A method for improving the quality of frozen fish fillets

Abstract

This invention discloses a method for improving the quality of frozen fish fillets, relating to the field of aquatic product freezing processing technology. Before quick-freezing after slicing, impedance spectroscopy is performed on samples from the same batch of fish fillets to be quick-frozen, constructing characteristic parameters for the batch, matching meat quality parameters, and determining the freezing compatibility level. Based on this, a freezing process parameter package is generated, and key parameters and characteristic parameter identification codes are associated and stored in a radio frequency identification temperature sensor tag mounted on a production transport carrier to obtain a full-cycle management tag. During quick-freezing, the target freezing rate is executed while simultaneously collecting temperature time-series data. The refrigeration parameters are adaptively adjusted based on the basic meat quality attribute data within the tag, and the adjustment record is written to the tag after quick-freezing. Based on the inherent physical properties of the fish fillets and the characteristics of the quick-freezing conditions in the tag, corresponding cold chain management methods and terminal thawing control data are matched. Through online detection and full-cycle linkage, ice crystal growth is synergistically suppressed, tissue integrity is maintained, and the quality stability of frozen fish fillets is improved.

Description

Technical Field

[0001] This invention relates to the field of frozen processing technology for aquatic products, and in particular to a method for improving the quality of frozen fish fillets. Background Technology

[0002] Frozen fish fillets are a core product category in my country's aquatic product processing industry, possessing extremely high economic value and industrial scale. Low-temperature freezing is a core technological means to ensure the long-distance, cross-regional distribution of aquatic products, extend shelf life, and achieve long-term stable storage. Its core objective is to maintain the original tissue structure and edible quality of the fish fillets to the greatest extent possible throughout the entire lifecycle of frozen processing, warehousing, and distribution. Currently, the core processes of conventional frozen fish fillet processing and preservation in the industry are raw material pretreatment, directional slicing, quick-freezing, and low-temperature refrigeration. To address the need for quality improvement in frozen fish fillets, existing technological research and development focuses primarily on two dimensions: equipment and process optimization in the quick-freezing stage, and formula optimization for water retention and shape preservation.

[0003] However, the aforementioned existing technologies all have fundamental limitations and cannot fundamentally solve the problem of quality deterioration in frozen fish fillets: Existing technologies generally only focus on optimizing the process of the quick-freezing single step, without establishing a full-cycle ice crystal control logic from freezing processing to cold storage and cold chain circulation. They only achieve initial ice crystal refinement by increasing the instantaneous freezing rate, but ignore the inevitable temperature fluctuations during subsequent storage and circulation that will cause ice crystal recrystallization and abnormal growth, failing to achieve a stable ice crystal inhibition effect throughout the entire cycle; Existing general-purpose freezing processes have poor adaptability to fish species with different meat characteristics. For fish species with delicate muscle fibers and cell structures that are easily damaged by ice crystals, they cannot form effective structural protection, leading to particularly prominent problems of product quality deterioration; At the same time, existing high-end technology solutions that can achieve full-cycle ice crystal control have poor mass production adaptability and cannot meet the mass production needs of large-scale aquatic product processing. Conventional water-retaining formula optimization solutions can only alleviate the surface phenomenon of juice loss and cannot solve the root problem of ice crystals piercing the fish meat structure. There is also the risk of food safety compliance due to excessive addition, which cannot meet the requirements of high-end markets and export standards. Summary of the Invention

[0004] This invention provides a method for improving the quality of frozen fish fillets, solving the technical problem that existing frozen fish fillet processing and preservation methods cannot inhibit abnormal ice crystal growth and maintain the integrity of fish meat tissue structure throughout the freezing and refrigeration cycle, resulting in substandard core quality of frozen fish fillets.

[0005] The first aspect of this invention provides a method for improving the quality of frozen fish fillets, comprising:

[0006] After the fish fillets are sliced ​​and ready to enter the quick-freezing process, representative samples are extracted from the same batch of fish fillets to be quick-frozen for electrochemical impedance spectroscopy detection, and the characteristic parameters of the electrochemical impedance spectroscopy of this batch of fish fillets are constructed.

[0007] Based on the impedance-meat quality correlation table pre-established in the production line, the meat quality characteristic parameters corresponding to the electrochemical impedance spectroscopy characteristic parameters are matched, and the freezing suitability level is determined based on the meat quality characteristic parameters.

[0008] Based on the freezing compatibility level, the corresponding freezing process conditions are configured to obtain a full-process freezing process parameter package. Before the quick-freezing begins, the key parameters of the full-process freezing process parameter package and the identification codes of the electrochemical impedance spectroscopy characteristic parameters are associated and stored in the radio frequency identification temperature sensing tag carried on the corresponding production turnover carrier to obtain a full-cycle management tag.

[0009] According to the target freezing rate in the full-process freezing process parameter package, the fish fillets in the batch bound by the full-cycle control tag are quick-frozen, and the temperature time-series data of the environment in which the fish fillets are located are collected simultaneously during the quick-freezing process.

[0010] Based on the temperature time series data and combined with the basic meat quality attribute data corresponding to the electrochemical impedance spectroscopy characteristic parameters pre-stored in the full-cycle management and control tag, the refrigeration operation parameters of the quick-freezing equipment are adaptively adjusted, and the quick-freezing adjustment record is written into the full-cycle management and control tag after the quick-freezing is completed.

[0011] Based on the inherent physical properties of the fish fillets and the characteristics of the quick-freezing conditions corresponding to the full-cycle management and control tags associated with the batch after quick-freezing, the corresponding cold chain management and control methods and terminal thawing control data are matched to obtain the data.

[0012] Optionally, the step of extracting representative samples from the same batch of fish fillets to be quick-frozen for electrochemical impedance spectroscopy detection and constructing the characteristic parameters of the electrochemical impedance spectroscopy of that batch of fish fillets, after the fish fillets have been sliced ​​and are about to enter the quick-freezing process, includes:

[0013] At the detection station with a dwell function where the fish fillets are sliced ​​and ready to enter the quick-freezing process, a surface contact multi-electrode array is used to sample and perform in-situ electrochemical impedance spectroscopy on the same batch of fish fillets to be quick-frozen, and the original electrochemical response signal is collected.

[0014] The invalid interference signals caused by ambient humidity and free water on the surface of the fish fillet are removed from the original electrochemical response signal to generate an intermediate electrochemical response signal;

[0015] Eliminate electrochemical response signals that are not within the preset frequency range from the intermediate electrochemical response signals to generate the target electrochemical response signal;

[0016] Spectral analysis and impedance feature extraction were performed on the target electrochemical response signal to obtain multiple fish fillet freezing tolerance characteristic indicators;

[0017] The target electrochemical response signal is fitted by a preset equivalent circuit model, and equivalent circuit parameters including extracellular fluid resistance, cell membrane capacitance and intracellular fluid resistance are extracted.

[0018] After normalizing all the aforementioned fish fillet freezing tolerance characteristic indicators, they are fused with the equivalent circuit parameters to generate electrochemical impedance spectroscopy characteristic parameters.

[0019] Optionally, the meat quality characteristics include muscle fiber density, intercellular space ratio, and bound water percentage; the step of determining the freeze compatibility grade based on the meat quality characteristics includes:

[0020] The muscle fiber density is compared with a preset muscle fiber density gradient range to determine the muscle fiber density level;

[0021] The intercellular gap ratio is compared with a preset intercellular gap ratio gradient range to determine the intercellular gap ratio level;

[0022] The bound water percentage is compared with a preset bound water percentage gradient range to determine the bound water percentage level.

[0023] The muscle fiber density level, the intercellular space ratio level, and the bound water ratio level are used to perform a comprehensive score based on their respective preset weights, and the cryogenic compatibility level is determined according to the comprehensive score.

[0024] Among them, the muscle fiber density is positively correlated with the cryofitness level, the intercellular gap ratio is negatively correlated with the cryofitness level, the bound water ratio is positively correlated with the cryofitness level, and the preset weight corresponding to the muscle fiber density is the highest.

[0025] Optionally, the step of configuring corresponding freezing process conditions according to the freezing compatibility level to obtain a complete freezing process parameter package includes:

[0026] Based on the target freezing rate curve, quick-freezing temperature, quick-freezing wind speed, segmented freezing parameters, and the time it takes for the maximum ice crystal formation zone to pass through, corresponding to the freezing compatibility level, the initial process configuration data is obtained.

[0027] Using the meat quality characteristic parameters as an index, a preset calibration coefficient is retrieved to correct the target freezing rate curve and the maximum ice crystal formation zone passage time in the initial process configuration data, thereby generating the target process configuration data.

[0028] The target process configuration data is encapsulated to generate a complete freezing process parameter package.

[0029] Optionally, the step of adaptively adjusting the refrigeration operation parameters of the quick-freezing equipment based on the temperature time-series data and the meat quality basic attribute data corresponding to the electrochemical impedance spectroscopy characteristic parameters pre-stored in the full-cycle control tag includes:

[0030] Based on the temperature time series data, calculate the maximum ice crystal formation zone passage time and cooling rate fluctuation value;

[0031] The equivalent diameter and distribution density of ice crystals are calculated using the maximum ice crystal formation zone passage time and the cooling rate fluctuation value.

[0032] Retrieve the basic meat quality attribute data corresponding to the electrochemical impedance spectroscopy characteristic parameters pre-stored in the full-cycle management tag;

[0033] Based on the meat quality basic attribute data, the equivalent diameter of the ice crystals, and the distribution density, the adjustment threshold and adjustment range are determined, and the refrigeration operation parameters are adjusted in steps within the adjustable range of the refrigeration output load of the quick-freezing equipment.

[0034] By comparing the difference between the actual freezing rate of the adjusted quick-freezing equipment and the target freezing rate curve, freezing rate deviation data is generated.

[0035] Optionally, the step of writing the quick-freezing adjustment record to the full-cycle management tag after the quick-freezing is completed includes:

[0036] Using equipment adjustment data, maximum ice crystal formation zone passage time, cooling rate fluctuation value, and freezing rate deviation data during the quick-freezing process, a quick-freezing adjustment record is constructed and temporarily stored in the cache unit of the quick-freezing equipment;

[0037] After the quick-freezing is completed and the production turnover carrier is removed from the low-temperature environment, the temporarily stored quick-freezing adjustment record is written into the full-cycle management tag.

[0038] Optionally, the quick-freezing condition characteristics include the temperature fluctuation range, refrigeration parameter adjustment frequency, and refrigeration parameter adjustment range throughout the quick-freezing process; the step of matching the corresponding cold chain management method and terminal thawing control data based on the inherent physical properties of the fish fillets corresponding to the full-cycle management and control tags associated with the batch after quick-freezing and the quick-freezing condition characteristics includes:

[0039] Based on the inherent properties of the fish fillets, the matching categories of cold chain management methods and terminal thawing control data are determined.

[0040] Under the matching category, based on the temperature fluctuation range and the refrigeration parameter adjustment frequency, the cold chain temperature benchmark and allowable fluctuation range are determined, and a cold chain management method is constructed.

