Intelligent preservation method and system for meat non-crystallization freezing

Abstract

The present invention provides a method and system for intelligent preservation of meat by non-crystallization freezing, which relates to the technical field of intelligent preservation of meat. The method comprises: obtaining the non-crystallization temperature zone of frozen meat; inputting the initial freshness parameter value, the target shelf life and the comprehensive quality evaluation threshold into the non-crystallization freezing critical temperature decision model, and outputting the non-crystallization freezing critical temperature; the non-crystallization freezing critical temperature is the highest temperature at which the meat reaches the target shelf life; determining the non-crystallization freezing temperature based on the principle of being lower than or equal to the non-crystallization freezing critical temperature and higher than or equal to the lower limit temperature of the non-crystallization temperature zone; determining the electric field parameters corresponding to the non-crystallization freezing temperature according to the non-crystallization freezing temperature and the non-crystallization freezing critical temperature data set; and performing electric field-assisted storage of meat based on the non-crystallization freezing temperature and the electric field parameters. The present invention breaks the boundary between traditional freezing and refrigeration temperature zones, avoids the quality deterioration of meat due to freezing, and realizes intelligent preservation of frozen quality and freshness.

Description

Technical Field

[0001] The present invention relates to the technical field of meat intelligent preservation, and in particular to a meat non-crystallization frozen storage intelligent preservation method and system. Background Art

[0002] As the main storage and transportation method for meat, freezing plays an important role in extending the shelf life of meat. Under low-temperature freezing (-18℃ and below), muscle water freezes, which changes the interaction between protein and water in the muscle, reduces water activity, prolongs the doubling time of microbial proliferation, inhibits microbial activity, delays the spoilage process of meat, and prolongs the shelf life; low temperature can also inhibit the activity of endogenous enzymes such as proteases and lipoxygenases in muscles, delays the process of biochemical reactions such as oxidative degradation, and reduces quality deterioration. However, freezing also brings many negative effects on meat quality. For example, under freezing conditions, the water in the food matrix freezes, forming ice crystals, destroying the cell structure and texture, and causing quality deterioration; and frozen meat needs to be thawed in subsequent processing, and the melting of ice crystals produces thawing juice, causing juice loss and quality deterioration (usually the thawing loss of meat in production is as high as 5%-8%), resulting in deterioration and loss of meat thawing quality; at the same time, low-temperature freezing requires lowering the ambient temperature, which consumes a lot of energy.

[0003] Therefore, developing new non-crystallized meat freezing technology, achieving non-freezing storage under theoretical freezing temperature conditions, and avoiding quality deterioration caused by low-temperature freezing have always been common key technical issues that the industry needs to solve urgently. Summary of the invention

[0004] The present invention provides a meat non-crystallization frozen intelligent preservation method and system, which are used to solve the defect that the prior art cannot realize a non-crystallization meat freezing technology, avoid the quality deterioration caused by low-temperature freezing, and realize the intelligent preservation of frozen meat with cold and fresh quality.

[0005] The present invention provides a meat amorphous frozen storage intelligent preservation method, comprising the following steps: obtaining an initial freshness parameter value, a target shelf life, a comprehensive quality evaluation threshold and the type of meat to be stored, and obtaining an amorphous temperature zone for the meat to achieve amorphous frozen storage; inputting the initial freshness parameter value, the target shelf life and the comprehensive quality evaluation threshold into an amorphous frozen storage critical temperature decision model corresponding to the meat type, and outputting an amorphous frozen storage critical temperature; wherein the amorphous frozen storage critical temperature is the maximum temperature required to ensure that the meat reaches the target shelf life; the amorphous frozen storage critical temperature decision model is obtained by training with training samples constructed based on a amorphous frozen storage critical temperature data set corresponding to the meat type, and the amorphous frozen storage critical temperature data set includes the initial freshness parameter value, shelf life, comprehensive quality of the meat sample, Evaluation threshold and corresponding amorphous frozen storage critical temperature and electric field parameters; the input data during the training of the amorphous frozen storage critical temperature decision model includes the initial freshness parameter value, the shelf life and the comprehensive quality evaluation threshold, and the output data during the training of the amorphous frozen storage critical temperature decision model includes the amorphous frozen storage critical temperature; the amorphous frozen storage temperature of the meat product is determined according to the amorphous frozen storage critical temperature output by the amorphous frozen storage critical temperature decision model; wherein the amorphous frozen storage temperature is lower than or equal to the amorphous frozen storage critical temperature and higher than or equal to the lower limit temperature of the amorphous temperature zone; the electric field parameters corresponding to the amorphous frozen storage temperature are determined according to the amorphous frozen storage temperature and the amorphous frozen storage critical temperature data set; the meat product is subjected to electric field assisted storage based on the amorphous frozen storage temperature and the electric field parameters.

