature is 10-15°C, and the extraction time is 10-15 minutes; the high-frequency pulse electric field is combined with ionic liquid and supercritical carbon dioxide to optimize the efficiency of cell disruption and active ingredient release. During the extraction process, an AI algorithm model based on Hamiltonian path optimization and fractal geometry is used to adjust the electric field parameters in real time to optimize the extraction efficiency;

[0109] S4. The extracted extract is subjected to multi-stage nanofiltration through a microfluidic chip, and an ultrafiltration membrane with a pore size of 0.001 micron is used for preliminary separation to remove macromolecular impurities, and a nanofiltration membrane with a pore size of 0.0001 micron is used for deep purification to remove small molecular impurities. The microfluidic chip system is combined with an AI optimization algorithm model based on quantum state transfer and chaotic dynamics to monitor and optimize the flow rate and pressure during the filtration process in real time;

[0110] S5. The purified extract is concentrated in multiple stages in a high-efficiency vacuum centrifugal concentrator at a low temperature of <25°C, and the extract is concentrated to 1 / 100 of the original volume by using rotary evaporation technology. During the concentration process, the temperature and vacuum parameters are optimized by using an AI optimization algorithm based on adaptive control algorithm and chaotic dynamics. The concentrated extract contains a high concentration of anti-wrinkle active ingredients.

[0111] S6, separating and purifying the concentrated extract through a bionic nanofiber membrane, using ethyl acetate and water in a volume ratio of 4:6 to further purify the extract components;

[0112] S7. Use high-resolution ultra-high performance liquid chromatography combined with high-precision mass spectrometry technology to conduct multi-dimensional molecular structure identification and quantitative analysis of the extracted anti-wrinkle active ingredients. Optimize the identification process through big data analysis, optimize the purity and effectiveness of the ingredients, and record and analyze data in real time during the analysis process;

[0113] S8. The absorption and anti-wrinkle effects of anti-wrinkle active ingredients in simulated human skin were evaluated by combining an intelligent bionic skin model with photoacoustic imaging technology. Cell activity analysis and gene expression profile analysis were used to verify their role in promoting skin collagen synthesis. The test process was optimized using AI algorithms to test the reliability and accuracy of experimental data.

[0114] In this implementation, S2 specifically includes:

[0115] S21, placing the raw material after low temperature plasma treatment in a vacuum freeze dryer for freeze drying, wherein the temperature during freeze drying is 50° C. to 80° C., and the pressure is 10 -2 Up to 10 -3 Pa, real-time monitoring of temperature and pressure during freeze drying, when the moisture content of the raw material drops below 1%, take out the dried raw material;

[0116] S22, using a nanomechanical ball mill to grind the dried raw material to a particle size of 1-10 microns, the rotation speed of the nanomechanical ball mill is 500-1000 rpm, the grinding time is 2-5 hours, collecting powder samples at different time points during the grinding process, and using a dynamic light scattering instrument to measure the particle size distribution P(d) of each sample to obtain particle size distribution data;

[0117] S23, the particle size distribution data P(d) is input into the optimization model based on topological data analysis and high-performance persistent coherence, and the topological feature vector T(d) is established by calculating the persistent coherence characteristics of the sample data:

[0118]

[0119] Among them, H i is the i-th permanent homology group, C(d) is the Simpson complex covering the sample space;

[0120] S24. Analyze and process the topological feature vector T(d) obtained from the topological data analysis using a high-dimensional geometric deep learning model:

[0121]

[0122] Among them, Tk(d) is the topological feature vector of the kth sample, is the output of the deep learning model, θ is the model parameter set, and λ is the regularization parameter;

[0123] S25. Combined with the optimized high-dimensional features obtained from the geometric deep learning model, the high-dimensional features are further optimized using quantum Monte Carlo simulation in quantum many-body systems:

[0124]

[0125] in, is the quantum state in the Hamiltonian The expected value under m is the target energy value, and the optimized quantum features are used for the final fusion model optimization;

[0126] S26. Input the optimized high-dimensional features into the optimization model based on the combination of geometric deep learning and quantum Monte Carlo simulation, and minimize the optimization objective function of the fusion model by iteratively optimizing the crushing parameters:

[0127]

[0128] Among them, γ is the adjustment coefficient, and the optimization of this objective function is used to update the adaptive gradient descent algorithm;

[0129] S27, based on the optimization objective function The feedback of is used to update the crushing parameters using the adaptive gradient descent algorithm:

[0130]

[0131] Among them, η is the learning rate, G t is the sum of squared gradients in the past, ∈ is the smoothing parameter, and the updated crushing parameters are used to monitor and adjust the operating parameters in real time;

[0132] S28. After each iteration, the particle size distribution P(d) is monitored in real time, and the operating parameters, rotation speed and crushing time of the nanomechanical ball mill are adjusted according to the feedback of the optimization model until the objective function is optimized. Converge to the preset threshold and obtain the final optimized crushing parameters.