[0041] Based on the adjustment range of the cooling parameters, the step-by-step temperature increase range and temperature increase interval are determined, and the terminal defrosting control data is constructed.

[0042] Optionally, the method further includes:

[0043] After quick-freezing, the quality evaluation data of the batch of fish fillets after thawing is collected and correlated with the electrochemical impedance spectroscopy characteristic parameters and quick-freezing adjustment records stored in the full-cycle management label, and the correspondence between impedance and meat quality in the correlation table is iteratively updated.

[0044] A second aspect of the present invention provides a quality improvement system for frozen fish fillets, comprising:

[0045] The electrochemical impedance spectroscopy (EIS) detection module is used to extract representative samples from the same batch of fish fillets to be quick-frozen after the fish fillets have been sliced ​​and are about to enter the quick-freezing process, and to construct the characteristic parameters of the electrochemical impedance spectroscopy of the batch of fish fillets.

[0046] The freezing compatibility level determination module is used to match the meat quality characteristic parameters corresponding to the electrochemical impedance spectroscopy characteristic parameters based on the impedance and meat quality correlation table pre-established in the production line, and determine the freezing compatibility level based on the meat quality characteristic parameters.

[0047] The full-cycle management tag generation module is used to configure the corresponding freezing process conditions according to the freezing adaptability level, obtain the full-process freezing process parameter package, and associate and store the identification codes of the key parameters of the full-process freezing process parameter package and the electrochemical impedance spectroscopy characteristic parameters to the radio frequency identification temperature sensing tag carried on the corresponding production turnover carrier before quick freezing begins, so as to obtain the full-cycle management tag.

[0048] The quick-freezing execution and temperature acquisition module is used to quick-freeze the fish fillets in the batch bound by the full-cycle control tag according to the target freezing rate in the full-process freezing process parameter package, and simultaneously acquire the temperature time series data of the environment in which the fish fillets are located during the quick-freezing process.

[0049] The quick-freezing control and recording module is used to adaptively adjust the refrigeration operation parameters of the quick-freezing equipment based on the temperature time series data and the basic meat quality attribute data corresponding to the electrochemical impedance spectroscopy characteristic parameters pre-stored in the full-cycle control tag. After the quick-freezing is completed, the quick-freezing adjustment record is written into the full-cycle control tag.

[0050] The cold chain and thawing matching module is used to match the inherent physical properties of the fish fillets corresponding to the full-cycle management and control tags associated with the batch after quick-freezing, as well as the characteristics of the quick-freezing conditions, to obtain the corresponding cold chain management and control methods and terminal thawing control data.

[0051] A third aspect of the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the method for improving the quality of frozen fish fillets as described above.

[0052] As can be seen from the above technical solutions, the present invention has the following advantages:

[0053] This invention first involves extracting representative samples from the same batch of fish fillets before they enter the quick-freezing process. Electrochemical impedance spectroscopy (EIS) is then performed to detect these samples and construct characteristic EIS parameters for that batch. Next, based on a pre-established impedance-meat quality correlation table on the production line, corresponding meat quality parameters are matched to determine the freezing compatibility level. A complete freezing process parameter package is then configured according to this level, and before quick-freezing begins, the key parameters of the parameter package and the identification codes of the EIS characteristic parameters are associated and stored in a radio frequency identification (RFID) temperature sensor tag mounted on the production transport carrier to obtain a full-cycle management tag. During quick-freezing, the bound batch of fish fillets is quick-frozen according to the target freezing rate in the parameter package, and temperature time-series data is collected simultaneously. The refrigeration operation parameters of the quick-freezing equipment are adaptively adjusted based on the pre-stored basic meat quality attribute data on the tag. After quick-freezing, the adjustment record is written to the tag. Finally, based on the inherent physical properties of the fish fillets corresponding to the tag and the characteristics of the quick-freezing conditions, the corresponding cold chain management method and terminal thawing control data are obtained. This method achieves accurate prediction of the freezing tolerance of each batch of fish fillets by online non-destructive testing of their cellular electrochemical properties. Based on this, it tailors a complete process parameter chain, from quick-freezing rate and dynamic adjustment of refrigeration parameters to cold chain storage temperature and even thawing curve. This proactively controls the nucleation size and distribution uniformity of ice crystals during quick-freezing, further optimizes temperature fluctuation range and heating / cooling procedures based on actual freezing conditions in the cold chain, and finally minimizes juice loss and cell structure damage during thawing through staged heating. Compared to the extensive approach of existing technologies that use uniform freezing parameters and lack full-cycle coordinated control, this invention effectively inhibits abnormal ice crystal growth throughout the freezing, storage, transportation, and thawing process, maintains the integrity of the multi-level structure of fish tissue from cell membrane integrity to macroscopic texture, reduces thawing juice loss, and improves the water-holding capacity, color, and consistency of taste of frozen fish fillets. Thus, it systematically solves the technical challenge of existing frozen fish fillet processing and preservation methods failing to inhibit abnormal ice crystal growth and ensure core quality standards throughout the entire process. Attached Figure Description

[0054] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0055] Figure 1 A flowchart illustrating the steps of a method for improving the quality of frozen fish fillets according to Embodiment 1 of the present invention;

[0056] Figure 2 This is a flowchart illustrating the steps of a method for improving the quality of frozen fish fillets according to Embodiment 2 of the present invention.

[0057] Figure 3 This is a structural block diagram of a quality improvement system for frozen fish fillets provided in Embodiment 4 of the present invention;

[0058] Figure 4 This is a structural block diagram of an electronic device provided in Embodiment 5 of the present invention. Detailed Implementation

[0059] This invention provides a method for improving the quality of frozen fish fillets, which solves the technical problem that existing frozen fish fillet processing and preservation methods cannot inhibit abnormal ice crystal growth and maintain the integrity of fish meat tissue structure throughout the freezing and refrigeration cycle, resulting in substandard core quality of frozen fish fillets.

[0060] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. 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. It should be noted that in the optional embodiments of the present invention, the object information and other related data involved require the permission or consent of the object when the embodiments of the present invention are applied to specific products or technologies, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. That is to say, if the embodiments of the present invention involve data related to the object, it needs to be obtained with the authorization and consent of the object, the authorization and consent of the relevant departments, and in compliance with the relevant laws, regulations, and standards of the country and region. If personal information is involved in the embodiments, the acquisition of all personal information requires the consent of the individual. If sensitive information is involved, the separate consent of the information subject is required, and the embodiments also need to be implemented with the authorization and consent of the object.

[0061] Example 1

[0062] Please see Figure 1 , Figure 1 This is a flowchart illustrating the steps of a method for improving the quality of frozen fish fillets according to Embodiment 1 of the present invention.

[0063] This invention provides a method for improving the quality of frozen fish fillets, comprising:

[0064] Step 101: After the fish fillets are sliced ​​and ready to enter the quick-freezing process, representative samples are extracted from the same batch of fish fillets to be quick-frozen for electrochemical impedance spectroscopy detection to construct the characteristic parameters of the electrochemical impedance spectroscopy of this batch of fish fillets.

[0065] It should be noted that the electrochemical impedance spectroscopy (EIS) detection in this invention is a batch-level detection performed on the entire batch of fish fillets, rather than detecting each individual fillet after slicing. Specifically, after the slicing process is completed, representative samples are taken from all fish fillets corresponding to the same raw material batch according to a preset sampling rule (e.g., randomly selecting 3-5 fillets from each batch, or selecting 1%-3% of the total weight of each batch). The samples are placed at the detection station for impedance spectroscopy detection. The electrochemical impedance spectroscopy characteristic parameters constructed based on the sample detection results are used as representative characteristic parameters of the entire batch of fish fillets for subsequent freezing compatibility level determination and process parameter configuration. Through the above batch-level sampling detection method, the statistical representativeness of the detection results is ensured, while avoiding the production efficiency loss and increased equipment cost caused by piece-by-piece detection, thus meeting the needs of large-scale mass production.

[0066] In this embodiment of the invention, at the detection station where the fish fillets remain after slicing and before quick-freezing, a surface contact multi-electrode array is used to perform in-situ detection on the extracted fish fillets, acquiring the original impedance response signal. This ensures the real-time and non-destructive nature of the detection. By eliminating invalid interference from environmental humidity and free water on the surface of the fish fillets in the original signal, the influence of the production environment on the detection accuracy is resolved. By eliminating electrochemical response signals outside the preset frequency range, the focus is on the effective frequency band most relevant to changes in cell structure. Spectral analysis is performed on the screened signals to extract multiple characteristic indicators of fish fillet freezing tolerance. The target electrochemical response signal is fitted using a preset equivalent circuit model to extract three core equivalent circuit parameters: extracellular fluid resistance, cell membrane capacitance, and intracellular fluid resistance. These parameters directly reflect the cell integrity of the fish fillets. All extracted fish fillet freezing tolerance characteristic indicators and equivalent circuit parameters are normalized and fused to finally generate an electrochemical impedance spectral characteristic parameter that can comprehensively characterize the freezing tolerance of fish fillets.

[0067] Step 102: Based on the impedance and meat quality correlation table pre-established in the production line, match the meat quality characteristic parameters corresponding to the electrochemical impedance spectroscopy characteristic parameters, and determine the freezing suitability level based on the meat quality characteristic parameters.

[0068] It should be noted that the specific process for establishing the impedance-meat quality correlation table is as follows: Representative batches of fish fillets are sampled, and their electrochemical impedance spectroscopy characteristic parameters (obtained according to step 101) and corresponding meat quality parameters are measured simultaneously (muscle fiber density is determined by tissue section image analysis, intercellular gap ratio is determined by scanning electron microscopy image processing, and bound water ratio is determined by low-field nuclear magnetic resonance or differential scanning calorimetry). The measured data are divided into several intervals according to the characteristic parameter value range, and the typical value range of meat quality parameters and corresponding comprehensive scores within each interval are statistically analyzed to form a one-to-one impedance-meat quality correlation table. This table can be stored in the production line control system. During actual testing, the electrochemical impedance spectroscopy characteristic parameters of the current fish fillet are input into the table for matching (if the parameter value falls within a certain interval, the typical or predicted value of the corresponding meat quality parameter for that interval is output), thereby obtaining the meat quality parameters (muscle fiber density, intercellular gap ratio, bound water ratio) corresponding to the current fish fillet. Since the meat quality characteristics may differ between fish species and production seasons, this table can be updated periodically based on actual production data or multiple versions can be maintained for different fish species.

