A manufacturing system for enhancing the shelf stability of probiotic bacteria in dairy products

Abstract

This invention relates to the field of probiotic viability maintenance and fermentation engineering technology, and particularly to a preparation system for improving the storage stability of probiotics in dairy products. The system includes a probe labeling device, a fluid granulation device, a liquid nitrogen quenching-associated ultrasonic device, and a spectral detection device, all connected in sequence. The control device receives photoelectric signals through an acquisition module and converts them into a continuous spectral sequence, which is then sent to an evaluation module. The evaluation module calculates the habitat micro-indices and pushes them to a control module. Based on the viability comparison results, the control module calculates the target value of the shell crystallization density and the ultrasonic modulation command, which is then converted by the drive component into pumping cooling commands and frequency adjustment commands, respectively, and sent to the fluid granulation device and the liquid nitrogen quenching-associated ultrasonic device to perform physical compensation. This invention solves the problems of probiotics being susceptible to thermal and oxidative stress during processing and storage, leading to inactivation, and the insufficient stability of the microcapsule structure.

Description

Technical Field

[0001] This invention relates to the field of probiotic viability maintenance and fermentation engineering technology, and particularly to a preparation system for improving the storage stability of probiotics in dairy products. Background Technology

[0002] Probiotics, as live microorganisms that are beneficial to the health of the host, are often added to dairy products such as yogurt. The proteins, fats and sugars in dairy products constitute the microbial growth substrate. Storage stability describes the ability of probiotics to maintain a high number of viable bacteria and metabolic activity during storage. The storage stability is affected by factors such as temperature fluctuations, pH changes, oxygen permeation and packaging material characteristics. By managing storage conditions, activity can be maintained, thereby promoting the extension of product shelf life.

[0003] Current probiotic microencapsulation technology faces several challenges: the frequent high-temperature sterilization processes and the accumulation of endogenous organic acids during fermentation in dairy production expose probiotic strains to severe heat and osmotic stress, leading to lipid peroxidation of cell membranes and protein denaturation. While microencapsulation can mitigate the impact of external environmental factors on live bacteria by creating physical barriers, in practical applications, microcapsule wall materials often struggle to balance density and flexibility. This can cause structural embrittlement and lysis under dairy filling pressure or long-term acidic storage conditions, resulting in the loss of an effective barrier for the core live bacteria and accelerated apoptosis. For example, in the preparation of room-temperature fermented milk, if the protective layer cannot resist the chemical corrosion caused by the continuous increase in acidity, the probiotics inside the microcapsules may completely lose their metabolic activity due to hydrogen ion penetration into the cells. Ultimately, this results in the product failing to provide sufficient functional live bacteria by the end of its shelf life, severely weakening the health benefits of dairy products. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a preparation system for improving the storage stability of probiotics in dairy products. This invention solves the technical problems that probiotics are susceptible to physical and chemical stresses such as high-temperature instantaneous sterilization, drastic fluctuations in environmental acidity, and oxidative stress during dairy product processing and storage, resulting in the inactivation of a large number of microencapsulated core live bacteria, insufficient physical stability of the microcapsule protective layer structure, and difficulty in achieving the required number of functional live bacteria during the product's shelf life.

[0005] This invention dynamically adjusts the degree of crystallization densification of microcapsule shells and acoustic field intervention parameters through probe labeling, online spectral detection, habitat micro-index assessment, liquid nitrogen quenching and ultrasonic standing wave synergistic regulation, and closed-loop calibration control, thereby improving the structural stability of microcapsule shells and enhancing the survival rate and metabolic activity of probiotics during dairy product storage.

[0006] To solve the above-mentioned technical problems, the specific contents of the present invention are as follows: This invention provides a preparation system for improving the storage stability of probiotics in dairy products, comprising an apparatus and a control device communicatively connected to the apparatus, the control device being used to control the apparatus; the apparatus includes a probe labeling device, a fluid granulation device, a liquid nitrogen quenching-associated ultrasonic device, and a spectral detection device located at the output end of the liquid nitrogen quenching-associated ultrasonic device, connected in sequence; the control device includes an acquisition module, an evaluation module, a regulation module, and a drive component; The acquisition module is used to receive the photoelectric signal sent by the spectral detection device, convert the photoelectric signal into a continuous spectral sequence, and transfer the continuous spectral sequence to the evaluation module; The evaluation module is used to receive the continuous spectral sequence, extract spectral data within the continuous spectral sequence, convert the spectral data into a habitat micro-index, and transfer the habitat micro-index to the regulation module. The control module is used to receive the habitat micro-index, compare the habitat micro-index with a preset survival threshold to generate a survival comparison result, calculate the target value of shell crystallization density and the ultrasonic modulation command based on the survival comparison result, and transfer the target value of shell crystallization density and the ultrasonic modulation command to the drive component. The drive component is configured to receive the target value of shell crystallization density and the ultrasonic modulation command, convert the target value of shell crystallization density into a pumping cooling command, convert the ultrasonic modulation command into a frequency adjustment command, send the pumping cooling command to the fluid granulation equipment, and send the frequency adjustment command to the liquid nitrogen quenching associated ultrasonic equipment.

[0007] Furthermore, the preparation system for improving the storage stability of probiotics in dairy products according to the present invention includes a probe labeling device comprising a dual-staining traceability device and a fluorescent pre-staining device connected in sequence; the dual-staining traceability device receives a probiotic solution and a dichlorofluorescein diacetate probe, mixes the probiotic solution and the dichlorofluorescein diacetate probe to generate a first labeling solution, and delivers the first labeling solution to the fluorescent pre-staining device; the fluorescent pre-staining device receives the first labeling solution and a trimethylaminodiphenylhexane probe, mixes the first labeling solution and the trimethylaminodiphenylhexane probe to generate a dual-labeling solution, and delivers the dual-labeling solution to the fluid granulation device.

[0008] Furthermore, the preparation system for improving the storage stability of probiotics in dairy products according to the present invention includes a fluid granulation device comprising a multiphase emulsification device and an electro-injection microfluidic device connected to the multiphase emulsification device. The multiphase emulsification device includes a twin-screw extruder, and the electro-injection microfluidic device includes a coaxial electrostatic nozzle. The multiphase emulsification device receives an aqueous solution of sodium alginate and hydrogenated palm oil. In some embodiments, the mass fraction of the aqueous solution of sodium alginate is 1.5% to 3.0%, the mass ratio of hydrogenated palm oil to the aqueous solution of sodium alginate is 1:(1 to 4), and the amount of polyglycerol polyricinoleate added as an emulsifier is 0.5% to 5.0% of the oil phase mass. The shear rate of the twin-screw extruder is preferably 2000–5000 rpm, and the operating voltage of the coaxial electrostatic nozzle is preferably 10–20 kV. The twin-screw extruder is used to melt and mix the sodium alginate aqueous solution and the hydrogenated palm oil to generate a water-in-oil-in-water composite wall material liquid. The water-in-oil-in-water composite wall material liquid is then transported to the coaxial electrostatic nozzle. The coaxial electrostatic nozzle receives the dual-labeling liquid and the water-in-oil-in-water composite wall material liquid, generating a coaxial electrostatic field. The coaxial electrostatic field is used to encapsulate the dual-labeling liquid inside the water-in-oil-in-water composite wall material liquid to generate primary microcapsules. The primary microcapsules are then transported to the liquid nitrogen quenching associated ultrasonic equipment.

[0009] Furthermore, the preparation system for improving the storage stability of probiotics in dairy products according to the present invention includes a liquid nitrogen quenching-associated ultrasonic device comprising a rapid quenching device and an ultrasonic standing wave device arranged inside the rapid quenching device; the rapid quenching device receives the primary microcapsules and liquid nitrogen, and contacts the liquid nitrogen with the primary microcapsules, causing the hydrogenated palm oil in the water-in-oil-in-water composite wall material liquid contained in the primary microcapsules to undergo phase change crystallization to form porous framework microcapsules; the ultrasonic standing wave device includes a piezoelectric ceramic transducer array, which is orthogonally arranged; the piezoelectric ceramic transducer array emits ultrasonic standing waves towards the porous framework microcapsules, and the ultrasonic standing waves generate standing wave node acoustic radiation force; the ultrasonic standing wave device uses the standing wave node acoustic radiation force to drive the hydrogenated palm oil in the water-in-oil-in-water composite wall material liquid contained in the porous framework microcapsules to undergo lattice rearrangement to form protective microcapsules, and the protective microcapsules are transported to the spectroscopic detection device.

[0010] Furthermore, in the preparation system for improving the storage stability of probiotics in dairy products according to the present invention, the evaluation module includes a polarity resolution module and a reactive oxygen species (ROS) resolution module; the acquisition module receives the photoelectric signal, calculates the photoelectric signal using a Kalman filter algorithm to generate a continuous spectral sequence, and transfers the continuous spectral sequence to the polarity resolution module and the ROS resolution module respectively; the polarity resolution module receives the continuous spectral sequence, extracts the parallel polarized light intensity analog signal and the vertical polarized light intensity analog signal within the continuous spectral sequence, calculates the first difference between the parallel polarized light intensity analog signal and the vertical polarized light intensity analog signal, calculates the first sum between the parallel polarized light intensity analog signal and the vertical polarized light intensity analog signal, divides the first difference by the first sum to generate a polarization degree value, and calculates the cell membrane fluidity micro-index based on the polarization degree value.

[0011] Furthermore, in the preparation system for improving the storage stability of probiotics in dairy products according to the present invention, the reactive oxygen species analysis module receives the continuous spectral sequence, extracts the peak area data of the secondary fluorescence emission spectrum within the continuous spectral sequence, and performs discrete integration calculation on the peak area data of the secondary fluorescence emission spectrum to generate an oxygen free radical accumulation index; the evaluation module extracts the cell membrane fluidity micro-index and the oxygen free radical accumulation index, performs data splicing of the cell membrane fluidity micro-index and the oxygen free radical accumulation index to generate a habitat micro-index, and transfers the habitat micro-index to the regulation module.