[0133] In this implementation, S3 specifically includes:

[0134] S31, mixing the crushed raw material powder with an ionic liquid supercritical carbon dioxide mixed solvent configured at a solid-liquid ratio of 1:25 in a volume ratio of 80:20 to obtain a mixed slurry;

[0135] S32, placing the mixed slurry in a high-frequency pulse electric field reactor, setting the extraction frequency to 50kHz, the electric field strength to 20kV / cm, extracting in the high-frequency pulse electric field reactor, controlling the extraction temperature at 10-15°C, and setting the extraction time to 10-15 minutes;

[0136] S33, during the extraction process, the electric field intensity E in the high-frequency pulse electric field reactor is monitored in real time by real-time monitoring of the electric field intensity and extraction time. i and extraction time t j , using electric field strength sensors and time recorders to record data;

[0137] S34, real-time monitoring data E i and t j The input is fed into the AI ​​algorithm model based on Hamiltonian path optimization and fractal geometry, which uses the fusion objective function for optimization:

[0138]

[0139] in, represents the Hamiltonian path length, E i is the electric field strength, t j is the extraction time, t opt To optimize the extraction time, N is the number of electric field intensity samples, M is the number of time samples, and β is the regularization parameter. The electric field parameters are adjusted through this optimization objective function;

[0140] S35. According to the fusion objective function The electric field strength and extraction time of the high-frequency pulse electric field reactor are adjusted in real time through the feedback loop according to the monitored electric field strength E i and extraction time t j , the system automatically adjusts these parameters for optimization;

[0141] S36. During the adjustment process, the optimization parameters are updated using an adaptive gradient descent algorithm based on Adamak surface optimization:

[0142]

[0143] Among them, θ is the optimization parameter set, η is the learning rate, γ is the high-order derivative adjustment coefficient, is the gradient of the objective function, Δ Had is the Laplace operator of the Adamak surface, h(θ) is the metric tensor, and the electric field intensity and extraction time are optimized by adjusting the optimization parameter θ;

[0144] S37, after each extraction process is completed, record and analyze the data of electric field strength and extraction time, and use these data to update the optimization algorithm model;

[0145] S38, repeating the above steps until the optimization parameters θ of the electric field intensity and extraction time in the extraction process converge to a preset threshold, and continuously optimizing the extraction efficiency and the stability of the active ingredient through continuous cycles and adjustments;

[0146] S39, after the extraction is completed, the extract is taken out from the high-frequency pulse electric field reactor, and is initially separated using a centrifugal separation device to separate the liquid portion as the extract;

[0147] S310, cooling the extract to reduce the temperature to below 5°C to stabilize the active ingredients. The cooled extract is used for subsequent filtration and purification steps.

[0148] In this implementation, S5 specifically includes:

[0149] S51, place the purified extract in a high-efficiency vacuum centrifugal concentrator and set the initial vacuum degree to 10 2 Up to 10 3 Pa, the temperature was controlled below 25°C, and the high-efficiency vacuum centrifugal concentrator was started for preliminary concentration. The extract was concentrated to 1 / 10 of the original volume under low temperature conditions using rotary evaporation technology, and the temperature and vacuum degree were monitored in real time during the process;

[0150] S52, the extract after preliminary concentration is transferred to the second stage vacuum centrifugal concentrator, and the vacuum degree is set to 10 4 Pa, continue to concentrate to 1 / 50 of the original volume;

[0151] S53. Using AI optimization algorithm model, real-time monitoring of vacuum degree P(t) and concentrated liquid volume V(t) is performed during the concentration process, and data is obtained using vacuum sensors and liquid level sensors;

[0152] S54. Input the real-time monitoring data P(t) and V(t) into the AI ​​optimization algorithm model based on quantum state transfer and chaotic dynamics:

[0153]

[0154] Among them, |ψ(P(t i ))| 2 represents the quantum state probability amplitude of the vacuum degree, represents the quantum state probability amplitude of the concentrated liquid volume, P(t) is the vacuum degree, V(t) is the concentrated liquid volume, α is the adjustment coefficient, V target is the target concentration volume, γ is the regularization parameter, T is the number of samples at the vacuum time point, and M is the number of samples at the volume time point;

[0155] S55. Calculate the gradient of the objective function using an adaptive control algorithm based on chaos mapping and fractal geometry The gradient calculation formula is:

[0156]

[0157] Among them, θ is the control parameter set, including vacuum degree and temperature control parameters;

[0158] S56, iteratively updating the control parameters through the adaptive control algorithm, the updating formula is:

[0159]

[0160] Among them, η is the learning rate, λ is the chaotic dynamics adjustment coefficient, Δ Fractal represents the Laplace operator of fractal geometry, F(θ) is the fractal metric tensor;

[0161] S57, during the concentration process, the vacuum degree and temperature parameters are adjusted in real time, and the objective function is optimized according to the feedback loop so that the volume of the concentrated liquid gradually reaches the target volume V target ;

[0162] S58. When optimizing the objective function When the vacuum and temperature control parameters converge to the preset threshold, the final vacuum and temperature control parameters are recorded and saved. The vacuum and temperature parameters are adjusted in real time through the feedback loop.