[0006] According to a meat amorphous frozen intelligent preservation method provided by the present invention, the process of determining the amorphous temperature zone includes: constructing an amorphous temperature data set of meat samples of the meat type; wherein the amorphous temperature data set includes electric field parameters and corresponding amorphous temperatures; taking the electric field parameters as independent variables and the amorphous temperature as dependent variable, obtaining an amorphous temperature prediction equation through fitting processing; solving the minimum temperature value of the amorphous temperature prediction equation; using the minimum temperature value as the lowest amorphous temperature point for the meat of the meat type to achieve amorphous frozen storage; using the supercooling temperature point of the meat of the meat type under the condition of no electric field as the upper limit temperature and the lowest amorphous temperature point as the lower limit temperature to determine the amorphous temperature zone for the meat to achieve amorphous frozen storage.

[0007] According to a meat non-crystallization frozen intelligent preservation method provided by the present invention, before obtaining the initial freshness parameter value, target shelf life, comprehensive quality evaluation threshold and meat type of the meat to be stored, the method also includes: obtaining the comprehensive quality restriction threshold control array of the meat; wherein the comprehensive quality restriction threshold control array includes quality parameter limiting conditions of at least one quality parameter, and the quality parameter limiting conditions include quality parameter thresholds and the relationship between quality parameter values ​​and the quality parameter thresholds; and performing weighted summation on the quality parameter thresholds of the at least one quality parameter to obtain the comprehensive quality evaluation threshold.

[0008] According to a meat amorphous frozen storage intelligent preservation method provided by the present invention, the method also includes: in the process of constructing the amorphous frozen storage critical temperature data set, for each data, as long as the quality parameter value of any of the quality parameters does not meet the corresponding quality parameter limitation condition, the shelf life is determined according to the current time.

[0009] According to a meat non-crystallization frozen storage intelligent preservation method provided by the present invention, the quality parameter threshold is set based on a preset percentage of the corresponding quality parameter value of the fresh meat.

[0010] According to a meat amorphous freezing intelligent preservation method provided by the present invention, after the meat is subjected to electric field assisted storage based on the amorphous freezing temperature and the electric field parameters, the method further includes: periodically obtaining the prediction result of the quality parameter value of at least one quality parameter; in response to the prediction result of the quality parameter value of any one of the quality parameters not satisfying the corresponding quality parameter limiting condition, ending the storage of the meat.

[0011] According to a meat amorphous frozen intelligent preservation method provided by the present invention, the method of obtaining the predicted result of the quality parameter value of the at least one quality parameter includes: inputting the amorphous frozen storage temperature, the initial freshness parameter value, the storage time of the meat and the electric field parameter into the quality parameter prediction model corresponding to each of the quality parameters, and outputting the predicted result of the quality parameter value of the quality parameter; wherein the quality parameter prediction model is trained with the amorphous frozen storage temperature, the initial freshness parameter value, the storage time and the electric field parameter of the meat sample as input data, and with the quality parameter value corresponding to the quality parameter after the storage time ends as output data.

[0012] According to a meat amorphous frozen intelligent preservation method provided by the present invention, after the meat is subjected to electric field assisted storage based on the amorphous frozen storage temperature and the electric field parameters, the method further includes: in response to obtaining crystallization warning information of the meat, performing a crystallization ablation operation by applying a preset high-frequency and high-voltage alternating electric field, and after confirming the crystal ablation, re-executing the action of performing electric field assisted storage of the meat based on the amorphous frozen storage temperature and the electric field parameters.

[0013] According to a meat non-crystallization frozen intelligent preservation method provided by the present invention, the method further includes: in response to detecting through the temperature sensor that the temperature rise change rate exceeds a set range, generating the crystallization warning information.