[0012] Furthermore, in the preparation system for improving the storage stability of probiotics in dairy products according to the present invention, the control module includes a lattice rearrangement decision unit and a phase transition decision unit. The lattice rearrangement decision unit receives the cell membrane fluidity micro-index and the oxygen free radical accumulation index, compares the cell membrane fluidity micro-index with a preset membrane threshold to generate a first comparison result, compares the oxygen free radical accumulation index with a preset oxygen threshold to generate a second comparison result, extracts the acoustic duty cycle parameter and the acoustic field frequency band parameter from a preset multidimensional situational awareness data table based on the first comparison result and the second comparison result, generates an ultrasonic modulation command based on the acoustic field frequency band parameter and the acoustic duty cycle parameter, and transfers the ultrasonic modulation command to the driving component. The phase transition decision unit receives the cell membrane fluidity micro-index, which is included in the habitat micro-index, compares the cell membrane fluidity micro-index with a preset survival threshold to generate a third comparison result, calculates the target value of the shell crystallization density based on the third comparison result, and transfers the target value of the shell crystallization density to the driving component.

[0013] Furthermore, in the preparation system for improving the storage stability of probiotics in dairy products according to the present invention, the driving component includes an acoustic field driving unit and an industrial control execution unit, and the high-speed quenching equipment includes a micro-flow guiding valve; the acoustic field driving unit receives the ultrasonic modulation command, generates a frequency adjustment command based on the ultrasonic modulation command, and sends the frequency adjustment command to the piezoelectric ceramic transducer array; the industrial control execution unit receives the target value of shell crystallization density, generates a pumping cooling command based on the target value of shell crystallization density, and sends the pumping cooling command to the micro-flow guiding valve and the twin-screw extruder respectively.

[0014] Furthermore, in the preparation system for improving the storage stability of probiotics in dairy products according to the present invention, the control device includes a closed-loop calibration module, and the rapid quenching equipment includes a temperature measuring element; the industrial control execution unit collects the electrical frequency response characteristic data of the micro-flow guide valve and the twin-screw extruder, and sends the electrical frequency response characteristic data to the closed-loop calibration module; the temperature measuring element collects cooling slope data and sends the cooling slope data to the closed-loop calibration module; the closed-loop calibration module receives the cooling slope data, calculates the deviation value between the cooling slope data and a preset thermodynamic slope threshold, calculates and generates a Kalman gain damping coefficient based on the deviation value, and sends the Kalman gain damping coefficient to the polarity analysis module; the polarity analysis module receives the Kalman gain damping coefficient and uses the Kalman gain damping coefficient to calculate and process the continuous spectral sequence.

[0015] Furthermore, in the preparation system for improving the storage stability of probiotics in dairy products described in this invention, the closed-loop calibration module collects acoustic impedance attenuation characteristic data generated by the porous framework microcapsules passing through the piezoelectric ceramic transducer array, extracts crystal density data from the acoustic impedance attenuation characteristic data, compares the crystal density data with a preset lattice standard value to generate a fourth comparison result, calculates frequency drift compensation data based on the fourth comparison result, and sends the frequency drift compensation data to the lattice rearrangement decision unit. The lattice rearrangement decision unit receives the frequency drift compensation data and uses the frequency drift compensation data to calculate and generate sound field frequency band parameters.

[0016] Beneficial effects of this invention: This invention provides a preparation system for improving the storage stability of probiotics in dairy products. It employs a probe labeling device to perform dual molecular labeling on the probiotic liquid, and combines this with a spectroscopic detection device and acquisition module to acquire photoelectric signals in real time and reconstruct them into a continuous spectral sequence. This establishes a microscopic sensing basis for the physiological stress state of probiotics, enabling the system to quantify the degree of thermal stress and oxidative damage to probiotics during dairy processing. The evaluation module generates a habitat micro-indices by calculating the cell membrane fluidity micro-indices and oxygen free radical accumulation indices, providing a basis for subsequent process compensation decisions. The control module generates a target value for shell crystallization density and ultrasonic modulation commands based on survival comparison results. These commands are converted from driving components into pumping cooling commands and frequency adjustment commands, directly intervening in the operating parameters of the fluid granulation equipment and the liquid nitrogen quenching-related ultrasonic equipment. The liquid nitrogen quenching-related ultrasonic equipment utilizes the acoustic radiation force of the standing wave nodes generated by the ultrasonic standing waves to drive lattice rearrangement of the lipid phase inside the porous microcapsules, helping to bridge the micropores generated by the cryogenic phase transition and improve the structural density of the microcapsule protective layer. In some embodiments, by comparing the protective microcapsules formed using the preparation system of the present invention with the control group without closed-loop control, it can be observed that the experimental group has a higher number of viable bacteria at the end of the shelf life, a lower microcapsule rupture rate, and a higher shell crystallization density under the same storage conditions, thereby demonstrating that the present invention helps to improve the storage stability of probiotics in dairy products. Attached Figure Description

[0017] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on the drawings without creative effort.

[0018] Figure 1 This is a system architecture diagram of a preparation system for improving the storage stability of probiotics in dairy products according to the present invention. Detailed Implementation

[0019] To make the technical solution of the present invention clearer, the present invention will be clearly and completely described below with reference to specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. The present invention provided by various embodiments will be described in detail below with reference to the accompanying drawings. To better understand the purpose of the present invention, the present invention will be described in further detail below.

[0020] Please see Figure 1This invention provides a preparation system for improving the storage stability of probiotics in dairy products, comprising an equipment and a control device communicatively connected to the equipment, the control device being used to control the equipment; the equipment includes a probe labeling device, a fluid granulation device, a liquid nitrogen quenching-associated ultrasonic device, and a spectral detection device located at the output end of the liquid nitrogen quenching-associated ultrasonic device, connected in sequence; the control device includes an acquisition module, an evaluation module, a regulation module, and a drive component; The acquisition module is used to receive the photoelectric signal sent by the spectral detection device, convert the photoelectric signal into a continuous spectral sequence, and transfer the continuous spectral sequence to the evaluation module; The evaluation module is used to receive the continuous spectral sequence, extract spectral data within the continuous spectral sequence, convert the spectral data into a habitat micro-index, and transfer the habitat micro-index to the regulation module. The control module is used to receive the habitat micro-index, compare the habitat micro-index with a preset survival threshold to generate a survival comparison result, calculate the target value of shell crystallization density and the ultrasonic modulation command based on the survival comparison result, and transfer the target value of shell crystallization density and the ultrasonic modulation command to the drive component. The drive component is configured to receive the target value of shell crystallization density and the ultrasonic modulation command, convert the target value of shell crystallization density into a pumping cooling command, convert the ultrasonic modulation command into a frequency adjustment command, send the pumping cooling command to the fluid granulation equipment, and send the frequency adjustment command to the liquid nitrogen quenching associated ultrasonic equipment.

[0021] The preparation system relies on the coordinated operation of equipment and control devices to address the physicochemical stresses posed by the dairy processing environment. Due to the frequent high-temperature instantaneous sterilization processes and the accumulation of endogenous organic acids during fermentation in dairy production, the harsh environment exposes probiotic strains directly to severe heat and osmotic stress. The research team integrated and modified a sequentially connected probe labeling device, a fluid granulation device, a liquid nitrogen quenching-linked ultrasonic device, and a spectroscopic detection device. The probe labeling device is responsible for establishing physiological state tracking anchors before microorganisms enter the high-temperature processing environment. Internally, the probe labeling device includes a sequentially connected dual-staining tracer and a fluorescent pre-staining device. The dual-staining tracer receives the probiotic solution and a dichlorofluorescein diacetate probe, mixing them to generate the first labeling solution. The dichlorofluorescein diacetate probe can penetrate the cell wall and chemically bind with endogenous reactive oxygen species, causing the first labeling solution to carry the internal oxidative stress state markers to the fluorescent pre-staining device. The fluorescent pre-staining device receives a first labeling solution and a trimethylaminodiphenylhexane probe, and mixes the first labeling solution with the trimethylaminodiphenylhexane probe to generate a dual-labeling solution. The trimethylaminodiphenylhexane probe specifically embeds into the hydrophobic region of the lipid bilayer to reflect the cell membrane damage. The fluorescent pre-staining device then delivers the dual-labeling solution, which has completed molecular-level tracking and deployment, to the downstream fluid granulation device.

[0022] The fluid granulation equipment is responsible for constructing a physical defense barrier against the corrosive effects of the external lactic acid environment. The equipment includes a multiphase emulsification unit and an electro-injection microfluidic unit connected to the multiphase emulsification unit. The multiphase emulsification unit is equipped with a twin-screw extruder, and the electro-injection microfluidic unit is equipped with a coaxial electrostatic nozzle. The multiphase emulsification unit receives sodium alginate aqueous solution and hydrogenated palm oil. Using the mechanical shear force provided by the twin-screw extruder, the sodium alginate aqueous solution and hydrogenated palm oil are melted and mixed to generate a water-in-oil-in-water composite wall material liquid. This causes the water-in-oil-in-water composite wall material liquid to form an alternating nested phase state of an outer hydrophilic layer and an inner hydrophobic layer. The multiphase emulsification unit pressurizes and delivers the water-in-oil-in-water composite wall material liquid to the coaxial electrostatic nozzle. The coaxial electrostatic nozzle simultaneously receives the dual-labeling liquid and the water-in-oil-in-water composite wall material liquid, generating a coaxial electrostatic field at the nozzle tip where the inner and outer fluids meet. The coaxial electrostatic field force overcomes the physical tension of the liquid surface and encapsulates the dual-labeled liquid inside the water-in-oil-in-water composite wall material liquid to generate primary microcapsules. The fluid granulation equipment uses gravity sedimentation to transport the primary microcapsules to the liquid nitrogen quenching associated ultrasonic equipment below.