[0163] S59. When the volume of the extract reaches the target concentrated volume, stop the vacuum centrifugal concentrator to collect the concentrated high-concentration anti-wrinkle active ingredients.

[0164] In this implementation, S8 specifically includes:

[0165] S81, applying the extracted anti-wrinkle active ingredients to the surface of the intelligent bionic skin model, where the bionic skin model has similar structure and physiological properties to human skin;

[0166] S82, using photoacoustic imaging technology to monitor the bionic skin model, and obtaining the absorption distribution data of the anti-wrinkle active ingredient in the skin in real time, wherein the absorption distribution data is represented by the photoacoustic signal intensity A(t, x, y, z), where t is time, and x, y, and z are spatial coordinates;

[0167] S83, input the photoacoustic signal intensity A(t, x, y, z) into a deep learning algorithm based on topological data analysis (TDA) and singular value decomposition (SVD) to extract the topological feature (T(A), the calculation formula of which is:

[0168]

[0169] Among them, σ krepresents singular value, β k represents the Betti number of the k-th homology group;

[0170] S84. The activity of cells in the bionic skin model is detected using a cell activity analyzer. The cell activity is represented by the Fermi-Dirac distribution function f(E, t):

[0171]

[0172] Where E is energy, μ(t) is chemical potential, k is Boltzmann constant, and T is absolute temperature;

[0173] S85. Perform gene expression spectrum analysis, analyze gene expression levels through multi-body wave functions, and express gene expression levels with quantum multi-body states Ψ(g, t), where g is a gene identifier and t is time. The calculation formula of quantum multi-body states is:

[0174]

[0175] Among them, c i (t) is the time-dependent coefficient, is the ground state wave function of the gene;

[0176] S86. The topological features T(A), the Fermi-Dirac distribution of cell activity f(E, t) and the quantum multi-body state Ψ(g, t) of gene expression levels were input into a hybrid model based on high-dimensional geometric deep learning and variational quantum eigensolver to evaluate the effect of anti-wrinkle active ingredients on skin collagen synthesis:

[0177]

[0178] Among them, γ, λ and ν are adjustment coefficients, <Ψ k |H|Ψ k > is the expected value of the multi-body state, E k is the corresponding energy level, f target For the target Fermi-Dirac distribution, N and M are the number of time samples, respectively, and P is the number of gene samples;

[0179] S87. Based on the evaluation results, optimize the formulation of the anti-wrinkle active ingredients and optimize their absorption and anti-wrinkle effects in simulated human skin;

[0180] S88, loop through the above steps until the objective function is optimized. Converge to a preset threshold.

[0181] In this embodiment, the device specifically includes:

[0182] Low-temperature plasma treatment unit, including a low-temperature plasma generator and a strong electric field generator, is used to treat the raw materials in a low-temperature environment of 80°C to further destroy the cell wall and retain the active ingredients. The low-temperature plasma system monitors the temperature and electric field strength during the treatment process in real time;

[0183] The vacuum freeze drying unit includes a vacuum freeze dryer for freeze drying the raw material after low temperature plasma treatment. The temperature during freeze drying is 50°C to 80°C and the pressure is 10 -2 Up to 10 -3 pa, real-time monitoring of temperature and pressure during freeze drying, when the moisture content of the raw material drops below 1%, take out the dried raw material;

[0184] A nanomechanical ball mill unit, comprising a nanomechanical ball mill, for crushing the dried raw material into a particle size of 1-10 microns, the rotation speed of the nanomechanical ball mill is 500-1000 rpm, the crushing time is 2-5 hours, the crushing parameters are optimized in combination with a machine learning algorithm, and the crushing process is controlled using the optimized crushing parameters to obtain a powder with uniform particle size distribution;

[0185] The high-frequency pulse electric field extraction unit includes a high-frequency pulse electric field reactor, which is used to mix and extract the crushed raw material powder with an ionic liquid supercritical carbon dioxide mixed solvent. The extraction frequency is set to 50kHz, the electric field strength is 20kV / cm, the extraction temperature is controlled at 10-15°C, and the extraction time is set to 10-15 minutes. The AI ​​algorithm adjusts the electric field strength and extraction time in real time to optimize the extraction efficiency;

[0186] The microfluidic chip filtration unit includes a microfluidic chip system for multi-stage nanofiltration of the extracted extract, with an ultrafiltration membrane with a pore size of 0.001 micron used for preliminary separation and a nanofiltration membrane with a pore size of 0.0001 micron used for deep purification. The microfluidic chip system is combined with an intelligent algorithm to monitor and optimize the flow rate and pressure during the filtration process in real time;

[0187] The high-efficiency vacuum centrifugal concentration unit includes a high-efficiency vacuum centrifugal concentrator for multi-stage concentration of the purified extract, with an initial vacuum degree of 10 -2 Up to 10 -3 Pa, the temperature is controlled below 25°C, the extract is concentrated to 1 / 100 of the original volume, and the AI ​​algorithm optimizes the temperature and vacuum parameters during the concentration process;