[0069] In this embodiment of the invention, after obtaining three parameters—muscle fiber density, intercellular space ratio, and bound water percentage—this step determines the cryogenic compatibility level based on the intrinsic correlation between each parameter and cryogenic tolerance. Higher muscle fiber density indicates denser muscle tissue, resulting in less mechanical damage to fibers from ice crystals during freezing; therefore, it is positively correlated with cryogenic compatibility level. A larger intercellular space ratio indicates larger gaps between cells, making it easier for ice crystals to grow and expand within these gaps, thus damaging the tissue structure; therefore, it is negatively correlated with cryogenic compatibility level. A higher bound water percentage indicates more water tightly bound to non-aqueous components in the fish fillet; this water is less likely to form ice crystals during freezing, which helps protect cell structure; therefore, it is also positively correlated with cryogenic compatibility level. This step compares these three measured parameters with preset gradient intervals (e.g., pre-dividing the numerical ranges corresponding to "high," "medium," and "low" levels for each parameter) to obtain their respective level scores. Then, a weighted comprehensive score is calculated according to preset weights (with muscle fiber density having the highest weight), ultimately mapping the comprehensive score to several discrete cryogenic compatibility levels.

[0070] Step 103: Configure the corresponding freezing process conditions according to the freezing compatibility level to obtain the full-process freezing process parameter package. Before the quick-freezing starts, associate and store the identification codes of the key parameters and electrochemical impedance spectroscopy characteristic parameters of the full-process freezing process parameter package with the RFID temperature sensing tag carried on the corresponding production turnover carrier to obtain the full-cycle management tag.

[0071] It should be noted that the freezing compatibility level and full-process freezing parameter package determined based on representative samples of the batch are applicable to all fish fillets in that entire batch. Before quick-freezing begins, the production line control system writes the key parameters and characteristic parameter identification codes of this parameter package into the RFID temperature sensor tag carried by the production transport carrier containing the fish fillets of that batch. This tag circulates with the transport carrier, serving as the basis for unified control of the fish fillets of that batch throughout the entire cycle of quick-freezing, cold chain, and thawing. If the same production transport carrier carries multiple batches of fish fillets, a separate tag must be configured for each batch and the corresponding differentiated parameter package must be written into it to ensure that the control accuracy between batches is not affected.

[0072] In this embodiment of the invention, the specific generation process of the full-process freezing parameter package is as follows: The production line control system pre-stores benchmark freezing process parameter templates corresponding to different freezing compatibility levels. After step 102 outputs the freezing compatibility level, the production line control system automatically matches the initial process configuration data corresponding to that level, including the target freezing rate, quick-freezing temperature, quick-freezing air velocity, segmented freezing parameters, and the allowable passage time of the maximum ice crystal formation zone. Taking a high compatibility level as an example, a relatively mild freezing rate and a higher quick-freezing temperature can be used; a low compatibility level requires a faster freezing rate and a lower quick-freezing temperature to quickly pass through the maximum ice crystal formation zone. Based on this, the meat quality characteristic parameters (muscle fiber density, intercellular gap ratio, and bound water ratio) obtained in step 102 are used as an index to retrieve preset calibration coefficients and correct the target freezing rate and the allowable passage time of the maximum ice crystal formation zone in the initial process configuration data. For example, when the intercellular gap ratio is too high, the target freezing rate is appropriately increased and the allowable passage time of the ice crystal formation zone is shortened; when the bound water ratio is too high, the requirements can be appropriately relaxed. The corrected target process configuration data, after being packaged, yields the complete freezing process parameter package.

[0073] Before quick-freezing begins, the production line control system associates and stores the key parameters (at least the target freezing rate, quick-freezing temperature, and maximum allowable passage time of the ice crystal formation zone) from the entire freezing process parameter package, along with the identification codes of the electronic impedance spectral characteristic parameters generated in step 101, into the user storage area of ​​the RFID temperature sensing tag mounted on the corresponding production transport carrier. This tag has temperature sensing and wireless read / write capabilities, and its storage capacity is sufficient to hold the aforementioned key parameters and identification codes. After association and storage, the tag is bound to the fish fillet batch, forming a full-cycle management tag that circulates with the production transport carrier, thereby achieving full-process quality traceability and dynamic control from quick-freezing processing to cold chain transportation and final thawing. Through the above configuration and storage operations, this step transforms the freezing compatibility level into an executable, personalized freezing process parameter package and electronically binds it to the fish fillet identification, providing a complete data foundation for parameter execution, temperature monitoring, refrigeration adjustment, and cold chain thawing scheme matching during the subsequent quick-freezing process.

[0074] Step 104: Quick-freeze the fish fillets in the batch bound to the full-cycle control tag according to the target freezing rate in the full-process freezing process parameter package, and simultaneously collect the temperature time series data of the environment in which the fish fillets are located during the quick-freezing process.

[0075] It should be noted that the target freezing rate is an achievable engineering setting, not a requirement for the quick-freezing equipment to precisely track an ideal curve. Production line quick-freezing equipment (such as tunnel freezers or plate freezers) is typically equipped with a programmable temperature controller. Operators or the production line control system convert the target freezing rate into the corresponding quick-freezing temperature (e.g., when the target freezing rate is 5℃ / min, the quick-freezing temperature is set to -35℃; when the target freezing rate is 3℃ / min, the quick-freezing temperature is set to -25℃), or directly adjust parameters such as compressor frequency and fan speed to make the actual freezing rate approach the target value.

[0076] In this embodiment of the invention, during the quick-freezing process, the production line control system synchronously collects time-series temperature data of the environment in which the fish fillets are located. Temperature acquisition can be achieved in two ways: First, by utilizing the temperature sensing function built into the full-cycle management tag, the temperature sensor built into the tag records the ambient temperature according to a preset sampling period (e.g., once every 10 seconds) and temporarily stores the timestamp and temperature value in the tag's memory; second, by arranging multiple fixed temperature probes along the material conveying direction inside the quick-freezing equipment, the probe signals are connected to the production line control system, and the production line control system records the temperature values ​​of each monitoring point in chronological order. The collected time-series temperature data includes at least the time point and its corresponding temperature value (in °C), which is used for subsequent calculation of key parameters such as the actual passage time of the maximum ice crystal formation zone and the fluctuation value of the cooling rate.

[0077] Step 105: Based on the temperature time series data and the basic meat quality attribute data corresponding to the electrochemical impedance spectroscopy characteristic parameters pre-stored in the full-cycle management tag, make adaptive adjustments to the refrigeration operation parameters of the quick-freezing equipment. After the quick-freezing is completed, write the quick-freezing adjustment record into the full-cycle management tag.

[0078] It should be noted that the production line control system calculates the deviation between the current actual cooling rate and the target freezing rate based on temperature time-series data, and combines this with basic meat quality attribute data (such as poor tolerance due to high intercellular gap ratio, requiring stricter control) to determine whether adjustments are needed and by how much. For example, when the actual cooling rate is significantly lower than the target value, the control system can increase the fan speed by one level or lower the quick-freezing temperature by one level; when the actual cooling rate is close to the target value, the current parameters remain unchanged. After each adjustment, the production line control system continues to monitor temperature changes and determines the next adjustment based on the deviation. This step-by-step, step-by-step adjustment method can be fully implemented in the control systems of existing commercial quick-freezing equipment without requiring additional hardware modifications.

[0079] In this embodiment of the invention, based on the temperature time-series data collected in step 104 and the basic meat quality attribute data pre-stored in the full-cycle management tag, the refrigeration operation parameters of the quick-freezing equipment are adaptively adjusted to make the actual freezing process as close as possible to the pre-set target freezing rate, thereby optimizing the frozen quality. After quick-freezing is completed, the relevant records of this adjustment are written into the full-cycle management tag for subsequent traceability and analysis.

[0080] Step 106: Based on the inherent physical properties of the fish fillets corresponding to the full-cycle management and control tags associated with the batch after quick-freezing and the characteristics of quick-freezing conditions, the corresponding cold chain management and control methods and terminal thawing control data are matched to obtain the corresponding data.

[0081] In this embodiment of the invention, after quick-freezing is completed, the production line control system reads two types of information from the full-cycle management tag: the first type is the inherent physical properties of the fish fillets, namely the meat quality characteristic parameters obtained in step 102, which reflect the fish fillets' own freezing tolerance; the second type is the quick-freezing condition characteristics, namely the temperature fluctuation range, refrigeration parameter adjustment frequency and refrigeration parameter adjustment range contained in the quick-freezing adjustment record written in step 105, which reflect the actual quick-freezing process experienced by the fish fillets.

[0082] The matching process follows this logic: Based on the inherent physical properties of the fish fillets, such as muscle fiber density and bound water percentage, the fillets are divided into three main categories: high tolerance (high muscle fiber density and high bound water percentage), medium tolerance (moderate in both indicators), and low tolerance (low in both indicators). Each category corresponds to a set of cold chain management benchmark requirements and thawing control benchmark requirements. After determining the matching categories, the cold chain management methods are further adjusted and refined based on the characteristics of the quick-freezing conditions. Specifically, the temperature fluctuation range (i.e., the difference between the highest and lowest temperatures during quick-freezing, in °C) and the frequency of refrigeration parameter adjustments (i.e., the total number of step-by-step adjustments performed during quick-freezing) are extracted from the quick-freezing adjustment records. A larger temperature fluctuation range or a higher adjustment frequency indicates a more unstable quick-freezing process, and uneven growth of ice crystals inside the fish fillets may occur. Therefore, stricter temperature control is required in the cold chain as compensation. Based on the above two parameters, further adjustments are made above and below the benchmark cold chain temperature for the matching category: if the temperature fluctuation range exceeds the preset threshold (e.g., 5℃) or the adjustment frequency exceeds the preset number of times (e.g., 3 times), the target cold chain temperature is reduced by 1 to 2℃, and the allowable fluctuation range is narrowed to ±1℃; if the quick-freezing condition is stable, the benchmark cold chain requirements are maintained.

[0083] For terminal thawing control data, the step-by-step heating amplitude and interval are mainly determined based on the adjustment range of the refrigeration parameters in the quick-freezing condition characteristics (i.e., the average or maximum value of each step adjustment level). A larger adjustment range indicates that the fish fillets experienced more intense freezing conditions during quick-freezing; the ice crystals may be finer, but the cells may also have experienced greater stress. Therefore, a gentler, step-by-step heating program is required during thawing. The adjustment levels are mapped to thawing parameters as follows: when the average adjustment range is level 1, two-stage thawing is used; when the average adjustment range is level 2, three-stage thawing is used; and when the average adjustment range is level 3, four-stage thawing is used. The above mapping relationship can be calibrated based on experimental data for different fish species, but this step does not limit the specific values.

[0084] Example 2

[0085] Please see Figure 2 , Figure 2 This is a flowchart illustrating the steps of a method for improving the quality of frozen fish fillets according to Embodiment 2 of the present invention.

[0086] Step 201: After the fish fillets are sliced ​​and ready to enter the quick-freezing process, representative samples are extracted from the same batch of fish fillets to be quick-frozen for electrochemical impedance spectroscopy detection to construct the characteristic parameters of the electrochemical impedance spectroscopy of this batch of fish fillets.

[0087] Further, step 201 includes the following steps:

[0088] S11. At the detection station with a dwell function where the fish fillets have been sliced ​​and are about to enter the quick-freezing process, a surface contact multi-electrode array is used to sample and perform in-situ electrochemical impedance spectroscopy detection on the fish fillets of the same production batch to be quick-frozen, and the original electrochemical response signal is collected.