[0014] The present invention also provides a meat amorphous frozen storage intelligent fresh-keeping system, comprising the following modules: an acquisition module, used to: acquire the initial freshness parameter value, target shelf life, comprehensive quality evaluation threshold and meat type of meat to be stored, and acquire the amorphous temperature zone for the meat to achieve amorphous frozen storage; a crystallization-freezing critical temperature decision module, used to: input the initial freshness parameter value, the target shelf life and the comprehensive quality evaluation threshold into the amorphous frozen storage critical temperature decision model corresponding to the meat type, and output the amorphous frozen storage critical temperature; wherein the amorphous frozen storage critical temperature is the highest temperature required to ensure that the meat reaches the target shelf life; the amorphous frozen storage critical temperature decision model is obtained by training with training samples constructed based on the amorphous frozen storage critical temperature data set corresponding to the meat type, and the amorphous frozen storage critical temperature data set includes the initial freshness parameter value, shelf life, comprehensive quality evaluation threshold and the amorphous frozen storage critical temperature of the meat sample. the input data of the training of the decision model for the critical temperature of frozen storage without crystallization include the initial freshness parameter value, the shelf life and the comprehensive quality evaluation threshold value, and the output data of the training of the decision model for the critical temperature of frozen storage without crystallization include the critical temperature of frozen storage without crystallization; a module for determining the temperature of frozen storage without crystallization, for determining the temperature of frozen storage without crystallization of the meat product according to the critical temperature of frozen storage without crystallization output by the decision model for the critical temperature of frozen storage without crystallization; wherein the temperature of frozen storage without crystallization is lower than or equal to the critical temperature of frozen storage without crystallization and higher than or equal to the lower limit temperature of the temperature zone of frozen storage without crystallization; an electric field parameter determination module, for determining the electric field parameters corresponding to the temperature of frozen storage without crystallization according to the temperature of frozen storage without crystallization and the critical temperature data set of frozen storage without crystallization; a frozen storage processing module, for performing electric field assisted storage of the meat product based on the temperature of frozen storage without crystallization and the electric field parameters.

[0015] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the intelligent meat non-crystallization freezing and preservation method as described above is implemented.

[0016] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-described intelligent meat non-crystallization freezing and preservation methods.

[0017] The present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements any of the above-mentioned intelligent meat non-crystallization freezing and preservation methods.

[0018] The meat amorphous frozen storage intelligent preservation method and system provided by the present invention obtain the initial freshness parameter value, target shelf life, comprehensive quality evaluation threshold and meat type of meat to be stored, and obtain the amorphous temperature zone for realizing amorphous frozen storage of meat, input the initial freshness parameter value, target shelf life and comprehensive quality evaluation threshold into a crystallization-free frozen storage critical temperature decision model corresponding to the meat type, output the crystallization-free frozen storage critical temperature, which is the highest temperature required to ensure that the meat reaches the target shelf life, determine the crystallization-free frozen storage temperature of the meat according to the crystallization-free frozen storage critical temperature output by the crystallization-free frozen storage critical temperature decision model, determine the electric field parameters corresponding to the crystallization-free frozen storage temperature according to the crystallization-free frozen storage temperature and the crystallization-free frozen storage critical temperature data set, perform electric field-assisted storage on the meat based on the crystallization-free frozen storage temperature and the electric field parameters of the meat, break the boundaries of traditional freezing and refrigeration temperature zones, broaden the amorphous temperature zone, avoid the quality deterioration of meat due to freezing, and realize the intelligent preservation of frozen meat with cold quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 This is one of the flow diagrams of the meat non-crystallization frozen storage intelligent preservation method provided by the present invention.

[0021] Figure 2 A relationship diagram between the amorphous temperature zone and the shelf life under electric field-assisted conditions in the meat amorphous freezing intelligent preservation method provided by the present invention.

[0022] Figure 3It is a schematic diagram of the intelligent decision-making process of the meat non-crystallization freezing intelligent preservation method provided by the present invention.

[0023] Figure 4 This is the second flow diagram of the meat non-crystallization frozen storage intelligent preservation method provided by the present invention.

[0024] Figure 5 It is a structural schematic diagram of the meat non-crystallization frozen storage intelligent fresh-keeping system provided by the present invention.