[0188] A biomimetic nanofiber membrane separation unit, including a biomimetic nanofiber membrane system, is used to separate and purify the concentrated extract, and further purify the target component using a solvent with a volume ratio of ethyl acetate to water of 4:6;

[0189] High-resolution analysis unit, including a high-resolution ultra-high-performance liquid chromatography and high-precision mass spectrometry system, for multi-dimensional molecular structure identification and quantitative analysis of extracted anti-wrinkle active ingredients, big data analysis to optimize the identification process, and real-time recording and analysis of data;

[0190] The intelligent bionic skin model evaluation unit includes an intelligent bionic skin model and a photoacoustic imaging system, which are used to evaluate the absorption and anti-wrinkle effects of anti-wrinkle active ingredients in simulated human skin. Cell activity analysis and gene expression profile analysis verify the promoting effect of anti-wrinkle active ingredients on skin collagen synthesis, and combine AI algorithms to optimize the test process. Example

[0191] In order to verify the feasibility of the present invention in implementation, the present invention is applied to a biotechnology laboratory located in Zhangjiang High-tech Park, Pudong New Area, a certain city. The laboratory is equipped with a low-temperature plasma treatment device, a vacuum freeze dryer, a nanomechanical ball mill, a high-frequency pulsed electric field reactor, a microfluidic chip filtration device, a high-efficiency vacuum centrifugal concentrator, a bionic nanofiber membrane separation device, a high-resolution ultra-high performance liquid chromatography and a high-precision mass spectrometry system, as well as an intelligent bionic skin model and a photoacoustic imaging system.

[0192] Select fresh peach leaves, fruits and bark, clean them and put them into the low-temperature plasma treatment device. In a low-temperature environment of -80℃, they are treated by the low-temperature plasma treatment system, using a strong electric field of >10kV / cm to further destroy the cell wall while retaining the active ingredients. During the treatment process, the temperature and electric field strength are monitored in real time to ensure that the parameters are within the optimal range.

[0193] The raw materials treated with low-temperature plasma are placed in a vacuum freeze dryer for freeze drying. The freeze drying process temperature is -50°C to -80°C and the pressure is 10 -2 Up to 10 -3 Pa. Monitor the temperature and pressure in real time. When the moisture content of the raw material drops below 1%, take out the dried raw material. The moisture content of the dried raw material is measured to be stable at 0.8%.

[0194] The dried raw materials were crushed to a particle size of 1-10 microns using a nanomechanical ball mill, the speed of the nanomechanical ball mill was 800 rpm, and the crushing time was 4 hours. The crushing parameters were optimized by combining machine learning algorithms to obtain a powder with a uniform particle size distribution, and the final powder particle size distribution was in the range of 1-8 microns.

[0195] The crushed raw material powder is mixed with an ionic liquid-supercritical carbon dioxide mixed solvent configured at a solid-liquid ratio of 1:25, with a volume ratio of 80:20 to obtain a mixed slurry. The mixed slurry is placed in a high-frequency pulse electric field reactor, the extraction frequency is set to 50kHz, the electric field strength is 20kV / cm, the extraction temperature is 10-15°C, and the extraction time is 12 minutes. During the extraction process, the electric field strength and extraction time are monitored in real time, and the electric field parameters are dynamically adjusted using an AI algorithm to optimize the extraction efficiency. After the extraction is completed, the extract is collected for the next step of filtration and purification.

[0196] The extracted liquid is subjected to multi-stage nanofiltration through a microfluidic chip. First, an ultrafiltration membrane with a pore size of 0.001 microns is used for preliminary separation to remove large molecular impurities. Then a nanofiltration membrane with a pore size of 0.0001 microns is used for deep purification to remove small molecular impurities. The microfluidic chip system combines intelligent algorithms to monitor and optimize the flow rate and pressure during the filtration process in real time, and the purity of the final extract reaches 98%.

[0197] The purified extract was placed in a high-efficiency vacuum centrifugal concentrator for multi-stage concentration. The initial vacuum degree was 10 -2 Up to 10 -3 Pa, the temperature is controlled below 25°C, and the extract is concentrated to 1 / 100 of the original volume. During the concentration process, the AI ​​algorithm is combined to optimize the temperature and vacuum parameters. The final extract contains a high concentration of anti-wrinkle active ingredients, and its concentration is 100 times that of the original extract.

[0198] The concentrated extract was separated and purified by a bionic nanofiber membrane, and the target component was further purified using a solvent with an ethyl acetate-water volume ratio of 4:6. The purity of the final extract was increased to 99%.

[0199] High-resolution ultra-high performance liquid chromatography combined with high-precision mass spectrometry technology was used to conduct multi-dimensional molecular structure identification and quantitative analysis of the extracted anti-wrinkle active ingredients. The identification process was optimized through big data analysis to ensure the purity and effectiveness of the ingredients. Then, the extracted anti-wrinkle active ingredients were applied to the surface of the intelligent bionic skin model, and photoacoustic imaging technology was used to obtain real-time absorption and distribution data of the anti-wrinkle active ingredients in the skin. Combined with cell activity analysis and gene expression profile analysis, the promotion effect of anti-wrinkle active ingredients on skin collagen synthesis was verified.