[0089] In this embodiment of the invention, a detection station with a dwell function is set up at the stage where fish fillets are sliced ​​and ready to enter the quick-freezing process. It is important to emphasize that this step uses batch-level sampling detection, rather than inspecting each sliced ​​fish fillet individually. Specifically, after the slicing process is completed, representative samples are drawn from the same production batch according to preset sampling rules, and the selected sample fish fillets are placed at the detection station for testing. At this station, a surface contact multi-electrode array (e.g., flexible printed electrodes or interdigitated electrodes certified for food contact compliance, made of food-grade stainless steel compliant with FDA / EC regulations) is non-invasively attached to the surface of the selected sample fish fillets, without direct contact with the internal tissue of the fish fillets. During detection, a small AC excitation signal with a frequency scanning range of 1Hz to 100kHz and a voltage amplitude ≤50mV is applied. By adjusting the frequency, impedance information at different detection depths can be obtained, and the response current and voltage phase difference flowing through the fish fillet tissue are collected, thereby obtaining the original electrochemical response signal. This signal contains impedance modulus and phase angle information at different frequencies.

[0090] S12. Remove invalid interference signals caused by ambient humidity and free water on the surface of the fish fillet from the original electrochemical response signal to generate an intermediate electrochemical response signal.

[0091] In this embodiment of the invention, ambient humidity introduces a parallel capacitance effect between the electrode and the fish fillet. Surface free moisture generates a characteristic low-impedance, large-phase-drift response in the low-frequency range (typically <10Hz). These components do not reflect the true electrical properties of the fish fillet's internal structure but severely interfere with the accuracy of freezing tolerance evaluation. Therefore, this step employs an adaptive filtering algorithm based on the fish fillet's intrinsic impedance characteristics. The production line control system first reads the stable low-frequency range... The estimated value, the dynamically generated signal retention threshold, and the corresponding dynamic signal rejection threshold are calculated using the following formula:

[0092] ;

[0093] in, The threshold for dynamic rejection is in V. Signals with amplitudes below this value are considered surface free water interference signals and must be removed from the original signal. The coefficient 0.85 is an empirical constant calibrated based on a large amount of experimental data. This is the impedance normalization factor, used to quantify the contribution of surface moisture to the total impedance. When the amount of free water on the surface of the fish fillet increases, this ratio approaches 1, and the threshold is automatically raised to retain more effective signals. Extracellular fluid resistance, i.e., the resistance of the external environment of the cell; This is the equivalent DC leakage resistance at low frequencies, i.e., the resistance of the cell membrane itself; The amplitude of the original electrochemical response signal is used as the basic input signal for dynamic threshold calculation.

[0094] When the amplitude of the original electrochemical response signal is acquired Below this dynamic rejection threshold When the signal is determined to be a short-circuit effect caused by surface free water, it is eliminated. After eliminating all invalid interference signals, the intermediate electrochemical response signal is obtained.

[0095] S13. Remove electrochemical response signals that are not within the preset frequency range from the intermediate electrochemical response signals, and generate the target electrochemical response signal.

[0096] In this embodiment of the invention, an adaptive characteristic frequency band selection algorithm is introduced for different fish species and different physiological states. First, the rate of change curve of the imaginary part of the intermediate electrochemical response signal as a function of frequency is calculated. The frequency corresponding to the peak of the rate of change is taken as the center point of the characteristic frequency, and the upper and lower boundaries corresponding to the rate of change decreasing to 30% of the peak value are taken as the effective frequency interval. The quantitative calculation formula for the interval boundary is:

[0097] ;

[0098] ;

[0099] in, This represents the imaginary part of the impedance at frequency f; It is the first derivative of the imaginary part of the impedance with respect to frequency, reflecting the sensitivity of cell membrane capacitance and extracellular fluid resistance to frequency changes; This is the attenuation threshold coefficient calibrated based on a large amount of experimental data from frozen fish fillets. The preset frequency range determined accordingly is […]. , The typical experimental statistical range is 10 Hz to 10 kHz. The intermediate electrochemical response signal with frequencies lower than […] is considered. or higher Data points are discarded, and signals within the specified intervals are retained to generate the target electrochemical response signal. This adaptive interval maximizes the sensitivity of extracellular fluid resistance and cell membrane capacitance to changes in freezing tolerance, avoiding the introduction of invalid or interfering frequency components due to differences in fish species or freshness within the fixed interval.

[0100] S14. Perform spectral analysis and impedance feature extraction on the target electrochemical response signal to obtain multiple fish fillet freezing tolerance characteristic indicators.

[0101] In this embodiment of the invention, spectrum analysis refers to calculating the impedance magnitude at each retained frequency point. and the virtual part Four characteristic indicators directly related to cryogenic tolerance were extracted from these indicators. The calculation formulas for each indicator are as follows:

[0102] (1) Characteristic frequency

[0103] ;

[0104] (2) Low-frequency impedance mode

[0105] ;

[0106] (3) High-frequency impedance mode

[0107] ;

[0108] (4) Peak value of the imaginary part of impedance

[0109] ;

[0110] in, The characteristic frequency, measured in Hz, corresponds to the frequency at which the imaginary part of the impedance reaches its maximum value. It reflects the charging and discharging characteristics of the cell membrane. A decrease usually means an increase in cell membrane capacitance (cell swelling or increased membrane area), indicating a decline in cryotolerance; For frequency; For the preset frequency range; For frequency The imaginary part of the impedance, in Ω, is the orthogonal component of the electrochemical impedance spectroscopy and is sensitive to changes in cell membrane capacitance. The low-frequency impedance mode is the average value of the impedance mode in the low-frequency range (1-10Hz), and the unit is Ω. It reflects the conductivity of the extracellular fluid pathway and the overall integrity of the cell. The number of measurement frequency points in the frequency range of 1Hz to 10Hz is dimensionless and used to calculate the arithmetic mean. This represents the impedance magnitude at frequency f, in Ω. To accumulate the impedance modes at discrete frequency points in the range of 1Hz to 10Hz; The high-frequency impedance mode is the average value of the impedance mode in the high-frequency band (10-100kHz), and the unit is Ω. It mainly reflects the conductivity of intracellular fluid and organelles. The number of measurement frequency points in the frequency range of 10 to 100 kHz; The maximum value of the imaginary part of the impedance within the effective frequency range is called the peak value of the imaginary part of the impedance, which is expressed in Ω and reflects the magnitude of the transmembrane ion gradient.

[0111] The four indicators mentioned above correspond to the four physical dimensions of freezing tolerance: cell membrane integrity, intracellular and extracellular fluid distribution, osmotic pressure buffering capacity, and risk of leakage of contents after mechanical damage. Through the above calculations, multiple characteristic indicators of fish fillet freezing tolerance were obtained.

[0112] S15. Fit the target electrochemical response signal using a preset equivalent circuit model and extract equivalent circuit parameters including extracellular fluid resistance, cell membrane capacitance, and intracellular fluid resistance.

[0113] In this embodiment of the invention, the preset equivalent circuit model is a three-element Randle circuit (extracellular fluid resistor). Cell membrane capacitance Intracellular fluid resistance (in series), its total impedance varies with frequency The expression for the change is:

[0114] ;

[0115] The target electrochemical response signal was analyzed using the complex nonlinear least squares method. To perform the fitting, the objective function is:

[0116] ;

[0117] To ensure that the fitting results have clear physiological significance and conform to the physical characteristics of fish fillet tissue, the following physical constraints are forcibly introduced in this step:

[0118] >0, >0, >0 (all component values ​​are positive);

[0119] (Experience-based ratio ranges for major export fish species such as tilapia and salmon).

[0120] The magnitude ranges from 0.1 to 10 μF (depending on the electrode contact area).

[0121] If the fitting result exceeds the above constraints, the algorithm automatically increases the regularization coefficient or adjusts the initial value to refit until the constraints are met or the maximum number of iterations (e.g., 10) is reached. The three final extracted equivalent circuit parameters are: extracellular fluid resistance... Cell membrane capacitance Intracellular fluid resistance These parameters respectively characterize the intercellular fluid conductivity, cell membrane integrity, and cytoplasmic leakage, complementing the characteristic indicators in S14, and together constitute the core parameter set for evaluating cryotolerance.

[0122] S16. After normalizing all the freezing tolerance characteristic indicators of fish fillets, they are fused with the equivalent circuit parameters to generate electrochemical impedance spectroscopy characteristic parameters.

[0123] In this embodiment of the invention, the four fish fillet freezing tolerance characteristic indicators (characteristic frequency, low-frequency impedance mode, high-frequency impedance mode, and peak value of the imaginary part of impedance) obtained in S14 are fused with the three equivalent circuit parameters (extracellular fluid resistance, cell membrane capacitance, and intracellular fluid resistance) obtained in S15 to generate an electrochemical impedance spectroscopy characteristic parameter that can comprehensively characterize the freezing tolerance of fish fillets. First, normalization is performed: for the above seven parameters, the original measured values ​​are linearly mapped to the dimensionless [0, 1] interval according to the physical boundaries obtained from offline calibration (i.e., the lower limit of the "excellent freezing tolerance" level and the upper limit of the "poor freezing tolerance" level). The larger the mapped value, the greater the positive contribution of the indicator to freezing tolerance. For indicators that are originally negatively correlated with tolerance (such as the peak value of the imaginary part of impedance and extracellular fluid resistance), the reciprocal is taken or a subtraction transformation is used during normalization to ensure that the physical direction of all normalized values ​​is consistent. A weighted fusion was then performed: based on the regression contribution of each indicator to quality results such as the juice loss rate and average ice crystal diameter of the quick-frozen fish fillets, weight coefficients were assigned to the seven normalized indicators, with the sum of all weights being 1. Cell membrane capacitance and intracellular fluid resistance were given higher weights because they directly reflect cell membrane integrity; characteristic frequency and imaginary peak value were given medium weights; and low-frequency impedance mode, high-frequency impedance mode, and extracellular fluid resistance were given lower weights. Each normalized indicator was multiplied by its corresponding weight and then summed to obtain a dimensionless comprehensive index between 0 and 1, namely the electrochemical impedance spectroscopy characteristic parameter. This parameter directly quantifies the freezing tolerance of the fish fillets to be quick-frozen; a higher value indicates better tolerance.

[0124] Step 202: Based on the impedance and meat quality correlation table pre-established in the production line, match the meat quality characteristic parameters corresponding to the electrochemical impedance spectroscopy characteristic parameters, and determine the freezing suitability level based on the meat quality characteristic parameters.

[0125] Furthermore, meat quality parameters include muscle fiber density, intercellular space ratio, and bound water content. Step 202 includes the following steps:

[0126] S21. Compare the muscle fiber density with the preset muscle fiber density gradient range to determine the muscle fiber density level.

[0127] It should be noted that muscle fiber density refers to the number of muscle fibers per unit area, measured in roots per square millimeter. The higher the muscle fiber density, the denser the muscle tissue, the less damage ice crystals cause to the muscle fibers during freezing, and the better the freezing tolerance. Therefore, muscle fiber density is positively correlated with freezing compatibility level.