[0023] The liquid nitrogen quenching-associated ultrasonic equipment integrates cryogenic thermodynamics and acoustic kinetic energy for microcapsule solidification and molding. This equipment integrates a rapid quenching device and an ultrasonic standing wave device arranged within the rapid quenching device. The rapid quenching device receives primary microcapsules and liquid nitrogen, directly contacting the liquid nitrogen with the primary microcapsules to establish an ultra-low temperature cryogenic bath. The liquid nitrogen forces the hydrogenated palm oil in the water-in-oil-in-water composite wall material liquid contained within the primary microcapsules to undergo a transient phase change crystallization, forming porous framework microcapsules. The lipid crystallization boundaries formed by conventional natural cooling rates are often accompanied by microscopic stress crack defects. The ultrasonic standing wave device introduces an acoustic intervention component, including a piezoelectric ceramic transducer array, to address these microscopic stress crack defects. The piezoelectric ceramic transducer array is orthogonally arranged around the cooling bath, emitting high-frequency penetrating ultrasonic standing waves into the suspended porous framework microcapsules, generating nodal acoustic radiation forces in the form of node intersections within the porous framework microcapsules. The ultrasonic standing wave device utilizes the mechanical squeezing effect generated by the acoustic radiation force of the standing wave node to drive the hydrogenated palm oil in the water-in-oil-in-water composite wall material liquid inside the porous skeleton microcapsule to undergo lattice rearrangement to generate protective microcapsules. The liquid nitrogen quenching associated ultrasonic device transports the protective microcapsules to the spectral detection device along the bottom discharge pipeline.

[0024] The control device takes over the data communication network of the underlying equipment and establishes a closed loop for bioelectric signal feedback. A spectroscopic detection device is fixedly installed outside the fluid output pipeline, continuously irradiating through protective microcapsules. It continuously captures the weak fluorescent photons emitted by excited live bacteria at a preset microsecond sampling frequency, generating raw photoelectric signals with uniform timestamps for subsequent strict alignment of multidimensional data within the same period. The control device internally includes an acquisition module, an evaluation module, a control module, and a drive component. The acquisition module receives the photoelectric signals sent by the spectroscopic detection device and uses an embedded Kalman filter algorithm to calculate and generate a continuous spectral sequence. The Kalman filter algorithm directly filters out the viscous matrix of the dairy products and background dispersion noise caused by air bubbles in the delivery pipeline. The acquisition module then transfers the purified and recombined continuous spectral sequence to the polarization analysis module and the reactive oxygen species analysis module under the evaluation module. The polarization analysis module receives the continuous spectral sequence and initiates feature extraction operations in the polarization optical dimension, extracting the parallel polarization intensity analog signals and the vertical polarization intensity analog signals within the continuous spectral sequence. The polarity analysis module calculates the first difference between the parallel polarized light intensity simulation signal and the vertical polarized light intensity simulation signal, and simultaneously calculates the first sum of the parallel polarized light intensity simulation signal and the vertical polarized light intensity simulation signal. The first difference is divided by the first sum to generate the polarization degree value. The polarity analysis module then substitutes the polarization degree value into the pre-stored biophysical mapping formula to calculate and generate the cell membrane fluidity micro-index.

[0025] The reactive oxygen species (ROS) analysis module processes data transformation related to intracellular chemical stress states in parallel. It receives continuous spectral sequences and extracts secondary fluorescence emission spectrum peak area data, characterizing the intensity of cellular redox reactions. The module then performs discrete integral calculations in the time domain to generate an oxygen free radical accumulation index. The evaluation module coordinates the computational progress of the underlying analysis unit and extracts both the cell membrane fluidity micro-index and the oxygen free radical accumulation index. It then performs multi-dimensional matrix concatenation calculations to generate a habitat micro-index. In this invention, the data concatenation calculation preferably includes first aligning the cell membrane fluidity micro-index and the oxygen free radical accumulation index within the same period, normalizing them, and then performing matrix concatenation. Finally, it performs a weighted fusion calculation based on preset weights to obtain the habitat micro-index. In other words, the data concatenation is a pre-processing step for the weighted fusion calculation, and the weighted fusion calculation is the preferred method for generating the habitat micro-index. The evaluation module then transfers the habitat micro-index to the control module via a high-speed communication interface for strategy decision-making.

[0026] The regulation module constructs a dual-parallel intervention decision model to cope with complex processing stress environments. The regulation module is divided into a lattice rearrangement decision unit and a phase transition decision unit. The lattice rearrangement decision unit receives the cell membrane fluidity micro-index and the oxygen free radical accumulation index, compares the cell membrane fluidity micro-index with a preset membrane threshold to generate a first comparison result, and simultaneously compares the oxygen free radical accumulation index with a preset oxygen threshold to generate a second comparison result. Based on the first and second comparison results, the lattice rearrangement decision unit extracts the acoustic duty cycle parameter and acoustic field frequency band parameter from a preset multidimensional situational awareness data table. The multidimensional situational awareness data table includes a membrane fluidity interval field, an oxygen free radical accumulation interval field, a recommended duty cycle field, and a recommended acoustic field frequency band field. This data table is obtained through pre-experiments. When both the cell membrane fluidity micro-index and the oxygen free radical accumulation index increase, it is recommended to increase the duty cycle and perform acoustic field frequency band fine-tuning to enhance the lattice rearrangement effect. Based on the acoustic field frequency band parameter and the acoustic duty cycle parameter, an ultrasonic modulation command is compiled and transmitted to the driving component. The phase transition decision unit receives the cell membrane fluidity micro-index, which is included in the habitat micro-indices. It compares the cell membrane fluidity micro-index with the preset survival threshold in the pre-set standard library to generate a third comparison result. Based on the third comparison result, it derives and calculates the target value of shell crystallization density that meets the current physical defense requirements. The phase transition decision unit then transfers the target value of shell crystallization density to the drive component through the internal data bus.

[0027] The drive component translates digital logic instructions into the execution actions of the engineering physical equipment. Internally, the drive component integrates a sound field drive unit and an industrial control execution unit. The high-speed quenching equipment is equipped with a micro-flow guide valve to control the liquid nitrogen flow rate. The sound field drive unit receives digital ultrasonic modulation instructions and calls the radio frequency amplification circuit to generate a frequency adjustment instruction in the form of a high-frequency alternating current based on the ultrasonic modulation instructions. This frequency adjustment instruction is sent to the piezoelectric ceramic transducer array, causing the piezoelectric ceramic transducer array to instantly change its mechanical oscillation frequency and adjust the position of the spatial standing wave node. The industrial control execution unit receives the target value of the shell crystallization density and performs digital-to-analog conversion calculations to generate an analog signal-based pumping cooling capacity instruction based on the target value. The industrial control execution unit sends the pumping cooling capacity instruction to the micro-flow guide valve and the twin-screw extruder. The micro-flow guide valve adjusts its opening and closing amplitude according to the pumping cooling capacity instruction to control the liquid nitrogen injection flow rate. The twin-screw extruder changes its motor speed according to the pumping cooling capacity instruction to adjust the liposome melt extrusion ratio in the composite wall material.

[0028] The control device establishes a closed-loop calibration module to prevent mechanical response delay errors in industrial production environments. Temperature sensing elements are pre-embedded inside the rapid quenching equipment to monitor temperature changes in the cryogenic bath. The industrial control execution unit collects electrical frequency response characteristic data of the micro-flow guiding valve and the twin-screw extruder during operation. This electrical frequency response characteristic data specifically includes the operating current fluctuation sequence of the drive motor and the control voltage feedback sequence of the servo valve. This data is sent to the closed-loop calibration module to establish an action response benchmark file. The temperature sensing element collects actual cooling slope data inside the quenching bath and sends this data to the closed-loop calibration module. The closed-loop calibration module receives the cooling slope data and uses a thermodynamic analysis comparison algorithm to calculate the deviation between the cooling slope data and a preset thermodynamic slope threshold. This preset thermodynamic slope threshold is obtained through preliminary experiments on the cooling curves of the target composite wall material liquid under different liquid nitrogen injection flow rates, and a cooling slope range that balances phase change rate and microcapsule integrity is optimally selected. The closed-loop calibration module calculates the Kalman gain damping coefficient based on the deviation value and inputs it into the filter gain compensation formula. This coefficient is then sent in reverse to the polarity analysis module, which receives it and uses it to correct the base weights used in real-time when processing continuous spectral sequences. The closed-loop calibration module also collects acoustic impedance attenuation characteristic data of porous framework microcapsules passing through a piezoelectric ceramic transducer array via the RF backhaul channel. Frequency domain analysis is performed on this data to extract crystal density data characterizing sound wave transmittance. The module compares the crystal density data with preset lattice standard values ​​in the system memory to generate a fourth comparison result. These preset lattice standard values ​​are obtained through frequency domain analysis calibration of protective microcapsule samples with high crystal density and good storage stability. Based on the fourth comparison result, frequency drift compensation data is generated, and the closed-loop calibration module sends this data to the upstream lattice rearrangement decision unit. The lattice rearrangement decision unit receives frequency drift compensation data and uses the data to dynamically adjust and calculate the acoustic field frequency band parameters for the next execution cycle.

[0029] The dual fluorescent dye system operating within the probe labeling device is based on the transmembrane transport mechanism of living cells. Dichlorofluorescein diacetate probes are lipid-soluble molecules and do not possess inherent fluorescent properties. After penetrating the probiotic cell membrane and entering the cytoplasm, the dichlorofluorescein diacetate probe is hydrolyzed by esterases within the cytoplasm to generate dichlorofluorescein. This dichlorofluorescein then undergoes an oxidation reaction with the high concentration of oxygen free radicals induced by the lactic acid fermentation environment, releasing a green emission spectrum at a specific wavelength. Trimethylaminodiphenylhexane triene probes possess hydrophobic properties and automatically seek out and embed into the hydrophobic tail region of the cell membrane phospholipid bilayer in a liquid environment. Increased fermentation temperature or a sudden drop in acidity causes the phospholipid molecules to become looser, and the trimethylaminodiphenylhexane triene probe undergoes a change in fluorescence polarization as the restriction on phospholipid molecule movement decreases.