[0200] Experimental location: Shanghai Kechuang Biotechnology Co., Ltd., Zhangjiang Hi-Tech Park, Pudong New District, Shanghai, experimental time: June 2024

[0201] Table 1: Effects of low temperature plasma treatment and vacuum freeze drying

[0202] project data Cell wall integrity before treatment (%) 95 Cell wall fragmentation rate after treatment (%) 85 Active ingredient retention rate (%) 90 Temperature(℃) -80 Electric field strength (kV / cm) >10 Moisture content before treatment (%) 70 Moisture content after treatment (%) 0.8 Drying time (hours) 24 Temperature range (℃) -50 to -80 Pressure(Pa) <![CDATA[10 -2 Up to 10 -3 ]]>

[0203] Table 2: Nanomechanical ball milling and high-frequency pulse electric field extraction effects

[0204]

[0205]

[0206] Table 3: Microfluidic chip nanofiltration and high-efficiency vacuum centrifugation concentration effects

[0207] kV / cm Project data Initial separation purity (%) 98 Purity of deep purification (%) 99 Filtering time (hours) 2 Initial separation membrane pore size (micrometer) 0.001 Deep purification membrane pore size (micrometer) 0.0001 Initial vacuum degree (Pa) <![CDATA[10 -2 Up to 10 -3 ]]> Final concentration multiple 100 times Concentration time (hours) 6 Temperature control (℃) <25

[0208] Table 4: Separation and high-resolution analysis of bionic nanofiber membranes and evaluation of smart bionic skin models

[0209] project data Separation purity (%) 99 Separation time (hours) 3 Purification solvent volume ratio (ethyl acetate-water) 4:6 Active ingredient absorption and distribution uniformity (%) 95 Cell activity enhancement rate (%) 80 Collagen synthesis enhancement rate (%) 70

[0210] It can be seen that under low-temperature plasma treatment, the cell wall integrity before treatment was 95%, the cell wall fragmentation rate after treatment was 85%, and the active ingredient retention rate was 90%. Vacuum freeze-drying effect, the moisture content before treatment was 70%, the moisture content after treatment was 0.8%, and the drying time was 24 hours. Nanomechanical ball milling effect, average particle size 5 microns, particle size distribution range 1-8 microns, crushing time 4 hours. High-frequency pulse electric field extraction effect, extraction efficiency 80%, extract purity 95%, extraction time 12 minutes. Microfluidic chip nanofiltration effect, initial separation purity 98%, deep purification purity 99%, filtration time 2 hours. High-efficiency vacuum centrifugal concentration effect, initial vacuum degree 10 -3 Pa, final concentration multiple 100 times, concentration time 6 hours. Bionic nanofiber membrane separation effect, separation purity 99%, separation time 3 hours. High-resolution analysis and intelligent bionic skin model evaluation effect, active ingredient absorption distribution uniformity 95%, cell activity improvement rate 80%, collagen synthesis improvement rate 70%

[0211] It can be seen from the above experimental data that the peach anti-wrinkle component extraction device and the extraction method of the present invention are excellent in extraction efficiency, active component retention, environmental protection and safety. Compared with the traditional extraction method, the present invention not only greatly improves the extraction efficiency and product purity, but also effectively reduces environmental pollution and operation risks, and has significant practical application value.