[0128] In this embodiment of the invention, the production line establishes a preset muscle fiber density gradient range in advance through offline experiments. A large number of representative fish fillet samples are taken, and the muscle fiber density of each sample is measured. Simultaneously, the actual freezing tolerance of each sample is determined through a quick-freezing experiment. Based on the tolerance distribution, the muscle fiber density is divided into three gradient ranges: the low-density range is defined as: muscle fiber density < The medium-density region is: ≤muscle fiber density< High-density areas are defined as areas with muscle fiber density ≥ .in, and The threshold for muscle fiber density, calibrated experimentally, is expressed in roots per square millimeter. Defined as the cutoff threshold between "low tolerance" and "moderate tolerance". Defined as the dividing threshold between "moderate tolerance" and "high tolerance". The specific calibration method is as follows: A large number of representative fish fillet samples are taken. While measuring the muscle fiber density of each sample, the juice loss rate of each sample is measured using a standard quick-freezing experiment (freezing rate -30℃ / min, core temperature reaching -18℃) to characterize its actual freezing tolerance. All samples are sorted by muscle fiber density from smallest to largest, and the muscle fiber density value corresponding to the 33rd percentile of the cumulative juice loss rate distribution is used as the threshold. The muscle fiber density value corresponding to the 66th percentile was used as... For the main processed fish species such as tilapia, golden pomfret, and basa fish, The typical value is , The typical value is In actual testing, the production line control system obtains the current fish fillet muscle fiber density value obtained from step 102, and compares this value with... and Comparison: If the value < If it is, then it is judged as low-level; if ≤ numerical value < If the value is ≥, it is judged as intermediate; if the value is ≥ If the result is not high, it is classified as advanced. After the comparison is completed, the corresponding muscle fiber density level is output.

[0129] S22. Compare the intercellular gap ratio with the preset intercellular gap ratio gradient range to determine the intercellular gap ratio level.

[0130] It should be noted that the intercellular gap ratio refers to the proportion of the area of ​​the space between cells to the total area of ​​the tissue, expressed as a percentage. The larger the intercellular gap ratio, the larger the space between cells, making it easier for ice crystals to grow in the gaps and tear the cell membrane during freezing, resulting in poorer freeze tolerance. Therefore, the intercellular gap ratio is negatively correlated with the freeze compatibility level.

[0131] In this embodiment of the invention, a preset intercellular gap ratio gradient range is established in advance through offline experiments. A large number of representative fish fillet samples are taken, and the intercellular gap ratio of each sample is measured. Simultaneously, the actual freezing tolerance of each sample is determined through a quick-freezing experiment. Based on the tolerance distribution, the intercellular gap ratio is divided into three gradient ranges: the low gap ratio range is defined as: intercellular gap ratio < The interstitial gap ratio region is: ≤ Intercellular space ratio< The high intercellular gap ratio region is defined as a cell intercellular gap ratio ≥ .in, and This represents the experimentally calibrated gap ratio threshold, expressed as a percentage. Since the gap ratio is negatively correlated with tolerance, a low gap ratio corresponds to a high level, a medium gap ratio to a medium level, and a high gap ratio to a low level. In actual testing, the production line control system acquires the current fish fillet gap ratio value obtained in step 102 and compares this value with… and Comparison: If the value < If it is, then it is judged as high-level; if ≤ numerical value < If the value is ≥, it is judged as intermediate; if the value is ≥ If the result is not satisfactory, it is classified as low-level. After the comparison is completed, the corresponding intercellular gap rate level is output.

[0132] S23. Compare the bound water percentage with the preset bound water percentage gradient range to determine the bound water percentage level.

[0133] It should be noted that the bound water percentage refers to the proportion of water in the muscle of a fish fillet that is tightly bound to non-aqueous components, expressed as a percentage. Bound water is less likely to form ice crystals during freezing, thus protecting cell structure. Therefore, a higher bound water percentage indicates better freezing tolerance and is positively correlated with the freezing compatibility level.

[0134] In this embodiment of the invention, the production line establishes a preset bound water percentage gradient range in advance through offline experiments. A large number of representative fish fillet samples are taken, and the bound water percentage of each sample is measured. Simultaneously, the actual freezing tolerance of each sample is determined through a quick-freezing experiment. Based on the tolerance distribution, the bound water percentage is divided into three gradient ranges: the low bound water range is defined as: bound water percentage < The combined water zone is: ≤Bound water ratio< The high bound water zone is defined as: bound water percentage ≥ .in and This represents the bound water percentage threshold determined experimentally, expressed as a percentage. The bound water percentage levels corresponding to these three intervals are low, medium, and high, respectively. In actual testing, the production line control system acquires the current bound water percentage value of the fish fillet obtained from step 102 and compares this value with… and Comparison: If the value < If it is, then it is judged as low-level; if ≤ numerical value < If the value is ≥, it is judged as intermediate; if the value is ≥ If it is, it is judged as high-level, and the corresponding bound water percentage level is output after the comparison is completed.

[0135] S24. The muscle fiber density level, intercellular space ratio level, and bound water ratio level are used to conduct a comprehensive score based on the corresponding preset weights, and the cryocompatibility level is determined according to the comprehensive score.

[0136] In this embodiment of the invention, a quantitative conversion from level to score is first performed. Let the muscle fiber density level output by S21 be... Its value can be classified as low, medium, or high, corresponding to a rating value. Let the score be: 1 point for low level, 2 points for medium level, and 3 points for high level. Let the intercellular gap rate level output by S22 be... Its value can be classified as low, medium, or high, corresponding to a rating value. Similarly, we set the score as follows: low level = 1 point, medium level = 2 points, high level = 3 points. Let the bound water percentage level of S23 output be... Its value can be classified as low, medium, or high, corresponding to a rating value. Similarly, the scores are set as follows: 1 point for basic level, 2 points for intermediate level, and 3 points for advanced level.

[0137] Then, calculate the overall score G according to the following weighted summation formula:

[0138] ;

[0139] in, , , These are preset weights corresponding to muscle fiber density, intercellular space ratio, and bound water percentage, respectively, to satisfy... + + =1. Muscle fiber density has the most significant impact on cryotolerance, therefore its weight α is the highest. For example, we can assume... =0.5, =0.2, =0.3. The specific weight value can be determined based on the experimental statistical results of different fish species or production lines.

[0140] After calculating the comprehensive score G, compare this score with the preset freezing adaptability level threshold to determine the final freezing adaptability level. Examples of setting the level threshold are as follows: Let the high-level threshold be T1 and the low-level threshold be T2, where T1 > T2. When G ≥ T1, it is determined as a high adaptability level, indicating good freezing tolerance, and a milder freezing process such as a slower freezing rate or a higher quick-freezing temperature can be adopted; when T2 ≤ G < T1, it is determined as a medium adaptability level, indicating medium freezing tolerance, and a standard freezing process is adopted; when G < T2, it is determined as a low adaptability level, indicating poor freezing tolerance, and a more intense freezing process such as a lower quick-freezing temperature and a faster cooling rate is required to quickly pass through the maximum ice crystal formation zone. For example, when the full score of the comprehensive score is 3 points, T1 can be set to 2.5 points and T2 to 1.5 points.

[0141] Through the above comprehensive scoring method, the meat quality characteristic parameters in three dimensions of muscle fiber density level, cell gap rate level, and bound water ratio level are integrated into an intuitive freezing adaptability level. This freezing adaptability level corresponds to the entire inspected batch, and the same process parameters under the same level are adopted for all fish slices in this batch.

[0142] Step 203: Configure the corresponding freezing process conditions according to the freezing adaptability level, obtain the full-process freezing process parameter package, and before the start of quick-freezing, associate and store the identification codes of the key parameters of the full-process freezing process parameter package and the electrochemical impedance spectrum characteristic parameters in the radio frequency identification temperature sensing label carried by the corresponding production turnover carrier to obtain the full-cycle control label.

[0143] Furthermore, step 203 includes the following steps:

[0144] S31: Based on the freezing adaptability level, match the corresponding target freezing rate curve, quick-freezing temperature, quick-freezing wind speed, segmented freezing parameters, and the passing time of the maximum ice crystal formation zone to obtain the initial process configuration data.

[0145] In this embodiment of the invention, based on the freezing compatibility level determined in step 102, corresponding baseline process parameters are matched from the pre-stored process parameter library of the production line control system. A higher freezing compatibility level indicates better freezing tolerance of the fish fillets, allowing for relatively mild freezing conditions; a lower level indicates poorer tolerance, requiring more intense freezing conditions to quickly pass through the maximum ice crystal formation zone. The pre-stored baseline process parameters include: a standard freezing rate curve; quick-freezing temperature (°C); quick-freezing air velocity (m / s); segmented freezing parameters, referring to the target temperature and duration set for the pre-cooling stage, phase change stage, and deep freezing stage, with temperature in °C and time in min for each stage; and the maximum ice crystal formation zone allowable passage time (min), i.e., the maximum time required to traverse the ice crystal formation zone from the initial freezing point of the fish fillets to complete freezing. The production line control system automatically matches the values ​​of the above parameters according to the freezing compatibility level to form initial process configuration data.

[0146] S32. Using meat quality characteristic parameters as an index, retrieve the preset calibration coefficients, correct the target freezing rate curve and the maximum ice crystal formation zone passage time in the initial process configuration data, and generate the target process configuration data.

[0147] In this embodiment of the invention, the initial process configuration data is finely adjusted using the meat quality characteristic parameters obtained in step 102, namely muscle fiber density, intercellular space ratio, and bound water ratio. Since these meat quality characteristic parameters reflect the differences in the microstructure of fish fillet tissue, even with the same freezing compatibility level, fish fillets with different meat quality characteristics still exhibit subtle differences in their sensitivity to ice crystals. Therefore, the production line has pre-established a calibration coefficient lookup table corresponding to different combinations of meat quality characteristic parameters through experiments. In specific operation, the production line control system uses the current values ​​of the three parameters—muscle fiber density, intercellular space ratio, and bound water ratio—as indexes to retrieve the corresponding target freezing rate calibration coefficient from the lookup table. The maximum ice crystal formation zone allows for time calibration coefficients. When the intercellular space ratio is high, >1, used to increase the target freezing rate. <1, used to shorten the allowable transit time; when the bound water content is high. It can be slightly less than 1. Slightly greater than 1, the requirement can be relaxed appropriately. Multiply the initial target freezing rate by... The initial maximum ice crystal formation zone allows passage time multiplied by This yields the corrected target process configuration data.

[0148] S33. Encapsulate the target process configuration data to generate a complete freezing process parameter package.