[0025] Figure 6 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] Figure 1 This is one of the flow diagrams of the meat non-crystallization frozen storage intelligent preservation method provided by the present invention, such as Figure 1 As shown, the method comprises the following steps:

[0028] Step S1, obtaining the initial freshness parameter value, target shelf life, comprehensive quality evaluation threshold and meat type of the meat to be stored, and obtaining the amorphous temperature zone for achieving amorphous frozen storage of the meat.

[0029] Due to the influence of processing conditions or other factors, the initial freshness of the meat to be stored at the beginning of storage is different, which can be represented by an initial freshness parameter value, and specifically, the parameter value representing freshness in the art can be used. The initial freshness parameter value will affect the determination of parameters during meat storage.

[0030] The target shelf life indicates the shelf life that can be achieved under the premise of ensuring the quality of meat. Among them, the quality of meat can be judged by the comprehensive quality evaluation value. The comprehensive quality evaluation value indicates the comprehensive quality of meat, which can be calculated according to the quality parameter values ​​of various quality parameters. For example, the quality parameter values ​​of various quality parameters can be weighted and summed to obtain the comprehensive quality evaluation value. The comprehensive quality evaluation threshold is used to limit the comprehensive quality evaluation value. Only when the comprehensive evaluation threshold is met can it be said that the quality of meat meets the requirements. That is, when the target shelf life and the comprehensive quality evaluation threshold are defined, the comprehensive quality evaluation value of meat within the target shelf life must not exceed the comprehensive quality evaluation threshold. Therefore, the target shelf life and the comprehensive quality evaluation threshold will also affect the determination of parameters during the storage of meat. Meat of different meat types will also have different characteristics during storage. Therefore, it is necessary to establish models for different meat types to determine storage parameters.

[0031] The amorphous temperature zone for the meat to be stored to achieve amorphous frozen storage is obtained. The amorphous temperature zone of the same meat type is the same, so the amorphous temperature zones of the meat of different meat types can be obtained in advance. When the meat to be stored is processed, the corresponding amorphous temperature zone is obtained according to the meat type to which the meat belongs. When the meat is stored at a temperature within the range of the amorphous temperature zone, the meat can achieve amorphous frozen storage.

[0032] The amorphous temperature zone can be determined experimentally. For example, a data set of amorphous temperature of meat samples of different meat types is constructed; wherein the data set of amorphous temperature includes electric field parameters and corresponding amorphous temperature. The amorphous temperature corresponding to the electric field parameters is related to the supercooling temperature point T of the meat under the electric field condition. 过冷’ The amorphization temperature corresponding to the electric field parameters can be expressed as T 过冷’ +ΔT 环境 The amorphous temperature zone of the meat of the meat type is determined according to the upper limit temperature and the lower limit temperature of the amorphous temperature corresponding to each electric field parameter in the amorphous temperature data set.

[0033] Step S2, inputting the initial freshness parameter value, the target shelf life and the comprehensive quality evaluation threshold into the amorphous frozen storage critical temperature decision model corresponding to the meat type, and outputting the amorphous frozen storage critical temperature; wherein, the amorphous frozen storage critical temperature is the highest temperature required to ensure that the meat reaches the target shelf life; the amorphous frozen storage critical temperature decision model is obtained by training with training samples constructed based on a amorphous frozen storage critical temperature data set corresponding to the meat type, and the amorphous frozen storage critical temperature data set includes the initial freshness parameter value, shelf life, comprehensive quality evaluation threshold and corresponding amorphous frozen storage critical temperature and electric field parameters of meat samples; the input data for training the amorphous frozen storage critical temperature decision model includes the initial freshness parameter value, the shelf life and the comprehensive quality evaluation threshold, and the output data for training the amorphous frozen storage critical temperature decision model includes the amorphous frozen storage critical temperature.

[0034] The amorphous frozen storage critical temperature decision model is used to determine the amorphous frozen storage critical temperature of meat products. The amorphous frozen storage critical temperature is the highest temperature of meat amorphous frozen storage to ensure that the meat reaches the target shelf life. If it is higher than the amorphous frozen storage critical temperature, the quality of the meat will not meet the requirements of the comprehensive quality evaluation threshold when it reaches the target shelf life. The amorphous frozen storage critical temperature decision model is trained based on the training samples constructed from the amorphous frozen storage critical temperature dataset corresponding to the meat types.