[0030] The water-in-oil-in-water composite wall material liquid prepared by the multiphase emulsification equipment exhibits a multi-layered nested emulsion structure at the microscopic scale. The inner aqueous phase carries a pure culture of probiotics treated with probe labeling. The middle oil phase mainly uses hydrogenated palm oil as a thermosensitive phase change liposome to construct a physical barrier that blocks the infiltration of external water-soluble organic acids and oxygen molecules through its hydrophobic properties. The outer aqueous phase contains a cross-linked polysaccharide matrix, such as sodium alginate aqueous solution. In some embodiments, after the primary microcapsules are formed, they enter a cross-linking curing bath containing divalent calcium ions. The divalent calcium ions can be sourced from calcium chloride aqueous solution, with a calcium chloride concentration preferably of 1% to 5%, and a cross-linking time preferably of 1 to 10 minutes. This causes a rapid ion exchange reaction when the sodium alginate aqueous solution comes into contact with the cross-linking curing bath containing divalent calcium ions, generating a tough hydrogel shell. To maintain the stability of the multi-layered nested structure, the research team added polyglycerol polyricinoleate as an emulsifier for mixing and preparation under the high shear force of the twin-screw extruder.

[0031] The ultrasonic standing waves emitted by the piezoelectric ceramic transducer array into the cryogenic liquid nitrogen bath converge and superimpose in space to form a stable periodic sound field distribution. The stationary regions within the sound field where the particle vibration velocity is zero constitute the standing wave nodes. When the porous framework microcapsules are suspended and pass through the standing wave sound field, they are subjected to a nonlinear time-averaged force pointing towards the standing wave nodes. This causes the acoustic radiation force of the standing wave nodes to act directly on the hydrogenated palm oil molecules undergoing a thermodynamic contraction phase transition inside the porous framework microcapsules. Hydrogenated palm oil molecules under conventional cryogenic quenching conditions often exhibit disordered amorphous crystals, leaving microscopic pore defects. The acoustic radiation force of the standing wave nodes, like a microscopic mold, applies high-frequency mechanical compression, forcing the free lipid molecules to overcome steric hindrance and stack in an orderly manner along the geometric direction of the close-packed hexagonal lattice.

[0032] The raw photoelectric signal output by the spectral detection equipment inevitably includes high-concentration milk protein dispersive light and ambient broadband noise induced by aerodynamic turbulence in the pipeline. The Kalman filter algorithm, as the optimal autoregressive data processing architecture, is embedded in the low-level code layer of the acquisition module to address this noise interference. The Kalman filter algorithm deduces the prior state estimate for the current moment based on the system state estimate from the previous observation period, and then uses the actual photoelectric signal observation value returned by the spectral detection equipment at the current moment for difference calculation. The Kalman filter algorithm dynamically solves for the optimal gain matrix by combining a pre-set state transition matrix and the observation noise covariance matrix. Using the optimal gain matrix, while filtering out random abrupt peaks, it retains the weak long-wavelength signal emitted by the probiotic live fluorescence. After time-domain filtering and reconstruction, a pure and smooth continuous spectral sequence is output. In some embodiments, the state vector includes at least the main emission peak intensity, polarization-related light intensity components, and background noise estimates. The observation vector is the multi-channel photoelectric signal acquired by the spectral detection equipment within the current sampling period. The state transition matrix is ​​constructed based on the trend of spectral signal changes within adjacent sampling periods, and the observation matrix is ​​constructed based on the channel configuration and detection response relationship of the spectral detection equipment. The process noise covariance matrix is ​​initialized using pre-acquired data from blank samples and standard fluorescence samples, while the observation noise covariance matrix is ​​obtained through equipment static sampling noise calibration. In some implementations, the initialization parameters of the Kalman filter algorithm can be recalibrated according to different strains, different dairy product systems, and different flow conditions to ensure the stability of continuous spectral sequence reconstruction.

[0033] The habitat micro-index integrates two underlying biological computational models: the cell membrane fluidity micro-index and the oxygen free radical accumulation index. The cell membrane fluidity micro-index originates from the anisotropy calculation of the difference and ratio between parallel-polarized and perpendicular-polarized simulated light intensity signals by the polarity analysis module. A rising cell membrane fluidity micro-index reflects the denaturation of membrane proteins and the loss of selective isolation function of the semi-permeable membrane due to heat and acid stimulation of probiotics. The oxygen free radical accumulation index is obtained by discretely integrating and summing the peak area data of secondary fluorescence emission spectra over the time axis using the reactive oxygen species analysis module. It is mainly used to calibrate the concentration levels of harmful metabolites such as hydrogen peroxide and superoxide anions within the cytoplasm. The evaluation module uses a multi-dimensional data fusion algorithm to linearly weight and sum the physical structural damage weight of the cell membrane fluidity micro-index and the chemical toxicity weight of the oxygen free radical accumulation index to generate the habitat micro-index.

[0034] The frequency adjustment command issued by the drive component carries the oscillation frequency and waveform duty cycle engineering parameters of the radio frequency drive electrical signal. Upon receiving the frequency adjustment command, the piezoelectric ceramic transducer array immediately changes the mechanical deformation rhythm of the piezoelectric wafer. This change in mechanical deformation rhythm causes the antinodes and nodes of the ultrasonic standing wave to shift spatially within the microcapsule curing bath, ensuring that all porous microcapsules tumbling with the fluid receive uniform acoustic radiation force compression. The synchronous pumping cooling command issued by the drive component includes analog control current sent to the micro-flow valve and the twin-screw extruder. This instructs the micro-flow valve to expand its opening, urgently replenishing the cryogenic liquid nitrogen into the rapid quenching equipment, thereby increasing the temperature rise and fall slope curve. Simultaneously, it controls the servo motor of the twin-screw extruder to increase its speed to match the cooling changes.

[0035] The Kalman gain damping coefficient generated by the closed-loop calibration module establishes a software-level feedforward compensation mechanism for valve hysteresis and thermodynamic conduction inertia in industrial settings. When the actual cooling slope data monitored by the temperature sensing element is far below the thermodynamic slope threshold, it indicates a severe lag in the heat absorption of liquid nitrogen vaporization. The closed-loop calibration module calculates the Kalman gain damping coefficient based on the deviation between the cooling slope data and the thermodynamic slope threshold and sends it inversely to the polarity analysis module. This prompts the polarity analysis module to use the Kalman gain damping coefficient to forcibly reduce the confidence weight of recent observation data in the continuous spectral sequence to avoid oscillation overshoot in the control system. The frequency drift compensation data calculated by the closed-loop calibration module comes from the spectral analysis model of the acoustic impedance attenuation characteristics of porous skeleton microcapsules passing through the ultrasonic standing wave field. If the crystal density data fails to match the preset lattice standard value, it indicates that the existing ultrasonic intervention frequency and the mechanical resonance frequency of the porous skeleton microcapsule shell itself have not achieved tight coupling. The closed-loop calibration module then calculates and outputs the frequency drift compensation data based on the fourth comparison result to guide the lattice rearrangement decision unit to perform a micro-frequency sweep in the next cycle.

[0036] Probiotics often face heat stress and osmotic stress from high-temperature instantaneous sterilization and the accumulation of organic acids during dairy product fermentation and processing. The preparation system relies on the coordinated operation of equipment and control devices to establish a physical defense barrier against harsh external environments. A probe labeling device is connected to the dairy fermentation pipeline to introduce probiotic liquid, which is then pumped into a dual-staining traceability device. This device connects to the probiotic liquid and a dichlorofluorescein diacetate probe, and the probiotic liquid and the dichlorofluorescein diacetate probe are mixed to generate the first labeling solution, which is then introduced into the secondary dyeing system. The chlorofluorescein diacetate probe is designed to penetrate the cell wall of probiotics and react with endogenous reactive oxygen species. After the first labeling solution is generated, it flows into the fluorescent pre-staining device. The fluorescent pre-staining device receives the first labeling solution and the trimethylaminodiphenylhexane probe, and mixes the first labeling solution and the trimethylaminodiphenylhexane probe to generate a double labeling solution. The trimethylaminodiphenylhexane probe will specifically embed in the hydrophobic region of the probiotic lipid bilayer to reflect the cell membrane damage. The double labeling solution, which has completed molecular-level tracking and deployment, is transported to the fluid granulation device through the pipeline.

[0037] The fluid granulation equipment includes a multiphase emulsification device and an electro-injection microfluidic device. The multiphase emulsification device receives sodium alginate aqueous solution and hydrogenated palm oil. Using the mechanical shear force provided by the twin-screw extruder, the sodium alginate aqueous solution and hydrogenated palm oil are melted and mixed to generate a water-in-oil-in-water composite wall material liquid. The water-in-oil-in-water composite wall material liquid exhibits an alternating nested phase state of an outer hydrophilic layer and an inner hydrophobic layer. Driven by a constant pressure pump, it flows into the coaxial electrostatic nozzle built into the electro-injection microfluidic device. The coaxial electrostatic nozzle simultaneously receives the dual labeling liquid and the water-in-oil-in-water composite wall material liquid. The coaxial electrostatic nozzle generates a coaxial electrostatic field force at the nozzle tip where the inner and outer fluids meet. The coaxial electrostatic field force overcomes the physical tension of the liquid surface and encapsulates the dual labeling liquid inside the water-in-oil-in-water composite wall material liquid to generate primary microcapsules. The fluid granulation equipment uses gravity sedimentation to transport the primary microcapsules to the liquid nitrogen quenching and associated ultrasonic device below.