[0149] In this embodiment of the invention, the modified target process configuration data generated in S32 is packaged according to a predetermined data format to form a structured full-process freezing process parameter package. The packaged content includes at least process parameter identifiers, fish fillet batch information, target freezing rate (unit: °C / min), quick-freezing temperature (unit: °C), quick-freezing air velocity (unit: m / s), segmented freezing parameters, and the maximum allowable passage time of the ice crystal formation zone (unit: min), along with metadata such as parameter effective time. The packaged full-process freezing process parameter package facilitates transmission, parsing, and execution between different processes in the production line and can be directly used to control the operation of the quick-freezing equipment.

[0150] Step 204: Quick-freeze the fish fillets in the batch bound to the full-cycle control tag according to the target freezing rate in the full-process freezing process parameter package, and simultaneously collect the temperature time series data of the environment in which the fish fillets are located during the quick-freezing process.

[0151] In this embodiment of the invention, the content of step 204 is the same as that of step 104, and will not be repeated here.

[0152] Step 205: Based on the temperature time series data and the basic meat quality attribute data corresponding to the electrochemical impedance spectroscopy characteristic parameters pre-stored in the full-cycle management tag, make adaptive adjustments to the refrigeration operation parameters of the quick-freezing equipment. After the quick-freezing is completed, write the quick-freezing adjustment record into the full-cycle management tag.

[0153] Furthermore, step 205 includes the following steps:

[0154] S41. Based on the temperature time series data, calculate the maximum ice crystal formation zone passage time and the cooling rate fluctuation value.

[0155] In this embodiment of the invention, the programmable controller of the quick-freezing equipment operates according to a fixed sampling period. (For example Read temperature sensor values ​​and generate a temperature time series data sequence. The controller searches the sequence for the first time the temperature has reached a certain level. The moment and first time reached The moment The time it takes for the maximum ice crystal formation zone to pass through Unit: min. Cooling rate fluctuation value. The calculation process is as follows: the entire quick-freezing process is divided into continuous fixed-duration windows. , for the Calculate the average cooling rate using a window. ,unit After all windows have been calculated, calculate all... Sample standard deviation ,in, The average cooling rate, The total number of windows, This is the value of the cooling rate fluctuation.

[0156] S42. Calculate the equivalent diameter and distribution density of ice crystals using the maximum ice crystal formation zone passage time and cooling rate fluctuation value.

[0157] In this embodiment of the invention, two empirical comparison tables are pre-stored in the controller's memory. The first table is established by taking representative batches of fish fillet samples and measuring the time it takes for the maximum ice crystal formation zone to pass through under different quick-freezing conditions. Simultaneously, the equivalent diameter of the ice crystals was obtained through cryogenic scanning electron microscopy image analysis. (Unit: mm) and The corresponding relationships are entered into the table. The second table is created in a similar way, recording the cooling rate fluctuation values. With ice crystal distribution density (unit The corresponding relationship is entered into the table. During this step, the controller will input the data calculated by S41... The first table is used as an index, and the result is obtained through table lookup or linear interpolation. ; The cooling rate fluctuation value The second table is used as an index to retrieve the results. .

[0158] S43. Retrieve the basic meat quality attribute data corresponding to the pre-stored electrochemical impedance spectroscopy characteristic parameters in the full-cycle management label.

[0159] In this embodiment of the invention, before the production transport carrier enters the quick-freezing station, the radio frequency identification reader reads the user storage area of ​​the full-cycle management tag and extracts the pre-stored basic meat quality attribute data, such as muscle fiber density. (unit ), intercellular space ratio (Unit: %) and percentage of bound water (Unit: %). The reader transmits these three values ​​to the programmable controller of the quick-freezing equipment via the communication interface, and stores them in the corresponding registers for subsequent steps.

[0160] S44. Based on the basic attributes of meat, the equivalent diameter and distribution density of ice crystals, determine the adjustment threshold and adjustment range, and make step-by-step adjustments to the refrigeration operation parameters within the adjustable range of the refrigeration output load of the quick-freezing equipment.

[0161] In this embodiment of the invention, the controller first... Determine the basic adjustment threshold: when High tolerance threshold group (upper limit of equivalent diameter of ice crystals) is called at the time. Lower limit of ice crystal distribution density ),when When the tolerance threshold group is called, The low tolerance threshold group is invoked at that time. Each threshold group includes the upper limit of the equivalent diameter of ice crystals. (unit: mm) and lower limit of ice crystal distribution density (unit Then according to and Adjust the base threshold:

[0162] like ,but ;

[0163] like ≤4%, then ;

[0164] like ,but ;

[0165] like ,but .

[0166] Revised and This serves as the threshold for this adjustment.

[0167] The controller compares the calculations obtained by S42. and :like ≥ If so, an adjustment is triggered; at the same time, a comparison is made. and :like ≤ This also triggers an adjustment. The adjustment process begins when either of the two conditions is met. The determination of the adjustment magnitude is based on factors exceeding the allowed proportion. :

[0168] when ≥ hour, ;

[0169] when hour, .

[0170] according to Determine the adjustment level :

[0171] like ,but (Minor adjustments);

[0172] like ,but (Medium adjustment);

[0173] like ,but (Significant adjustment).

[0174] The step-by-step adjustment is executed as follows: the controller adjusts according to... Send instructions to the actuator of the quick-freezing equipment. If necessary, increase the fan speed by one level or decrease the target freezing temperature by 2°C. At that time, increase the temperature by two levels or decrease it by 4 degrees Celsius; At this time, the temperature will be increased by three levels or decreased by 6°C. After each adjustment, the controller waits for a preset stabilization time (e.g., 2 minutes) and then restarts a new round of monitoring via S41 until the quick-freezing process is complete.

[0175] S45. Compare the difference between the actual freezing rate and the target freezing rate curve of the adjusted quick-freezing equipment to generate freezing rate deviation data.

[0176] In this embodiment of the invention, after each step adjustment, the controller extracts the temperature change during the stabilization period after the adjustment from the temperature time series data, calculates the average cooling rate during this time period, and records it as the actual freezing rate. The unit is ℃ / min. Simultaneously, the target freezing rate for this batch is recorded in the full-process freezing parameter package generated in step 203. Calculate the freezing rate deviation rate .Will It is stored in the controller's temporary storage area along with the corresponding timestamp.

[0177] Furthermore, step 205 also includes the following steps:

[0178] S51. Using equipment adjustment data during the quick-freezing process, the time it takes for the maximum ice crystal formation zone to pass through, the temperature drop rate fluctuation value, and the freezing rate deviation data, construct quick-freezing adjustment records and temporarily store them in the cache unit of the quick-freezing equipment.

[0179] In this embodiment of the invention, after the quick-freezing process is completed, the controller summarizes all relevant data generated during this quick-freezing process into a quick-freezing adjustment record. This record includes the following fields: quick-freezing start time and end time, batch identifier, and the calculation result of S41. (unit S41 calculation (unit ), timestamp of each adjustment, cooling parameter value before adjustment, cooling parameter value after adjustment, reason for adjustment ( or Adjustment range levels And each adjustment generated by S45 The controller packages these fields into binary data blocks according to a predetermined format and temporarily stores them in the built-in cache unit of the quick-freezing equipment controller.

[0180] S52. After the quick-freezing is completed and the production turnover carrier is removed from the low-temperature environment, the temporarily stored quick-freezing adjustment record is written into the full-cycle management label.

[0181] In this embodiment of the invention, after quick-freezing, the production transport carrier is conveyed out of the quick-freezing room by a conveyor belt and enters the ambient temperature or refrigerated sorting area. When the carrier reaches the RFID writing station, the reader establishes a communication link with the full-cycle management tag on the carrier. The controller sends the quick-freezing adjustment record data block temporarily stored in the cache unit of S51 to the reader through the communication interface. The reader performs a writing operation, storing the data block in the user storage area of ​​the tag. After writing is completed, the reader sends a read verification command to confirm that the written data is consistent with the original data. At this point, the full-cycle management tag has completely stored all information from electrochemical impedance spectroscopy characteristic parameters, basic meat quality attribute data, full-process freezing process parameter package to quick-freezing adjustment records, providing a complete data foundation for the subsequent cold chain management and terminal thawing control scheme matching of this batch of fish fillets.

[0182] Step 206: Based on the inherent physical properties of the fish fillets corresponding to the full-cycle management and control tags associated with the batch after quick-freezing and the characteristics of quick-freezing conditions, the corresponding cold chain management and control methods and terminal thawing control data are matched to obtain the data.

[0183] Furthermore, the characteristics of the quick-freezing operation include the temperature fluctuation range, the frequency of refrigeration parameter adjustments, and the magnitude of refrigeration parameter adjustments throughout the quick-freezing process. Step 206 includes the following steps:

[0184] S61. Based on the inherent properties of fish fillets, determine the matching categories of cold chain management methods and terminal thawing control data.

[0185] In this embodiment of the invention, the production line control system reads the inherent physical property data of the fish fillets from the full-cycle management tag, namely the meat quality characteristic parameters (muscle fiber density, intercellular space ratio, and bound water percentage) obtained in step 102. The system uses muscle fiber density and bound water percentage as the main classification criteria, dividing the fish fillets into three matching categories: high tolerance (muscle fiber density ≥ 55 fibers / mm² and bound water percentage ≥ 12%), medium tolerance (muscle fiber density between 40 and 55 fibers / mm² and bound water percentage between 8% and 12%), and low tolerance (muscle fiber density ≤ 40 fibers / mm² or bound water percentage ≤ 8%). Each matching category has a pre-stored set of cold chain management baseline requirements and thawing control baseline requirements. For example, the high tolerance category corresponds to a cold chain baseline temperature of -18℃±2℃ and a two-stage thawing procedure; the medium tolerance category corresponds to -19℃±1.5℃ and a three-stage thawing procedure; and the low tolerance category corresponds to -20℃±1℃ and a four-stage thawing procedure. This classification method reflects the fundamental constraints of the inherent physical properties of the fish fillets on subsequent cold chain and thawing processes.

[0186] S62. Under the matching category, based on the temperature fluctuation range and the frequency of refrigeration parameter adjustment, determine the cold chain temperature benchmark and allowable fluctuation range, and construct the cold chain management method.

[0187] In this embodiment of the invention, based on the matching category and its baseline cold chain requirements determined in S61, the control system further reads the quick-freezing condition characteristics stored in the full-cycle management tag: temperature fluctuation range (unit: °C) and refrigeration parameter adjustment frequency (unit: times). The temperature fluctuation range refers to the difference between the highest and lowest temperatures during quick-freezing, and the adjustment frequency refers to the total number of step-by-step adjustments performed during quick-freezing. The following correction rules are applied: if the temperature fluctuation range is ≥5 °C or the adjustment frequency is ≥3 times, the baseline cold chain target temperature is reduced by 1 °C and the allowable fluctuation range is narrowed to ±1 °C; if the temperature fluctuation range is ≤2 °C and the adjustment frequency is ≤1 time, the baseline requirements are maintained; in other cases, the allowable fluctuation range is narrowed to ±1.5 °C based on the baseline. Through the above corrections, the specific parameters (target temperature and fluctuation range) of the cold chain management method are finally determined and written into the tag or output to the cold chain management system.