[0035] The amorphous frozen storage critical temperature dataset includes the initial freshness parameter values, shelf life, comprehensive quality evaluation thresholds of meat samples, and the corresponding amorphous frozen storage critical temperature and electric field parameters. The following example illustrates the construction process of a piece of data in the amorphous frozen storage critical temperature dataset for a certain type of meat:

[0036] The corresponding amorphous temperature is determined by adjusting the electric field parameters, the initial freshness parameter indicates the initial freshness of the meat sample, the meat sample is frozen amorphous at the determined amorphous temperature, and the quality parameters of the meat sample are monitored. The comprehensive quality evaluation threshold reflects the requirements for the comprehensive quality of the meat, which can be calculated by the quality parameter thresholds of each quality parameter. According to the requirements of the comprehensive quality evaluation threshold, if the calculated comprehensive quality evaluation value of the meat sample is greater than the comprehensive quality evaluation threshold, the shelf life is determined. It means that the shelf life is the longest shelf life that can be achieved under the amorphous temperature freezing. If the storage time is greater than the shelf life, the quality cannot be guaranteed. Because the higher the temperature, the easier the meat is to deteriorate, and the lower the temperature, the less likely the meat is to deteriorate. If the amorphous freezing temperature is increased, the shelf life will not meet the requirements. In other words, to achieve the requirements of the shelf life and ensure the quality, the currently determined amorphous temperature is the highest temperature for amorphous freezing of the meat sample. Therefore, the amorphous temperature is saved as the amorphous frozen storage critical temperature, and is taken as a piece of data in the amorphous frozen storage critical temperature data set together with the corresponding initial freshness parameter value, shelf life, comprehensive quality evaluation threshold and electric field parameter.

[0037] The training samples for training the non-crystallization critical temperature decision model are constructed based on the non-crystallization critical temperature data set. The input data for training the non-crystallization critical temperature decision model include the initial freshness parameter value, shelf life and comprehensive quality evaluation threshold, and the output data for training the non-crystallization critical temperature decision model include the non-crystallization critical temperature. The input data and the corresponding output data are taken from a piece of data in the non-crystallization critical temperature data set. After the training is completed, the corresponding non-crystallization critical temperature can be determined based on the initial freshness parameter value, the target shelf life and the comprehensive quality evaluation threshold.

[0038] Therefore, the initial freshness parameter value, target shelf life and comprehensive quality evaluation threshold of the meat to be stored are input into the non-crystallization frozen storage critical temperature decision model corresponding to the meat type, and the non-crystallization frozen storage critical temperature is output. The non-crystallization frozen storage critical temperature is the highest non-crystallization frozen storage temperature required for the meat to ensure the target shelf life and comprehensive quality evaluation threshold.

[0039] The amorphous freezing temperature is determined within the amorphous temperature range. Under certain electric field parameters, the freezing temperature is T zone The crystal-free frozen storage can be achieved at all times, among which, T 过冷 >T zone >(T 过冷’ +ΔT 环境 ), T 过冷 Indicates the supercooling temperature point of meat under the condition of no electric field, T 过冷’ Indicates the supercooling temperature point of meat under electric field conditions, ΔT 环境Indicates the change in ambient temperature. Under a large number of electric field parameters, select the smallest T 过冷’ Value T 过冷’mini , according to T 过冷’mini and ΔT 环境 Determine the lowest value of the achievable amorphization temperature band (T 过冷’mini +ΔT 环境 ), so that T 过冷 is the upper limit temperature, T 过冷’mini +ΔT 环境 is the lower limit temperature, and the amorphous temperature zone is determined.

[0040] Figure 2 The relationship between the amorphous temperature zone and the shelf life under the electric field assisted condition in the meat amorphous frozen storage intelligent preservation method provided by the present invention. Figure 2 It can be seen that different shelf lives correspond to different a-crystallization temperatures. This temperature is called the critical temperature of a-crystallization frozen storage, which is the highest temperature to achieve a-crystallization frozen storage under the corresponding shelf life.

[0041] Step S3, determining the amorphous frozen storage temperature of the meat product according to the amorphous frozen storage critical temperature output by the amorphous frozen storage critical temperature decision model; wherein the amorphous frozen storage temperature is lower than or equal to the amorphous frozen storage critical temperature and higher than or equal to the lower limit temperature of the amorphous temperature zone.