[0212] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for extracting anti-wrinkle components from peach, characterized in that: The steps include: S1. Select the leaves, fruits and bark of peach trees as raw materials, wash them, and treat them by low-temperature plasma in a low-temperature environment of 80°C. Use a strong electric field >10kV / cm to further destroy the cell wall while retaining the active ingredients. The low-temperature plasma system monitors the temperature and electric field strength during the treatment process in real time. S2. Place the raw material after low-temperature plasma treatment in a vacuum freeze dryer for freeze drying. Real-time monitoring of the temperature and pressure during the drying process shows that when the moisture content of the raw material drops below 1%, take out the dried raw material, crush it into particles of 1-10 microns using a nanomechanical ball mill, and optimize the crushing parameters using an optimization model based on topological data analysis and high-performance long-term coherence. S3. Mix the crushed raw material powder with ionic liquid supercritical carbon dioxide configured at a solid-liquid ratio of 1:25, and the solvent volume ratio is 80:20, and extract it in a high-frequency pulse electric field. The extraction frequency is set to 50kHz, the electric field strength is 20kV / cm, the extraction temperature is 10-15°C, and the extraction time is 10-15 minutes; the high-frequency pulse electric field is combined with ionic liquid and supercritical carbon dioxide to optimize the efficiency of cell disruption and active ingredient release. During the extraction process, an AI algorithm model based on Hamiltonian path optimization and fractal geometry is used to adjust the electric field parameters in real time to optimize the extraction efficiency; S4. The extracted extract is subjected to multi-stage nanofiltration through a microfluidic chip, and an ultrafiltration membrane with a pore size of 0.001 micron is used for preliminary separation to remove macromolecular impurities, and a nanofiltration membrane with a pore size of 0.0001 micron is used for deep purification to remove small molecular impurities. The microfluidic chip system is combined with an AI optimization algorithm model based on quantum state transfer and chaotic dynamics to monitor and optimize the flow rate and pressure during the filtration process in real time; S5. The purified extract is concentrated in multiple stages in a high-efficiency vacuum centrifugal concentrator at a low temperature of <25°C, and the extract is concentrated to 1 / 100 of the original volume by using rotary evaporation technology. During the concentration process, the temperature and vacuum parameters are optimized by using an AI optimization algorithm based on adaptive control algorithm and chaotic dynamics. The concentrated extract contains a high concentration of anti-wrinkle active ingredients. S6, separating and purifying the concentrated extract through a bionic nanofiber membrane, using ethyl acetate and water in a volume ratio of 4:6 to further purify the extract components; S7. Use high-resolution ultra-high performance liquid chromatography combined with high-precision mass spectrometry technology to conduct multi-dimensional molecular structure identification and quantitative analysis of the extracted anti-wrinkle active ingredients. Optimize the identification process through big data analysis, optimize the purity and effectiveness of the ingredients, and record and analyze data in real time during the analysis process; S8. The absorption and anti-wrinkle effects of anti-wrinkle active ingredients in simulated human skin were evaluated by combining an intelligent bionic skin model with photoacoustic imaging technology. Cell activity analysis and gene expression profile analysis were used to verify their role in promoting skin collagen synthesis. The test process was optimized using AI algorithms to test the reliability and accuracy of experimental data.

2. The method for extracting the anti-wrinkle component of peach according to claim 1, characterized in that: The S2 specifically includes: S21, placing the raw material treated with low temperature plasma in a vacuum freeze dryer for freeze drying, wherein the temperature during freeze drying is 50° C. to 80° C., and the pressure is 10 -2 Up to 10 -3 Pa, real-time monitoring of temperature and pressure during freeze drying, when the moisture content of the raw material drops below 1%, take out the dried raw material; S22, using a nanomechanical ball mill to grind the dried raw material to a particle size of 1-10 microns, the rotation speed of the nanomechanical ball mill is 500-1000 rpm, the grinding time is 2-5 hours, collecting powder samples at different time points during the grinding process, and using a dynamic light scattering instrument to measure the particle size distribution P(d) of each sample to obtain particle size distribution data; S23, the particle size distribution data P(d) is input into the optimization model based on topological data analysis and high-performance persistent coherence, and the topological feature vector T(d) is established by calculating the persistent coherence characteristics of the sample data: Among them, H i is the i-th permanent homology group, C(d) is the Simpson complex covering the sample space; S24. Analyze and process the topological feature vector T(d) obtained from the topological data analysis using a high-dimensional geometric deep learning model: Among them, T k (d) is the topological feature vector of the kth sample, is the output of the deep learning model, θ is the model parameter set, and λ is the regularization parameter; S25. Combined with the optimized high-dimensional features obtained from the geometric deep learning model, the high-dimensional features are further optimized using quantum Monte Carlo simulation in quantum many-body systems: in, is the quantum state in the Hamiltonian The expected value under m is the target energy value, and the optimized quantum features are used for the final fusion model optimization; S26. Input the optimized high-dimensional features into the optimization model based on the combination of geometric deep learning and quantum Monte Carlo simulation, and minimize the optimization objective function of the fusion model by iteratively optimizing the crushing parameters: Among them, γ is the adjustment coefficient, and the optimization of this objective function is used to update the adaptive gradient descent algorithm; S27, based on the optimization objective function The feedback of is used to update the crushing parameters using the adaptive gradient descent algorithm: Among them, η is the learning rate, G t is the sum of squared gradients in the past, ∈ is the smoothing parameter, and the updated crushing parameters are used to monitor and adjust the operating parameters in real time; S28. After each iteration, the particle size distribution P(d) is monitored in real time, and the operating parameters, rotation speed and crushing time of the nanomechanical ball mill are adjusted according to the feedback of the optimization model until the objective function is optimized. Converge to the preset threshold and obtain the final optimized crushing parameters.