[0188] S63. Based on the adjustment range of the refrigeration parameters, determine the step-by-step heating range and heating interval, and construct the terminal defrosting control data.

[0189] In this embodiment of the invention, the control system extracts the adjustment range of refrigeration parameters (i.e., the level value 1, 2, or 3 of each step adjustment) from the quick-freezing adjustment record of the full-cycle control tag, and calculates the average adjustment range level of this quick-freezing process. The system maps the average adjustment range level to the corresponding graded thawing parameters: when the average level is 1, two-stage thawing is used (holding at -2℃ for 2 hours, then holding at 4℃ for 1 hour); when the average level is 2, three-stage thawing is used (holding at -4℃ for 1.5 hours, holding at 0℃ for 1.5 hours, and holding at 4℃ for 1 hour); when the average level is 3, four-stage thawing is used (1 hour each at -6℃, -3℃, 0℃, and 4℃). The above mapping relationship and specific temperature and time values ​​can be calibrated for different fish species through offline experiments. The final constructed terminal thawing control data includes the target temperature for step-by-step heating and the duration of each stage, which can be written into the tag or directly displayed on the terminal thawing device as an operation guide.

[0190] Step 207: After quick-freezing, collect the quality evaluation data of the batch of fish fillets after thawing, and correlate it with the electrochemical impedance spectroscopy characteristic parameters and quick-freezing adjustment records stored in the full-cycle management label, and iteratively update the correspondence between impedance and meat quality in the correlation table.

[0191] In this embodiment of the invention, after quick-freezing and cold chain transportation or short-term storage, the company's quality inspectors sample and thaw each batch of fish fillets and measure their post-thaw quality evaluation data. The quality evaluation data includes at least the thawed juice loss rate (%), and may also include indicators such as texture hardness (N) and color. The specific measurement method is as follows: a representative sample of fish fillets from the batch is taken, weighed, and thawed in a 4°C refrigerated environment until the core temperature reaches 0°C~2°C. After absorbing surface moisture with absorbent paper, it is weighed again, and the weight is calculated. The lower the juice loss rate, the better the freezing quality.

[0192] The production line control system retrieves two key types of information stored in the associated full-cycle management tag from the database based on the production traceability code of this batch of fish fillets: first, the electrochemical impedance spectroscopy characteristic parameters (i.e., the comprehensive index of freezing tolerance) generated in step 101; and second, the quick-freezing adjustment record written in step 105 (including the time to pass through the maximum ice crystal formation zone, adjustment frequency, adjustment range, etc.). The measured juice loss rate is then correlated with the above two types of parameters to form a complete data record of "impedance characteristics - quick-freezing conditions - quality results".

[0193] The company periodically (e.g., monthly or every 50 batches) uses these accumulated data records to iteratively update the impedance-meat quality correlation table used in step 102. The update method involves grouping the latest collected quality evaluation data according to the range of impedance characteristic parameters, re-analyzing the correlation between the corresponding meat quality parameters (muscle fiber density, intercellular space ratio, bound water percentage) and juice loss rate within each group, and adjusting the typical values ​​or predicted weights of each parameter interval in the correlation table. For example, if the actual thawing juice loss rate of fish fillets corresponding to a certain impedance interval is consistently higher than the predicted value in the correlation table, the predicted value of the corresponding meat quality parameter in that interval is appropriately lowered (reflecting poorer freezing tolerance). The updated correlation table replaces the original table and is used for matching calculations in subsequent batches.

[0194] Example 3

[0195] 1. Validation of freezing process suitable for fish species with high-density muscle fibers (such as tilapia)

[0196] (1) Detection and grading

[0197] At the inspection station after the fish fillets are sliced, a batch of Nile tilapia fillets (specifications) are inspected. Electrochemical impedance spectroscopy was performed. An interdigitated electrode array was attached to the dorsal side of the fish fillet, and... Amplitude The excitation signal. After interference removal and spectrum analysis, the characteristic parameters are extracted as follows: characteristic frequency. Low-frequency impedance mode The muscle fiber density level was rated as "high" (measured density). ,correspond The intercellular gap ratio level is "medium" (measured). The water content level is "high" (measured). Overall score Weighted ( ) Calculated The score was determined to be "high freezing compatibility level".

[0198] (2) Refrigeration process configuration and execution

[0199] Based on the "high adaptability level", the target process parameter package is obtained by matching and correcting from the process library: quick-freezing temperature. average wind speed Target freeze rate The maximum ice crystal formation zone (-1℃ to -5℃) is subject to a time limit of [time limit]. During the quick-freezing process, the actual average freezing rate is calculated by real-time temperature data acquisition. Cooling rate fluctuation value Calculate the equivalent diameter of ice crystals Estimated as Below the threshold No adjustment was triggered.

[0200] (3) Quality evaluation

[0201] After being stored in a cold chain (standard warehouse at -18℃±2℃) for 14 days, the ice crystals were thawed using a two-stage thawing process (holding them at -2℃ for 2 hours and at 4℃ for 1 hour). The thawed juice loss rate was measured to be 2.1%, which is 41.7% lower than the factory's original general process (juice loss rate of 3.6%). The texture and hardness were well maintained, and the average diameter of the ice crystals was 26 μm according to microscopic image analysis, with uniform distribution.

[0202] 2. Validation of freezing processes suitable for fish species with high intercellular gap ratios (such as golden pomfret)

[0203] (1) Detection and grading

[0204] A batch of oval pomfret (golden pomfret) fillets was analyzed. Impedance spectral characteristic parameters: Meat quality parameter matching: muscle fiber density level is "medium" (actual measurement). The intercellular gap ratio level was determined to be "high" (measured). Exceeding Threshold 8%), combined with water percentage "intermediate" ( Overall score Score, below threshold However, since it is located at the lower edge, it is judged to be of a low freezing compatibility level.

[0205] (2) Freezing process configuration and freezing control

[0206] Given its low adaptability and high intercellular gap ratio, the process parameters were significantly enhanced: quick-freezing temperature -38℃, air velocity 4.5m / s, target freezing rate increased to 6.0℃ / min, and the maximum ice crystal formation zone passage time strictly limited to 25min. In actual freezing, in the initial stage... Up to 28 minutes, The estimated value is 38 μm, which exceeds the correction threshold. (30μm, because) (downward adjustment), and To Below the lower limit. The control system triggers a medium adjustment ( The system automatically lowered the quick-freezing temperature from -38℃ to -42℃, and increased the fan speed by one level. After adjustment, the freezing rate increased to 6.3℃ / min, with a deviation rate of... Restored to version 1.05.

[0207] (3) Quality evaluation

[0208] After cold chain storage, the samples were thawed using a four-stage process (1 hour each at -6°C, -3°C, 0°C, and 4°C). The juice loss rate was measured to be 3.2%, while the juice loss rate of the control sample from the same batch using a common process was as high as 6.9%, representing a reduction of 53.6%. Microscopic observation showed that the ice crystals were mostly small intracellular ice crystals, with no large-area cell rupture.

[0209] 3. Validation of freezing process suitable for fish species with high moisture content and low bound water (such as basa fish)

[0210] (1) Detection and grading

[0211] A batch of imported frozen basa fillets (Pangasius hypophthalmus) underwent simulated thawing and refrozen testing. Impedance characteristics: Jumping to 1050Hz, Matching meat quality: "Low" muscle fiber density (measured). The intercellular space ratio was "low" (4.0%), and the bound water percentage was "low" (...). The overall score is 1.1, which is considered a low fit and indicates extremely poor tolerance.

[0212] (2) Matching process parameters with cold chain

[0213] Extreme quick-freezing parameters were generated: quick-freezing temperature locked at -40℃, wind speed 5m / s, and target freezing rate 7.5℃ / min. (Due to limitations in actual testing...) Large fluctuations ( ), triggering significant adjustments ( The equipment operates at maximum refrigeration load. After the quick-freezing is completed, due to the temperature fluctuation range of 7℃ and the adjustment frequency of 5 times in the operating conditions, the matching cold chain management method is automatically tightened to a strict temperature control chain of -21℃ constant temperature with a fluctuation tolerance of ±0.8℃, and the terminal thawing program is set to a four-level slow thawing.

[0214] (3) Effect verification

[0215] Under strict cold chain conditions, the juice loss rate of this batch of basa fillets was controlled at 4.8%, while that of ordinary stored and transported samples reached 9.5%. Moreover, after thawing, the tissue still maintained a good sheet-like structure and did not show the common water stains, softening, or collapse.

[0216] Example 4

[0217] Please see Figure 3 , Figure 3 This is a structural block diagram of a quality improvement system for frozen fish fillets provided in Embodiment 4 of the present invention.

[0218] This invention provides a quality improvement system for frozen fish fillets, comprising:

[0219] The electrochemical impedance spectroscopy detection module 301 is used to extract representative samples from the same batch of fish fillets to be quick-frozen and perform electrochemical impedance spectroscopy detection when the fish fillets have been sliced ​​and are about to enter the quick-freezing process, so as to construct the electrochemical impedance spectral characteristic parameters of the batch of fish fillets.

[0220] The freezing compatibility level determination module 302 is used to match the meat quality characteristic parameters corresponding to the electrochemical impedance spectroscopy characteristic parameters based on the impedance and meat quality correlation table pre-established in the production line, and determine the freezing compatibility level based on the meat quality characteristic parameters.

[0221] The full-cycle management and control tag generation module 303 is used to configure the corresponding freezing process conditions according to the freezing compatibility level, obtain the full-process freezing process parameter package, and associate and store the identification codes of the key parameters and electrochemical impedance spectroscopy characteristic parameters of the full-process freezing process parameter package with the radio frequency identification temperature sensing tag carried on the corresponding production turnover carrier before quick freezing begins, thus obtaining the full-cycle management and control tag.

[0222] The quick-freezing execution and temperature acquisition module 304 is used to quick-freeze the fish fillets in the batch bound by the full-cycle control tag according to the target freezing rate in the full-process freezing process parameter package, and simultaneously acquire the temperature time series data of the environment in which the fish fillets are located during the quick-freezing process.

[0223] The quick-freezing control and recording module 305 is used to adaptively adjust the refrigeration operation parameters of the quick-freezing equipment based on temperature time series data and the basic meat quality attribute data corresponding to the electrochemical impedance spectroscopy characteristic parameters pre-stored in the full-cycle management tag. After the quick-freezing is completed, the quick-freezing adjustment record is written into the full-cycle management tag.

[0224] The cold chain and thawing matching module 306 is used to match the corresponding cold chain management method and terminal thawing control data based on the inherent physical properties of the fish fillets corresponding to the full-cycle management and control tags associated with the batch after quick-freezing and the characteristics of quick-freezing conditions.

[0225] Since the above is a system corresponding to a method for improving the quality of frozen fish fillets, and its implementation principle is the same as that of a method for improving the quality of frozen fish fillets, for the sake of convenience and brevity, those skilled in the art can clearly understand that the specific working process of the system and modules described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0226] Example 5

[0227] Please see Figure 4 , Figure 4 This is a structural block diagram of an electronic device provided in Embodiment 5 of the present invention.