[0038] The liquid nitrogen quenching-linked ultrasonic equipment integrates cryogenic thermodynamics and acoustic kinetic energy for microcapsule solidification. The internal ultra-rapid quenching device receives primary microcapsules and liquid nitrogen, creating an ultra-low temperature cryogenic bath by bringing the liquid nitrogen into contact with the primary microcapsules. The ultra-low temperature forces the hydrogenated palm oil in the water-in-oil-in-water composite wall material liquid within the primary microcapsules to undergo a transient phase transition crystallization, forming porous framework microcapsules. Since lipid crystal boundaries formed by conventional natural cooling rates are usually accompanied by microscopic stress crack defects, the ultrasonic standing wave device arranged inside the ultra-rapid quenching equipment activates in a positive... A piezoelectric ceramic transducer array is arranged in an alternating pattern. The piezoelectric ceramic transducer array emits high-frequency penetrating ultrasonic standing waves into the suspended porous skeleton microcapsule. The standing wave nodal acoustic radiation force in the form of nodal intersection is generated in the internal space of the porous skeleton microcapsule. The ultrasonic standing wave device uses the mechanical squeezing effect generated by the standing wave nodal acoustic radiation force to drive the hydrogenated palm oil in the water-in-oil-in-water composite wall material liquid contained in the porous skeleton microcapsule to undergo lattice rearrangement to generate protective microcapsules. The liquid nitrogen quenching associated ultrasonic device transports the protective microcapsules to the spectral detection device along the bottom discharge pipe.

[0039] The control device takes over the data communication network of the underlying equipment and establishes a bioelectric signal feedback mechanism. A spectroscopic detection device is fixedly installed outside the fluid output pipeline, continuously irradiating through protective microcapsules to capture the weak fluorescent photons emitted by excited live bacteria and generate photoelectric signals. The acquisition module inside the control device receives the photoelectric signals sent by the spectroscopic detection device. The acquisition module uses an embedded Kalman filter algorithm to calculate and generate a continuous spectral sequence from the photoelectric signals. The Kalman filter algorithm directly filters out the viscous matrix of the dairy products and background dispersion noise caused by air bubbles in the delivery pipeline. The acquisition module then transfers the purified and recombined continuous spectral sequence to the polarity analysis module and the reactive oxygen species analysis module under the evaluation module. The polarity analysis module receives the continuous spectral sequence and initiates feature extraction operations in the polarization optical dimension, extracting the parallel polarization intensity analog signal and the vertical polarization intensity analog signal within the continuous spectral sequence. The polarity analysis module calculates the first difference between the parallel-polarized and vertically polarized light intensity simulated signals and simultaneously calculates their first sum. The polarity analysis module divides the first difference by the first sum to generate a polarization degree value. Based on this polarization degree value, it calculates the cell membrane fluidity micro-index. The parallel reactive oxygen species (ROS) analysis module receives a continuous spectral sequence and extracts the peak area data of the secondary fluorescence emission spectrum within the sequence. It performs discrete integration on the secondary fluorescence emission spectrum peak area data to generate an oxygen free radical accumulation index. The evaluation module coordinates the underlying analysis unit to extract both the cell membrane fluidity micro-index and the oxygen free radical accumulation index. Finally, it concatenates the cell membrane fluidity micro-index and the oxygen free radical accumulation index to generate a habitat micro-index, which is then transferred to the regulation module.

[0040] The regulation module constructs a dual-parallel intervention decision model to cope with complex processing stress environments. The module is divided into a lattice rearrangement decision unit and a phase transition decision unit. The lattice rearrangement decision unit receives the cell membrane fluidity micro-index and the oxygen free radical accumulation index, compares the cell membrane fluidity micro-index with a preset membrane threshold to generate a first comparison result, and simultaneously compares the oxygen free radical accumulation index with a preset oxygen threshold to generate a second comparison result. Based on the first and second comparison results, the lattice rearrangement decision unit extracts the acoustic duty cycle parameter and acoustic field frequency band parameter from a preset multidimensional situational awareness data table, and compiles and generates an ultrasonic modulation command based on the acoustic field frequency band parameter and acoustic duty cycle parameter, which is then transferred to the drive component. The phase transition decision unit receives the habitat micro-index, including the cell membrane fluidity micro-index, and compares the cell membrane fluidity micro-index with a preset survival threshold. A third comparison result is generated. Based on the third comparison result, the target value of shell crystallization density that meets the current physical defense requirements is calculated and transferred to the drive component. The acoustic field drive unit inside the drive component receives the ultrasonic modulation command and generates a frequency adjustment command based on the ultrasonic modulation command. This command is sent to the piezoelectric ceramic transducer array, causing the piezoelectric ceramic transducer array to instantly change the mechanical oscillation frequency and adjust the position of the spatial standing wave node. The industrial control execution unit receives the target value of shell crystallization density and generates a pumping cooling command in the form of an analog signal based on the target value of shell crystallization density. The pumping cooling command is sent to the micro-flow guide valve and the twin-screw extruder respectively. The micro-flow guide valve adjusts the valve body opening and closing amplitude according to the pumping cooling command to control the liquid nitrogen injection flow rate. The twin-screw extruder changes the motor speed according to the pumping cooling command to adjust the liposome melt extrusion ratio in the composite wall material.

[0041] The control device establishes a closed-loop calibration module to prevent mechanical response delay errors in industrial production environments. The temperature sensing element embedded inside the rapid quenching equipment collects cooling slope data and sends it to the closed-loop calibration module. The industrial control execution unit collects electrical frequency response characteristic data of the micro-flow guide valve and the twin-screw extruder during operation and sends it to the closed-loop calibration module. The closed-loop calibration module receives the cooling slope data, calls a thermodynamic analysis comparison algorithm to calculate the deviation between the cooling slope data and a preset thermodynamic slope threshold, and calculates and generates a Kalman gain damping coefficient based on the deviation value. This Kalman gain damping coefficient is then sent to the polarity analysis module. The Kalman gain damping coefficient is received and used to calculate and process the continuous spectral sequence to correct the extraction weight. The closed-loop calibration module collects the acoustic impedance attenuation characteristic data generated by the porous skeleton microcapsules passing through the piezoelectric ceramic transducer array through the RF backhaul channel, extracts the crystal density data in the acoustic impedance attenuation characteristic data, compares the crystal density data with the preset lattice standard value to generate the fourth comparison result, calculates and generates frequency drift compensation data based on the fourth comparison result, and sends the frequency drift compensation data to the lattice rearrangement decision unit. The lattice rearrangement decision unit receives the frequency drift compensation data and uses the frequency drift compensation data to calculate and generate the sound field frequency band parameters.

[0042] The specific data processing path for the acquisition module to calculate and generate a continuous spectral sequence from the photoelectric signal using the embedded Kalman filter algorithm is as follows.

[0043] The acquisition module establishes state equations and observation equations for photoelectric signals. The state equations are:

[0044] In the above state equation, This represents the true spectral state vector of the system at the current moment. This represents the true spectral state vector of the previous observation period. Represents the state transition matrix. This represents the process noise vector. The observation equation is:

[0045] In the above observation equation, This represents the actual photoelectric signal observation value returned by the spectral detection equipment at the current moment. Represents the observation matrix. This represents the true spectral state vector of the system at the current moment. This represents the observation noise vector. The acquisition module derives the prior state estimate for the current moment based on the system state estimate from the previous observation period. The derivation formula is as follows:

[0046] In the above derivation formula, This represents the prior state estimate at the current moment. Represents the state transition matrix. This represents the system state estimate from the previous observation period. The acquisition module synchronously calculates the prior error covariance matrix for the current moment, using the following formula:

[0047] In the above calculation formula, This represents the prior error covariance matrix at the current time. Represents the state transition matrix. The transpose of the state transition matrix. This represents the error covariance matrix of the previous observation period. This represents the process noise covariance matrix. The acquisition module dynamically solves for the optimal gain matrix by combining the observation noise covariance matrix. The solution formula is:

[0048] In the above solution formula, Represents the optimal gain matrix. This represents the prior error covariance matrix at the current time. Represents the observation matrix. This represents the transpose of the observation matrix. This represents the observation noise covariance matrix.

[0049] The acquisition module updates the posterior state estimate at the current moment using the optimal gain matrix and the actual photoelectric signal observations. The update formula is as follows:

[0050] In the above update formula, This represents the posterior state estimate at the current moment. This represents the prior state estimate at the current moment. Represents the optimal gain matrix. This represents the actual photoelectric signal observation value returned by the spectral detection equipment at the current moment. This represents the observation matrix. The posterior state estimate at the current moment is the pure spectral data after filtering out noise. The acquisition module performs time-domain filtering and recombination on the posterior state estimates arranged in a time series to generate and output a pure and smooth continuous spectral sequence. The specific data processing path for the polarity analysis module to calculate and generate the cell membrane fluidity micro-index based on the polarization degree value is as follows: The polarity analysis module extracts the parallel polarized light intensity analog signal and the vertical polarized light intensity analog signal within the continuous spectral sequence. The polarity analysis module calculates the first difference between the parallel polarized light intensity analog signal and the vertical polarized light intensity analog signal, and simultaneously calculates the first sum of the parallel polarized light intensity analog signal and the vertical polarized light intensity analog signal. The polarity analysis module divides the first difference by the first sum to generate the polarization degree value. The calculation formula is:

[0051] In the above calculation formula, Indicates the degree of polarization. This represents a simulated signal of parallel polarized light intensity. This represents a simulated signal of vertically polarized light intensity. The polarity resolution module calculates and generates a cell membrane fluidity micro-index based on the polarization degree value and a pre-stored biophysical mapping formula. The biophysical mapping formula is established by fitting the polarization degree values ​​of samples with different degrees of damage to the results of membrane integrity testing. The fitting method can be linear fitting, piecewise linear fitting, or nonlinear regression fitting. The biophysical mapping formula is as follows:

[0052] In the above biophysical mapping formula, Indicating a microscopic index of cell membrane fluidity, The standard polarization constant of a cell membrane under ideal healthy conditions. This represents the degree of polarization. The specific data processing path for the reactive oxygen species (ROS) analysis module to perform discrete integral calculations on the secondary fluorescence emission spectrum peak area data to generate the oxygen free radical accumulation index is as follows: The ROS analysis module establishes a discrete integral summation model on the time axis. The discrete integral summation model is as follows:

[0053] In the above discrete integral summation model, Indicates the oxygen free radical accumulation index. This represents the total number of discrete sampling points within the acquisition period. Indicates the current sampling sequence number. Indicates the first The secondary fluorescence emission spectrum peak area data corresponding to each sampling time. This represents the time interval between two adjacent samples. The specific data processing path for the evaluation module to calculate the habitat micro-index by concatenating the cell membrane fluidity micro-index and the oxygen free radical accumulation index is as follows: The evaluation module extracts the cell membrane fluidity micro-index and the oxygen free radical accumulation index. The evaluation module calls a multi-dimensional data fusion algorithm to perform a weighted calculation of the cell membrane fluidity micro-index and the oxygen free radical accumulation index. The fusion calculation formula is:

[0054] In the above fusion calculation formula, E represents the habitat micro-index. Before performing weighted calculation, the cell membrane fluidity micro-index F and the oxygen free radical accumulation index ROS are normalized by mapping the system's preset maximum and minimum values ​​to the dimensionless interval [0,1], thereby eliminating the dimensional differences of cross-dimensional data. α represents the physical structure damage weight corresponding to the cell membrane fluidity micro-index, and β represents the chemical toxicity weight corresponding to the oxygen free radical accumulation index. The specific acquisition method of the physical structure damage weight and the chemical toxicity weight is as follows: pre-extract the cell membrane fluidity micro-index sequence and the oxygen free radical accumulation index sequence of multiple batches of historical fermentation broth samples under different intensities of thermodynamic stress, calculate the first information entropy of the cell membrane fluidity micro-index sequence and the second information entropy of the oxygen free radical accumulation index sequence, calculate and output the physical structure damage weight based on the dispersion of the first information entropy, calculate and output the chemical toxicity weight based on the dispersion of the second information entropy, and the sum of the values ​​of the physical structure damage weight and the chemical toxicity weight is equal to one; F represents the cell membrane fluidity micro-index, and ROS represents the oxygen free radical accumulation index.

[0055] The specific data processing path for the closed-loop calibration module to calculate and generate the Kalman gain damping coefficient based on the deviation value is as follows: The temperature sensing element continuously collects discrete temperature values ​​inside the rapid quenching equipment at a fixed millisecond time step. The closed-loop calibration module receives the discrete temperature values ​​and establishes a temperature sequence matrix that changes over time. It then applies the least squares method to perform linear regression fitting on a preset number of consecutive discrete temperature values ​​within the temperature sequence matrix, extracting the slope value of the linearly fitted line to generate the cooling slope data. The closed-loop calibration module calculates the deviation value between the cooling slope data and the preset thermodynamic slope threshold. The calculation formula is as follows:

[0056] In the above calculation formula, Indicates the deviation value. This represents the cooling slope data collected by the temperature sensing element. This represents the preset thermodynamic slope threshold. The closed-loop calibration module calculates the Kalman gain damping coefficient based on the deviation value, using the filter gain compensation formula. The filter gain compensation formula is:

[0057] In the above filter gain compensation formula, D represents the Kalman gain damping coefficient, and γ represents the heat transfer hysteresis adjustment coefficient of the rapid quenching equipment. The calibration path of the heat transfer hysteresis adjustment coefficient is as follows: when the rapid quenching equipment is in an unloaded state, record the time delay data from the moment the micro-guide valve receives the maximum opening control signal to the moment the temperature sensing element detects that the temperature of the bath inside the rapid quenching equipment reaches the steady-state lower limit. Divide the constant by the time delay data to generate the heat transfer hysteresis adjustment coefficient; ΔTslope represents the deviation value. The closed-loop calibration module sends the Kalman gain damping coefficient in reverse to the polarity analysis module. The polarity analysis module receives the Kalman gain damping coefficient and uses it to correct the basic weights when calculating and processing the continuous spectral sequence in real time. Specifically, the Kalman gain damping coefficient is directly multiplied by the process noise covariance matrix in the Kalman filtering algorithm, thereby reducing the confidence weight of recent observation data in the continuous spectral sequence in the underlying logic. The specific data processing path of the closed-loop calibration module in calculating and generating frequency drift compensation data based on the fourth comparison result is as follows. The closed-loop calibration module collects acoustic impedance attenuation characteristic data generated by porous framework microcapsules passing through a piezoelectric ceramic transducer array. The module then performs frequency domain analysis on the acoustic impedance attenuation characteristic data to extract crystal density data. This frequency domain analysis is specifically implemented using a spectral analysis model, whose data processing path is as follows: First, the collected time-domain acoustic impedance attenuation characteristic data is windowed and subjected to a Fast Fourier Transform (FFT) to convert it into a frequency domain amplitude spectrum. Second, the fundamental peak amplitude corresponding to the fundamental frequency of the ultrasonic standing wave and the harmonic peak amplitude corresponding to the second harmonic frequency are extracted from the frequency domain amplitude spectrum. Third, the harmonic peak amplitude and the fundamental peak amplitude are calculated. The ratio of amplitudes generates nonlinear acoustic response characteristic values. Finally, these nonlinear acoustic response characteristic values ​​are substituted into a pre-calibrated density mapping function to calculate and output crystal density data. The density mapping function is constructed as follows: multiple sets of standard porous skeleton microcapsule samples with gradient differences are pre-prepared, and their actual crystal density is determined using micro-CT (Micro-CT) non-destructive scanning. Simultaneously, the nonlinear acoustic response characteristic values ​​of each sample under an ultrasonic field are collected. Polynomial curve fitting is performed using the least squares method to establish a unique mathematical mapping relationship between the characteristic values ​​and the density. The closed-loop calibration module compares the crystal density data with the preset lattice standard values ​​in the system memory to generate a fourth comparison result. The underlying data structure of the fourth comparison result is the arithmetic difference between the crystal density data and the preset lattice standard values. The closed-loop calibration module generates frequency drift compensation data based on the fourth comparison result. The calculation formula is:

[0058] In the above calculation formula, This represents frequency drift compensation data. This represents the frequency drift response coefficient of the piezoelectric ceramic transducer array. Indicates the preset lattice standard value. This represents the crystal density data. The frequency drift response coefficient is obtained by calibrating the output response of the piezoelectric ceramic transducer array at different driving frequencies. The closed-loop calibration module sends the frequency drift compensation data to the upstream lattice rearrangement decision unit. The lattice rearrangement decision unit receives the frequency drift compensation data and uses it to dynamically adjust and calculate the acoustic field frequency band parameters for the next execution cycle. Specifically, the adjustment method is to add the received frequency drift compensation data to the acoustic field frequency band parameters applied in the current cycle, and use the sum of the two as the new acoustic field frequency band parameters output in the next execution cycle. The control device continuously executes the above-mentioned frequency domain closed-loop adjustment cycle until it detects that the current batch of dairy product fluid granulation and conveying task has ended or receives a system shutdown command, at which point the iterative feedback loop is terminated.

[0059] In some implementations, the preset membrane threshold, preset oxygen threshold, preset survival threshold, preset thermodynamic slope threshold, and preset lattice standard values ​​are all established through preliminary experiments. Specifically, samples of the target probiotics in a dairy product simulation system under normal, mildly stressed, and severely stressed conditions are selected. Corresponding parallel polarized light intensity simulation signals, vertically polarized light intensity simulation signals, secondary fluorescence emission spectrum peak area data, cooling slope data, and acoustic impedance attenuation characteristic data are collected. These data are then combined with the viable cell survival rate, microcapsule rupture rate, and crystal density results obtained using the plate count method to establish a corresponding relationship. Based on the parameter range corresponding to a viable cell survival rate not lower than a preset lower limit and microcapsule density meeting storage requirements, the preset membrane threshold, preset oxygen threshold, preset survival threshold, preset thermodynamic slope threshold, and preset lattice standard values ​​are determined. Preferably, the preset survival threshold is determined based on a comprehensive analysis of the target probiotics' minimum acceptable viable cell count in the target dairy product system, the shelf-life survival rate, and the level of metabolic activity retention.

[0060] In some implementations, when the target probiotic strain, dairy product matrix composition, fluid granulation flow rate conditions, or storage temperature conditions change, the preset membrane threshold, preset oxygen threshold, preset survival threshold, preset thermodynamic slope threshold, preset lattice standard value, and the multidimensional situational awareness data table can be recalibrated based on the new pre-experiment results.

[0061] In some implementations, the multidimensional situational awareness data table uses the cell membrane fluidity micro-index range and the oxygen free radical accumulation index range as input dimensions, and the acoustic duty cycle parameter and acoustic field frequency band parameter as output dimensions, and is calibrated through multiple sets of process experiments.