3. The method for extracting the anti-wrinkle component of peach according to claim 1, characterized in that: The S3 specifically includes: S31, mixing the crushed raw material powder with an ionic liquid supercritical carbon dioxide mixed solvent configured at a solid-liquid ratio of 1:25 in a volume ratio of 80:20 to obtain a mixed slurry; S32, placing the mixed slurry in a high-frequency pulse electric field reactor, setting the extraction frequency to 50kHz, the electric field strength to 20kV / cm, extracting in the high-frequency pulse electric field reactor, controlling the extraction temperature at 10-15°C, and setting the extraction time to 10-15 minutes; S33, during the extraction process, the electric field intensity E in the high-frequency pulse electric field reactor is monitored in real time by real-time monitoring of the electric field intensity and extraction time. i and extraction time t j , using electric field strength sensors and time recorders to record data; S34, real-time monitoring data E i and t j The input is fed into the AI ​​algorithm model based on Hamiltonian path optimization and fractal geometry, which uses the fusion objective function for optimization: in, represents the Hamiltonian path length, E i is the electric field strength, t j is the extraction time, t opt To optimize the extraction time, N is the number of electric field intensity samples, M is the number of time samples, and β is the regularization parameter. The electric field parameters are adjusted through this optimization objective function; S35. According to the fusion objective function The electric field strength and extraction time of the high-frequency pulse electric field reactor are adjusted in real time through the feedback loop according to the monitored electric field strength E i and extraction time t j , the system automatically adjusts these parameters for optimization; S36. During the adjustment process, the optimization parameters are updated using an adaptive gradient descent algorithm based on Adamak surface optimization: Among them, θ is the optimization parameter set, η is the learning rate, γ is the high-order derivative adjustment coefficient, is the gradient of the objective function, Δ Had is the Laplace operator of the Adamak surface, h(θ) is the metric tensor, and the electric field intensity and extraction time are optimized by adjusting the optimization parameter θ; S37, after each extraction process is completed, record and analyze the data of electric field strength and extraction time, and use these data to update the optimization algorithm model; S38, looping through steps S33-S37 until the optimization parameter θ of the electric field intensity and the extraction time in the extraction process converges to a preset threshold, and continuously optimizing the extraction efficiency and the stability of the active ingredient through continuous looping and adjustment; S39, after the extraction is completed, the extract is taken out from the high-frequency pulse electric field reactor, and is initially separated using a centrifugal separation device to separate the liquid portion as the extract; S310, cooling the extract to reduce the temperature to below 5°C to stabilize the active ingredients. The cooled extract is used for subsequent filtration and purification steps.

4. The method for extracting anti-wrinkle ingredients from peach according to claim 1, characterized in that: The S5 specifically includes: S51, place the purified extract in a high-efficiency vacuum centrifugal concentrator and set the initial vacuum degree to 10 2 Up to 10 3 Pa, the temperature was controlled below 25°C, and the high-efficiency vacuum centrifugal concentrator was started for preliminary concentration. The extract was concentrated to 1 / 10 of the original volume under low temperature conditions using rotary evaporation technology, and the temperature and vacuum degree were monitored in real time during the process; S52, the extract after preliminary concentration is transferred to the second stage vacuum centrifugal concentrator, and the vacuum degree is set to 10 4 Pa, continue to concentrate to 1 / 50 of the original volume; S53. Using AI optimization algorithm model, real-time monitoring of vacuum degree P(t) and concentrated liquid volume V(t) is performed during the concentration process, and data is obtained using vacuum sensors and liquid level sensors; S54. Input the real-time monitoring data P(t) and V(t) into the AI ​​optimization algorithm model based on quantum state transfer and chaotic dynamics: Among them, |ψ(P(t i ))| 2 represents the quantum state probability amplitude of the vacuum degree, represents the quantum state probability amplitude of the concentrated liquid volume, P(t) is the vacuum degree, V(t) is the concentrated liquid volume, α is the adjustment coefficient, V target is the target concentration volume, γ is the regularization parameter, T is the number of samples at the vacuum time point, and M is the number of samples at the volume time point; S55. Calculate the gradient of the objective function using an adaptive control algorithm based on chaos mapping and fractal geometry The gradient calculation formula is: Among them, θ is the control parameter set, including vacuum degree and temperature control parameters; S56, iteratively updating the control parameters through the adaptive control algorithm, the updating formula is: Among them, η is the learning rate, λ is the chaotic dynamics adjustment coefficient, Δ Fractal represents the Laplace operator of fractal geometry, F(θ) is the fractal metric tensor; S57, during the concentration process, the vacuum degree and temperature parameters are adjusted in real time, and the objective function is optimized according to the feedback loop so that the volume of the concentrated liquid gradually reaches the target volume V target ; S58. When optimizing the objective function When the vacuum and temperature control parameters converge to the preset threshold, the final vacuum and temperature control parameters are recorded and saved. The vacuum and temperature parameters are adjusted in real time through the feedback loop. S59. When the volume of the extract reaches the target concentrated volume, stop the vacuum centrifugal concentrator to collect the concentrated high-concentration anti-wrinkle active ingredients.