[0228] An electronic device according to an embodiment of the present invention includes: a memory 401 and a processor 402. The memory 401 stores a computer program. When the computer program is executed by the processor 402, the processor 402 performs a method for improving the quality of frozen fish fillets as described in any of the above embodiments.

[0229] Memory 401 may be an electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read-Only Memory), EPROM, hard disk, or ROM. Memory 401 has storage space 403 for program code 413 for performing any of the method steps described above. For example, storage space 403 for program code may include individual program codes 413 for implementing the various steps in the methods described above. This program code may be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, CDs, memory cards, or floppy disks. The program code may be compressed, for example, in a suitable form. When run by a computing processing device, this code causes the computing processing device to perform the various steps in the methods described above. This program code may be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, CDs, memory cards, or floppy disks. The program code may be compressed, for example, in a suitable form. When this code is run by a computing device, it causes the computing device to perform the various steps in the method for improving the quality of frozen fish fillets described above.

[0230] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for improving the quality of frozen fish fillets, characterized in that, include: After the fish fillets are sliced ​​and ready to enter the quick-freezing process, representative samples are extracted from the same batch of fish fillets to be quick-frozen for electrochemical impedance spectroscopy detection, and the characteristic parameters of the electrochemical impedance spectroscopy of this batch of fish fillets are constructed. Based on the impedance-meat quality correlation table pre-established in the production line, the meat quality characteristic parameters corresponding to the electrochemical impedance spectroscopy characteristic parameters are matched, and the freezing suitability level is determined based on the meat quality characteristic parameters. Based on the freezing compatibility level, the corresponding freezing process conditions are configured to obtain a full-process freezing process parameter package. Before the quick-freezing begins, the key parameters of the full-process freezing process parameter package and the identification codes of the electrochemical impedance spectroscopy characteristic parameters are associated and stored in the radio frequency identification temperature sensing tag carried on the corresponding production turnover carrier to obtain a full-cycle management tag. According to the target freezing rate in the full-process freezing process parameter package, the fish fillets in the batch bound by the full-cycle control tag are quick-frozen, and the temperature time-series data of the environment in which the fish fillets are located are collected simultaneously during the quick-freezing process. Based on the temperature time series data and combined with the basic meat quality attribute data corresponding to the electrochemical impedance spectroscopy characteristic parameters pre-stored in the full-cycle management and control tag, the refrigeration operation parameters of the quick-freezing equipment are adaptively adjusted, and the quick-freezing adjustment record is written into the full-cycle management and control tag after the quick-freezing is completed. Based on the inherent physical properties of the fish fillets and the characteristics of the quick-freezing conditions corresponding to the full-cycle management and control tags associated with the batch after quick-freezing, the corresponding cold chain management and control methods and terminal thawing control data are matched to obtain the data.

2. The method for improving the quality of frozen fish fillets according to claim 1, characterized in that, The step of extracting representative samples from the same batch of fish fillets to be quick-frozen for electrochemical impedance spectroscopy detection and constructing the characteristic parameters of the electrochemical impedance spectroscopy of that batch of fish fillets, after the fish fillets have been sliced ​​and are about to enter the quick-freezing process, includes: At the detection station with a dwell function where the fish fillets are sliced ​​and ready to enter the quick-freezing process, a surface contact multi-electrode array is used to sample and perform in-situ electrochemical impedance spectroscopy on the same batch of fish fillets to be quick-frozen, and the original electrochemical response signal is collected. The invalid interference signals caused by ambient humidity and free water on the surface of the fish fillet are removed from the original electrochemical response signal to generate an intermediate electrochemical response signal; Eliminate electrochemical response signals that are not within the preset frequency range from the intermediate electrochemical response signals to generate the target electrochemical response signal; Spectral analysis and impedance feature extraction were performed on the target electrochemical response signal to obtain multiple fish fillet freezing tolerance characteristic indicators; The target electrochemical response signal is fitted by a preset equivalent circuit model, and equivalent circuit parameters including extracellular fluid resistance, cell membrane capacitance and intracellular fluid resistance are extracted. After normalizing all the aforementioned fish fillet freezing tolerance characteristic indicators, they are fused with the equivalent circuit parameters to generate electrochemical impedance spectroscopy characteristic parameters.

3. The method for improving the quality of frozen fish fillets according to claim 1, characterized in that, The meat quality characteristics include muscle fiber density, intercellular space ratio, and bound water percentage; the step of determining the freeze compatibility level based on the meat quality characteristics includes: The muscle fiber density is compared with a preset muscle fiber density gradient range to determine the muscle fiber density level; The intercellular gap ratio is compared with a preset intercellular gap ratio gradient range to determine the intercellular gap ratio level; The bound water percentage is compared with a preset bound water percentage gradient range to determine the bound water percentage level. The muscle fiber density level, the intercellular space ratio level, and the bound water ratio level are used to perform a comprehensive score based on their respective preset weights, and the cryogenic compatibility level is determined according to the comprehensive score. Among them, the muscle fiber density is positively correlated with the cryofitness level, the intercellular gap ratio is negatively correlated with the cryofitness level, the bound water ratio is positively correlated with the cryofitness level, and the preset weight corresponding to the muscle fiber density is the highest.

4. The method for improving the quality of frozen fish fillets according to claim 1, characterized in that, The step of configuring the corresponding freezing process conditions according to the freezing compatibility level to obtain the full-process freezing process parameter package includes: Based on the target freezing rate curve, quick-freezing temperature, quick-freezing wind speed, segmented freezing parameters, and the time it takes for the maximum ice crystal formation zone to pass through, corresponding to the freezing compatibility level, the initial process configuration data is obtained. Using the meat quality characteristic parameters as an index, a preset calibration coefficient is retrieved to correct the target freezing rate curve and the maximum ice crystal formation zone passage time in the initial process configuration data, thereby generating the target process configuration data. The target process configuration data is encapsulated to generate a complete freezing process parameter package.

5. The method for improving the quality of frozen fish fillets according to claim 1, characterized in that, The step of adaptively adjusting the refrigeration operation parameters of the quick-freezing equipment based on the temperature time-series data and the basic meat quality attribute data corresponding to the electrochemical impedance spectroscopy characteristic parameters pre-stored in the full-cycle control tag includes: Based on the temperature time series data, calculate the maximum ice crystal formation zone passage time and cooling rate fluctuation value; The equivalent diameter and distribution density of ice crystals are calculated using the maximum ice crystal formation zone passage time and the cooling rate fluctuation value. Retrieve the basic meat quality attribute data corresponding to the electrochemical impedance spectroscopy characteristic parameters pre-stored in the full-cycle management tag; Based on the meat quality basic attribute data, the equivalent diameter of the ice crystals, and the distribution density, the adjustment threshold and adjustment range are determined, and the refrigeration operation parameters are adjusted in steps within the adjustable range of the refrigeration output load of the quick-freezing equipment. By comparing the difference between the actual freezing rate of the adjusted quick-freezing equipment and the target freezing rate curve, freezing rate deviation data is generated.

6. The method for improving the quality of frozen fish fillets according to claim 5, characterized in that, The step of writing the quick-freezing adjustment record into the full-cycle management tag after the quick-freezing is completed includes: Using equipment adjustment data, maximum ice crystal formation zone passage time, cooling rate fluctuation value, and freezing rate deviation data during the quick-freezing process, a quick-freezing adjustment record is constructed and temporarily stored in the cache unit of the quick-freezing equipment; After the quick-freezing is completed and the production turnover carrier is removed from the low-temperature environment, the temporarily stored quick-freezing adjustment record is written into the full-cycle management tag.

7. The method for improving the quality of frozen fish fillets according to claim 1, characterized in that, The quick-freezing operating condition characteristics include the temperature fluctuation range, frequency of refrigeration parameter adjustment, and magnitude of refrigeration parameter adjustment throughout the quick-freezing process; the step of matching the inherent physical properties of the fish fillets corresponding to the full-cycle management and control tags associated with the batches after quick-freezing and the quick-freezing operating condition characteristics to obtain the corresponding cold chain management and control methods and terminal thawing control data includes: Based on the inherent properties of the fish fillets, the matching categories of cold chain management methods and terminal thawing control data are determined. Under the matching category, based on the temperature fluctuation range and the refrigeration parameter adjustment frequency, the cold chain temperature benchmark and allowable fluctuation range are determined, and a cold chain management method is constructed. Based on the adjustment range of the cooling parameters, the step-by-step temperature increase range and temperature increase interval are determined, and the terminal defrosting control data is constructed.

8. The method for improving the quality of frozen fish fillets according to claim 1, characterized in that, The method further includes: After quick-freezing, the quality evaluation data of the batch of fish fillets after thawing is collected and correlated with the electrochemical impedance spectroscopy characteristic parameters and quick-freezing adjustment records stored in the full-cycle management label, and the correspondence between impedance and meat quality in the correlation table is iteratively updated.

9. A quality improvement system for frozen fish fillets, characterized in that, include: The electrochemical impedance spectroscopy (EIS) detection module is used to extract representative samples from the same batch of fish fillets to be quick-frozen after the fish fillets have been sliced ​​and are about to enter the quick-freezing process, and to construct the characteristic parameters of the electrochemical impedance spectroscopy of the batch of fish fillets. The freezing compatibility level determination module is used to match the meat quality characteristic parameters corresponding to the electrochemical impedance spectroscopy characteristic parameters based on the impedance and meat quality correlation table pre-established in the production line, and determine the freezing compatibility level based on the meat quality characteristic parameters. The full-cycle management tag generation module is used to configure the corresponding freezing process conditions according to the freezing adaptability level, obtain the full-process freezing process parameter package, and associate and store the identification codes of the key parameters of the full-process freezing process parameter package and the electrochemical impedance spectroscopy characteristic parameters to the radio frequency identification temperature sensing tag carried on the corresponding production turnover carrier before quick freezing begins, so as to obtain the full-cycle management tag. The quick-freezing execution and temperature acquisition module is used to quick-freeze the fish fillets in the batch bound by the full-cycle control tag according to the target freezing rate in the full-process freezing process parameter package, and simultaneously acquire the temperature time series data of the environment in which the fish fillets are located during the quick-freezing process. The quick-freezing control and recording module is used to adaptively adjust the refrigeration operation parameters of the quick-freezing equipment based on the temperature time series data and the basic meat quality attribute data corresponding to the electrochemical impedance spectroscopy characteristic parameters pre-stored in the full-cycle control tag. After the quick-freezing is completed, the quick-freezing adjustment record is written into the full-cycle control tag. The cold chain and thawing matching module is used to match the inherent physical properties of the fish fillets corresponding to the full-cycle management and control tags associated with the batch after quick-freezing, as well as the characteristics of the quick-freezing conditions, to obtain the corresponding cold chain management and control methods and terminal thawing control data.

10. An electronic device, characterized in that, The method includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the method for improving the quality of frozen fish fillets as described in any one of claims 1-8.

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