[0062] In some implementations, the multidimensional situational awareness data table can be established by statistically analyzing and discretely categorizing the crystallinity, microcapsule rupture rate, and viable bacteria retention level corresponding to different membrane fluidity micro-index intervals and oxygen free radical accumulation index intervals. Alternatively, it can be stored in an interval lookup table format after fitting a regression model. The construction path of the regression model is as follows: using the cell membrane fluidity micro-index and oxygen free radical accumulation index as two-dimensional independent variables, and the optimal acoustic duty cycle parameter and acoustic field frequency band parameter to meet the preset viable bacteria retention level at the end of the shelf life as two dependent variables. A training set is constructed based on a large amount of multidimensional sample data collected in the pre-experiment. The training set is iteratively fitted using a multivariate nonlinear regression algorithm. The mean squared error loss function between the model prediction output and the actual optimal intervention parameters is continuously minimized using a gradient descent algorithm until the loss function converges, thereby establishing and preserving the continuous mapping relationship between the independent and dependent variables, and completing the construction of the regression model. In some implementations, when the cell membrane fluidity micro-index is in the high-damage range and the oxygen free radical accumulation index is in the high-stress range, the lattice rearrangement decision unit extracts a higher duty cycle parameter and a sound field frequency band parameter corrected by a preset offset from the multidimensional situational awareness data table to enhance the lattice rearrangement effect of ultrasonic standing waves on the lipid phase inside the porous framework microcapsules. When the cell membrane fluidity micro-index is in the moderate-damage range and the oxygen free radical accumulation index is in the moderate-stress range, the lattice rearrangement decision unit extracts a moderate duty cycle parameter and a reference sound field frequency band parameter. The phase transition decision unit selects a target range for shell crystallization density corresponding to the survival risk level corresponding to the third comparison result, and uses a preset value in the target range as the target value for shell crystallization density in the current period.

[0063] The "data splicing calculation" described in this specification preferably includes an overall processing procedure of splicing, normalizing, and weighted fusion of multi-dimensional indicators, with weighted fusion calculation being the preferred implementation method. The preset survival threshold described in this specification is preferably stored in the standard parameter library of the control device; "preset survival threshold in the preset standard library" and "preset survival threshold" have the same technical meaning.

[0064] Embodiment 1 of this invention: In the probiotic addition process of a conventional pasteurized milk production line, the preparation system first pumps a logarithmically growing *Lactobacillus rhamnosus* solution into a probe labeling device. A dual-staining traceability device receives the probiotic solution and adds a 5 μmol / L dichlorofluorescein diacetate probe, mixing to generate a first labeling solution, which is then sent to a fluorescent pre-staining device. The first labeling solution is mixed with a 10 μmol / L trimethylaminodiphenylhextriene probe, completing the molecular labeling process. The resulting dual-labeled solution is then transferred to a fluid granulation device. A multiphase emulsification device receives a 2% (w / w) sodium alginate aqueous solution and molten hydrogenated palm oil. Using a twin-screw extruder at a shear rate of 3,000 rpm, a composite wall material liquid is generated and delivered to a coaxial electrostatic nozzle. Under the influence of a 15 kV coaxial electrostatic field, the coaxial electrostatic nozzle encapsulates the dual-labeled solution within the composite wall material liquid, forming primary microcapsules. These primary microcapsules then freely fall into a liquid nitrogen quenching and associated ultrasonic device. The rapid quenching equipment introduces liquid nitrogen by opening a micro-flow valve. The liquid nitrogen contacts the primary microcapsules, causing hydrogenated palm oil to undergo a phase change and crystallize into porous framework microcapsules. An orthogonally arranged piezoelectric ceramic transducer array emits ultrasonic standing waves at a frequency of 40 kHz towards the porous framework microcapsules. The acoustic radiation force at the standing wave nodes drives the hydrogenated palm oil to rearrange its lattice, generating protective microcapsules. A spectroscopic detection device captures the fluorescence signal emitted by the protective microcapsules and sends the raw photoelectric signal to the acquisition module. The acquisition module uses a Kalman filter algorithm to generate a continuous spectral sequence and transfers it to the evaluation module. The polarity analysis module extracts the parallel and perpendicular polarized light intensity signals and calculates the cell membrane fluidity micro-index. The control module receives the cell membrane fluidity micro-index and compares it with a preset survival threshold. Based on the survival comparison result, it calculates a target value for 90% shell crystallization density. The industrial control execution unit receives the target value for shell crystallization density and converts it into a pumping cold load command, which is sent to the micro-flow valve to dynamically adjust the liquid nitrogen injection volume to cope with the sterilization temperature rise pressure. After the prepared protective microcapsules were added to the pasteurized milk system, the viable cell count, microcapsule rupture rate, and shell crystallinity were measured under the same storage conditions. The results showed that, compared with the control group without closed-loop control, the protective microcapsules obtained in this embodiment had a higher viable cell retention level and a lower rupture rate at the end of the shelf life.

[0065] Embodiment 2 of this invention: The preparation system addresses the problem of organic acid permeation during long-term storage of room-temperature fermented milk by selecting *Bifidobacterium animalis* subsp. *lactamase* as the core live bacteria. A dual-staining traceability device receives the live bacteria solution and mixes it with a reactive oxygen species fluorescent probe to generate a first labeled solution. A fluorescent pre-staining device receives the first labeled solution and mixes it with a polar fluorescent probe to generate a dual-labeled solution. A multiphase emulsification device receives polysaccharide matrix and liposomes, and uses a twin-screw extruder to physically melt and generate a composite wall material liquid. A coaxial electrostatic nozzle generates a coaxial electrostatic field force to encapsulate the dual-labeled solution within the composite wall material liquid, generating primary microcapsules. These primary microcapsules are then transported to a liquid nitrogen quenching and associated ultrasonic device. A rapid quenching device uses liquid nitrogen to cryogenically treat the primary microcapsules, causing the internal lipids to undergo a phase transition and crystallize, generating porous framework microcapsules. An ultrasonic standing wave device activates a piezoelectric ceramic transducer array to emit high-frequency sound waves. The acoustic radiation force at the standing wave nodes drives the hydrogenated palm oil lattice rearrangement to eliminate micropores, protecting the microcapsules as they flow sequentially through a spectroscopic detection device. The acquisition module receives photoelectric signals and uses filtering to generate a continuous spectral sequence, which is then transferred to the reactive oxygen species (ROS) analysis module. The ROS analysis module extracts the peak area of ​​the secondary fluorescence emission spectrum and integrates it to generate an oxygen free radical accumulation index. The lattice rearrangement decision unit receives the oxygen free radical accumulation index and compares it with a preset oxygen threshold. When the oxidative stress level exceeds the limit, it extracts 50% of the pulse duty cycle parameter from the multidimensional situational awareness data table. The acoustic field driving unit receives ultrasonic modulation commands and converts them into frequency adjustment commands to regulate the operating frequency nodes of the transducer array. The closed-loop calibration module collects acoustic impedance attenuation characteristic data of porous framework microcapsules as they pass through the acoustic field. The closed-loop calibration module compares the crystal density data with preset lattice standard values, generates frequency drift compensation data, and transfers it to the control module to adaptively correct the physical intervention parameters. Storage stability tests show that, under long-term storage conditions of fermented milk at room temperature, the adaptively corrected physical intervention parameters used in this embodiment can reduce the damage to the microcapsule structure caused by the acidic environment, helping to maintain the activity of *Bifidobacterium animalis* subsp. *lactobacterium*.

[0066] Embodiment 3 of this invention: In a large-scale continuous production environment, the preparation system maintains probiotic activity through deep coupling between the control device and the equipment. The probe labeling device sequentially mixes dichlorofluorescein diacetate probe and trimethylaminodiphenylhextriene probe to generate a dual-labeled solution, which then enters the fluid granulation device. The multiphase emulsification device uses a twin-screw extruder to prepare the composite wall material solution. The electro-spray microfluidic device uses electrostatic force to encapsulate the dual-labeled solution inside the composite wall material solution to generate primary microcapsules. The rapid quenching device receives the primary microcapsules and contacts them with liquid nitrogen, causing the hydrogenated palm oil inside the primary microcapsules to undergo phase transition crystallization to generate porous framework microcapsules. The ultrasonic standing wave device uses the acoustic radiation force generated by an orthogonally arranged piezoelectric ceramic transducer array to drive the lattice rearrangement of lipid molecules. The spectral detection device transmits photoelectric signals back to the acquisition module, which calculates and generates a continuous spectral sequence. The evaluation module splices data from the cell membrane fluidity micro-index and the oxygen free radical accumulation index to calculate the habitat micro-index. The control module generates ultrasonic modulation commands and target values ​​for shell crystallization density based on the comparison of habitat micro-indices with survival thresholds. The industrial control execution unit collects the electrical frequency response characteristic data of the micro-flow valve and the twin-screw extruder and sends it to the closed-loop calibration module. The temperature measuring element inside the rapid quenching equipment collects cooling slope data and sends it to the closed-loop calibration module. The closed-loop calibration module calculates the deviation between the cooling slope data and the preset thermodynamic slope threshold, calculates the Kalman gain damping coefficient, and sends it to the polarity analysis module. The evaluation module uses the Kalman gain damping coefficient to correct the processing weights of subsequent spectral sequences, effectively compensating for thermodynamic conduction lag in the industrial control process. The preparation system establishes a high-density physical barrier around the microcapsules through data synergy of acoustic intervention and cold injection. Under continuous production conditions, the closed-loop calibration module can reduce batch-to-batch fluctuations in microcapsule shell density and improve the consistency of the preparation process by real-time feedback correction of cooling slope and acoustic impedance attenuation characteristic data.

[0067] Efficacy Verification Example: Both the experimental and control groups were stored in dairy product systems with the same formulation, under the same packaging conditions, and at the same storage temperature. Viable cell counts were determined using the plate count method, microcapsule rupture rate was determined using statistical methods based on microscopic images, and shell crystallinity was characterized using frequency domain analysis or image analysis. To verify the effect of the preparation system of this invention on improving the storage stability of probiotics in dairy products, experimental and control groups were set up. The experimental group used the preparation system of this invention to prepare protective microcapsules; the control group used a conventional microcapsule preparation method without closed-loop control and ultrasonic standing wave lattice rearrangement. The two groups of microcapsules were added to dairy product systems with the same formulation, and viable cell counts, microcapsule rupture rates, and shell crystallinity were measured on days 1, 7, 14, and at the end of the shelf life under the same storage temperature.