5. The method for extracting anti-wrinkle ingredients from peach according to claim 1, characterized in that: The S8 specifically includes: S81, applying the extracted anti-wrinkle active ingredients to the surface of the intelligent bionic skin model, where the bionic skin model has similar structure and physiological properties to human skin; S82. Use photoacoustic imaging technology to monitor the bionic skin model and obtain the absorption distribution data of the anti-wrinkle active ingredient in the skin in real time, wherein the absorption distribution data is represented by the photoacoustic signal intensity A(t,x,y,z), where t is time, and x, y and z are spatial coordinates; S83, input the photoacoustic signal intensity A(t,x,y,z) into a deep learning algorithm based on topological data analysis (TDA) and singular value decomposition (SVD) to extract the topological feature (T(A), the calculation formula of which is: Among them, σ k represents singular value, β k represents the Betti number of the k-th homology group; S84. The activity of cells in the bionic skin model is detected using a cell activity analyzer. The cell activity is represented by the Fermi-Dirac distribution function f(E, t): Where E is energy, μ(t) is chemical potential, k is Boltzmann constant, and T is absolute temperature; S85. Perform gene expression spectrum analysis, analyze gene expression levels through multi-body wave functions, and express gene expression levels with quantum multi-body states Ψ(g, t), where g is a gene identifier and t is time. The calculation formula of quantum multi-body states is: Among them, c i (t) is the time-dependent coefficient, is the ground state wave function of the gene; S86. The topological features T(A), the Fermi-Dirac distribution of cell activity f(E,t) and the quantum multi-body state Ψ(g,t) of gene expression levels were input into a hybrid model based on high-dimensional geometric deep learning and variational quantum eigensolver to evaluate the effect of anti-wrinkle active ingredients on skin collagen synthesis: Among them, γ, λ and ν are adjustment coefficients, <Ψ k |H|Ψ k > is the expected value of the multi-body state, E k is the corresponding energy level, f target For the target Fermi-Dirac distribution, N and M are the number of time samples, respectively, and P is the number of gene samples; S87. Based on the evaluation results, optimize the formulation of the anti-wrinkle active ingredients and optimize their absorption and anti-wrinkle effects in simulated human skin; S88, loop through the above steps until the objective function is optimized. Converge to a preset threshold.

6. The device for extracting anti-wrinkle components from peach according to claim 1, characterized in that: The device specifically comprises: Low-temperature plasma treatment unit, including a low-temperature plasma generator and a strong electric field generator, is used to treat the raw materials in a low-temperature environment of 80°C to further destroy the cell wall and retain the active ingredients. The low-temperature plasma system monitors the temperature and electric field strength during the treatment process in real time; The vacuum freeze drying unit includes a vacuum freeze dryer for freeze drying the raw material after low temperature plasma treatment. The temperature during freeze drying is 50°C to 80°C and the pressure is 10 -2 Up to 10 -3 Pa, real-time monitoring of temperature and pressure during freeze drying, when the moisture content of the raw material drops below 1%, take out the dried raw material; A nanomechanical ball mill unit, comprising a nanomechanical ball mill, for crushing the dried raw material into a particle size of 1-10 microns, the rotation speed of the nanomechanical ball mill is 500-1000 rpm, the crushing time is 2-5 hours, the crushing parameters are optimized in combination with a machine learning algorithm, and the crushing process is controlled using the optimized crushing parameters to obtain a powder with uniform particle size distribution; The high-frequency pulse electric field extraction unit includes a high-frequency pulse electric field reactor, which is used to mix and extract the crushed raw material powder with an ionic liquid supercritical carbon dioxide mixed solvent. The extraction frequency is set to 50kHz, the electric field strength is 20kV / cm, the extraction temperature is controlled at 10-15°C, and the extraction time is set to 10-15 minutes. The AI ​​algorithm adjusts the electric field strength and extraction time in real time to optimize the extraction efficiency; The microfluidic chip filtration unit includes a microfluidic chip system for multi-stage nanofiltration of the extracted extract, with an ultrafiltration membrane with a pore size of 0.001 micron used for preliminary separation and a nanofiltration membrane with a pore size of 0.0001 micron used for deep purification. The microfluidic chip system is combined with an intelligent algorithm to monitor and optimize the flow rate and pressure during the filtration process in real time; The high-efficiency vacuum centrifugal concentration unit includes a high-efficiency vacuum centrifugal concentrator for multi-stage concentration of the purified extract, with an initial vacuum degree of 10 -2 Up to 10 -3 Pa, the temperature is controlled below 25°C, the extract is concentrated to 1 / 100 of the original volume, and the AI ​​algorithm optimizes the temperature and vacuum parameters during the concentration process; A biomimetic nanofiber membrane separation unit, including a biomimetic nanofiber membrane system, is used to separate and purify the concentrated extract, and further purify the target component using a solvent with a volume ratio of ethyl acetate to water of 4:6; High-resolution analysis unit, including a high-resolution ultra-high-performance liquid chromatography and high-precision mass spectrometry system, for multi-dimensional molecular structure identification and quantitative analysis of extracted anti-wrinkle active ingredients, big data analysis to optimize the identification process, and real-time recording and analysis of data; The intelligent bionic skin model evaluation unit includes an intelligent bionic skin model and a photoacoustic imaging system, which are used to evaluate the absorption and anti-wrinkle effects of anti-wrinkle active ingredients in simulated human skin. Cell activity analysis and gene expression profile analysis verify the promoting effect of anti-wrinkle active ingredients on skin collagen synthesis, and combine AI algorithms to optimize the test process.

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