[0068] The results showed that the number of viable bacteria in the experimental group was higher than that in the control group at the end of the shelf life, and the microcapsule rupture rate and shell crystallization density were lower than those in the control group, indicating that the preparation system of the present invention can improve the storage stability of probiotics in dairy products.

[0069] In some implementations, the above results can also be obtained by observing the surface structure of the microcapsules with a scanning electron microscope, determining the number of viable bacteria by plate counting, and characterizing the crystal density by image analysis or frequency domain analysis. The above effect verification results can also serve as experimental basis for establishing or correcting the preset membrane threshold, preset oxygen threshold, preset survival threshold, preset thermodynamic slope threshold, preset lattice standard value, and multidimensional situational awareness data table, thereby achieving the adaptation of the preparation system to different probiotic strains and different dairy product systems.

Claims

1. A preparation system for improving the storage stability of probiotics in dairy products, characterized in that, The device includes an apparatus and a control device communicatively connected to the apparatus, the control device being used to control the apparatus; the apparatus includes a probe marking device, a fluid granulation device, a liquid nitrogen quenching associated ultrasonic device, and a spectral detection device located at the output end of the liquid nitrogen quenching associated ultrasonic device, which are connected in sequence; the control device includes an acquisition module, an evaluation module, a regulation module, and a drive component. The acquisition module is used to receive the photoelectric signal sent by the spectral detection device, convert the photoelectric signal into a continuous spectral sequence, and transfer the continuous spectral sequence to the evaluation module; The evaluation module is used to receive the continuous spectral sequence, extract spectral data within the continuous spectral sequence, convert the spectral data into a habitat micro-index, and transfer the habitat micro-index to the regulation module. The control module is used to receive the habitat micro-index, compare the habitat micro-index with a preset survival threshold to generate a survival comparison result, calculate the target value of shell crystallization density and the ultrasonic modulation command based on the survival comparison result, and transfer the target value of shell crystallization density and the ultrasonic modulation command to the drive component. The drive component is configured to receive the target value of shell crystallization density and the ultrasonic modulation command, convert the target value of shell crystallization density into a pumping cooling command, convert the ultrasonic modulation command into a frequency adjustment command, send the pumping cooling command to the fluid granulation equipment, and send the frequency adjustment command to the liquid nitrogen quenching associated ultrasonic equipment.

2. The preparation system for improving the storage stability of probiotics in dairy products according to claim 1, characterized in that, The probe labeling device includes a sequentially connected dual-staining tracing device and a fluorescent pre-staining device; The dual-staining traceability device receives a probiotic solution and a dichlorofluorescein diacetate probe, mixes the probiotic solution and the dichlorofluorescein diacetate probe to generate a first labeling solution, and delivers the first labeling solution to the fluorescent pre-staining device; The fluorescent pre-staining device receives the first labeling solution and the trimethylaminodiphenylhextriene probe, mixes the first labeling solution and the trimethylaminodiphenylhextriene probe to generate a dual labeling solution, and delivers the dual labeling solution to the fluid granulation device.

3. The preparation system for improving the storage stability of probiotics in dairy products according to claim 2, characterized in that, The fluid granulation equipment includes a multiphase emulsification device and an electro-injection microfluidic device connected to the multiphase emulsification device. The multiphase emulsification device includes a twin-screw extruder, and the electro-injection microfluidic device includes a coaxial electrostatic nozzle. The multiphase emulsification device receives an aqueous solution of sodium alginate and hydrogenated palm oil. The twin-screw extruder melts and mixes the aqueous solution of sodium alginate and the hydrogenated palm oil to generate a water-in-oil-in-water composite wall material liquid. The water-in-oil-in-water composite wall material liquid is then conveyed to the coaxial electrostatic nozzle. The coaxial electrostatic nozzle receives the dual-labeled liquid and the water-in-oil-in-water composite wall material liquid, generates a coaxial electrostatic field, and uses the coaxial electrostatic field to encapsulate the dual-labeled liquid inside the water-in-oil-in-water composite wall material liquid to generate primary microcapsules. The primary microcapsules are then conveyed to the liquid nitrogen quenching associated ultrasonic device.

4. The preparation system for improving the storage stability of probiotics in dairy products according to claim 3, characterized in that, The liquid nitrogen quenching-associated ultrasonic equipment includes a rapid quenching device and an ultrasonic standing wave device arranged inside the rapid quenching device. The rapid quenching device receives the primary microcapsule and liquid nitrogen, and contacts the liquid nitrogen with the primary microcapsule, causing the hydrogenated palm oil in the water-in-oil-in-water composite wall material liquid contained in the primary microcapsule to undergo phase change crystallization to form a porous framework microcapsule. The ultrasonic standing wave device includes a piezoelectric ceramic transducer array, which is orthogonally arranged. The piezoelectric ceramic transducer array emits ultrasonic standing waves towards the porous framework microcapsule. The ultrasonic standing waves generate standing wave node acoustic radiation force. The ultrasonic standing wave device uses the standing wave node acoustic radiation force to drive the hydrogenated palm oil in the water-in-oil-in-water composite wall material liquid contained in the porous framework microcapsule to undergo lattice rearrangement to form a protective microcapsule, and then delivers the protective microcapsule to the spectroscopic detection device.

5. The preparation system for improving the storage stability of probiotics in dairy products according to claim 4, characterized in that, The evaluation module includes a polarity resolution module and a reactive oxygen species (ROS) resolution module. The acquisition module receives the photoelectric signal, uses a Kalman filter algorithm to calculate and generate a continuous spectral sequence from the photoelectric signal, and transfers the continuous spectral sequence to the polarity resolution module and the ROS resolution module respectively. The polarity resolution module receives the continuous spectral sequence, extracts the parallel polarized light intensity simulation signal and the vertical polarized light intensity simulation signal within the continuous spectral sequence, calculates the first difference between the parallel polarized light intensity simulation signal and the vertical polarized light intensity simulation signal, calculates the first sum between the parallel polarized light intensity simulation signal and the vertical polarized light intensity simulation signal, divides the first difference by the first sum to generate a polarization degree value, and calculates and generates a cell membrane fluidity micro-index based on the polarization degree value.

6. The preparation system for improving the storage stability of probiotics in dairy products according to claim 5, characterized in that, The reactive oxygen species (ROS) analysis module receives the continuous spectral sequence, extracts the peak area data of the secondary fluorescence emission spectrum within the continuous spectral sequence, and performs discrete integration on the peak area data of the secondary fluorescence emission spectrum to generate an oxygen free radical accumulation index. The evaluation module extracts the cell membrane fluidity micro-index and the oxygen free radical accumulation index, performs data splicing of the cell membrane fluidity micro-index and the oxygen free radical accumulation index to generate a habitat micro-index, and transfers the habitat micro-index to the regulation module.

7. The preparation system for improving the storage stability of probiotics in dairy products according to claim 6, characterized in that, The control module includes a lattice rearrangement decision unit and a phase transition decision unit. The lattice rearrangement decision unit receives the cell membrane fluidity micro-index and the oxygen free radical accumulation index, compares the cell membrane fluidity micro-index with a preset membrane threshold to generate a first comparison result, compares the oxygen free radical accumulation index with a preset oxygen threshold to generate a second comparison result, extracts acoustic duty cycle parameters and acoustic field frequency band parameters from a preset multidimensional situational awareness data table based on the first and second comparison results, generates an ultrasonic modulation command based on the acoustic field frequency band parameters and acoustic duty cycle parameters, and transfers the ultrasonic modulation command to the driving component. The phase transition decision unit receives the cell membrane fluidity micro-index, which is included in the habitat micro-index, compares the cell membrane fluidity micro-index with a preset survival threshold to generate a third comparison result, calculates the target value of the shell crystallization density based on the third comparison result, and transfers the target value of the shell crystallization density to the driving component.

8. The preparation system for improving the storage stability of probiotics in dairy products according to claim 7, characterized in that, The driving assembly includes an acoustic field driving unit and an industrial control execution unit. The high-speed quenching equipment includes a micro-flow guiding valve. The acoustic field driving unit receives the ultrasonic modulation command, generates a frequency adjustment command based on the ultrasonic modulation command, and sends the frequency adjustment command to the piezoelectric ceramic transducer array. The industrial control execution unit receives the target value of shell crystallization density, generates a pumping cooling capacity command based on the target value of shell crystallization density, and sends the pumping cooling capacity command to the micro-flow guiding valve and the twin-screw extruder, respectively.

9. The preparation system for improving the storage stability of probiotics in dairy products according to claim 8, characterized in that, The control device includes a closed-loop calibration module, and the rapid quenching equipment includes a temperature measuring element. The industrial control execution unit collects the electrical frequency response characteristic data of the micro-flow guide valve and the twin-screw extruder, and sends the electrical frequency response characteristic data to the closed-loop calibration module. The temperature measuring element collects cooling slope data and sends the cooling slope data to the closed-loop calibration module. The closed-loop calibration module receives the cooling slope data, calculates the deviation value between the cooling slope data and a preset thermodynamic slope threshold, calculates and generates a Kalman gain damping coefficient based on the deviation value, and sends the Kalman gain damping coefficient to the polarity analysis module. The polarity analysis module receives the Kalman gain damping coefficient and uses the Kalman gain damping coefficient to calculate and process the continuous spectral sequence.

10. The preparation system for improving the storage stability of probiotics in dairy products according to claim 9, characterized in that, The closed-loop calibration module collects acoustic impedance attenuation characteristic data generated by the porous framework microcapsules passing through the piezoelectric ceramic transducer array, extracts crystal density data from the acoustic impedance attenuation characteristic data, compares the crystal density data with a preset lattice standard value to generate a fourth comparison result, calculates and generates frequency drift compensation data based on the fourth comparison result, and sends the frequency drift compensation data to the lattice rearrangement decision unit. The lattice rearrangement decision unit receives the frequency drift compensation data and uses the frequency drift compensation data to calculate and generate sound field frequency band parameters.

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