[0042] When meat is stored, if the temperature is higher than the critical temperature for amorphous frozen storage, amorphous frozen storage can be achieved, but the quality cannot be guaranteed. The quality of the meat will not meet the requirements of the comprehensive quality evaluation threshold when the target shelf life is reached. Of course, if a crystallization freezing temperature lower than the critical temperature for amorphous frozen storage is used, and it is a temperature that can achieve amorphous frozen storage of meat, the amorphous frozen storage of meat can be guaranteed, and at the same time, the quality can be guaranteed when the target shelf life meets the requirements of the comprehensive quality evaluation threshold, that is, the quality can be guaranteed at the same time.

[0043] The amorphous temperature zone for the amorphous frozen storage of meat products includes the upper and lower temperature limits at which the meat products of this type can be amorphous frozen. As long as the meat products of this type are frozen at the temperature included in the amorphous temperature zone, it can be guaranteed not to freeze, that is, it can be guaranteed to be amorphous frozen. Here, the amorphous temperature zone only guarantees that there will be no freezing, and does not take into account the requirements of quality, shelf life, etc.

[0044] The non-crystallization critical temperature decision model takes into account the target shelf life, the initial freshness parameter value and the comprehensive quality evaluation threshold when building the model. That is, the non-crystallization critical temperature output by the non-crystallization critical temperature decision model is the highest temperature of the non-crystallization frozen storage of the meat product that can ensure that the meat product meets the quality requirements within the target shelf life. Since lowering the non-crystallization frozen storage temperature will better ensure the quality and target shelf life requirements, the non-crystallization frozen storage temperature actually used when storing meat products can be selected within [non-crystallization critical temperature, non-crystallization temperature zone lower limit temperature]. That is, the non-crystallization frozen storage temperature of the meat product is determined under the condition that it is lower than or equal to the non-crystallization critical temperature and higher than or equal to the lower limit temperature of the non-crystallization temperature zone for non-crystallization frozen storage of the meat product type.

[0045] Under the condition of electric field assistance, it can be achieved that the temperature point that would freeze under the condition of no electric field does not freeze, that is, amorphous freezing is achieved. Different temperatures in the amorphous temperature zone correspond to different electric field parameters. The specific selection of which temperature as the amorphous freezing temperature can be determined from the convenience of realizing the electric field parameters, the cost of realization and the stability of amorphous freezing, or it can be determined randomly. Among them, the electric field parameters can include parameters such as voltage, field strength, and frequency.

[0046] Step S4, determining the electric field parameters corresponding to the amorphous freezing temperature according to the amorphous freezing temperature and the amorphous freezing critical temperature data set.

[0047] The non-crystallization freezing critical temperature in the non-crystallization freezing critical temperature data set is essentially the non-crystallization temperature, which is only the highest non-crystallization freezing temperature that meets the corresponding shelf life and comprehensive quality evaluation threshold requirements. The non-crystallization freezing critical temperature in the non-crystallization freezing critical temperature data set can cover discrete non-crystallization temperatures between the upper limit temperature and the lower limit temperature of the non-crystallization temperature zone. The temperature of the non-crystallization freezing of meat products is lower than or equal to the non-crystallization freezing critical temperature determined in step S2 and higher than or equal to the lower limit temperature of the non-crystallization temperature zone. In the non-crystallization freezing critical temperature data set, the lower limit temperature of the non-crystallization temperature zone is also expressed as the non-crystallization freezing critical temperature, corresponding to the corresponding shelf life and comprehensive quality evaluation threshold. Therefore, the non-crystallization freezing temperature of meat products is actually selected from the non-crystallization freezing critical temperature determined in step S2 and the non-crystallization temperature zone The lower limit temperature corresponds to the non-crystallization temperature zone (the temperature value is also the lower limit temperature of the non-crystallization temperature zone). Since the amorphous freezing critical temperature data set has discrete amorphous freezing critical temperature data entries, each data entry includes the amorphous freezing critical temperature and the corresponding electric field parameters, the electric field parameters corresponding to the amorphous freezing critical temperature can be determined through interpolation processing based on the amorphous freezing critical temperature data set.

[0048] Step S5: performing electric field assisted storage on the meat based on the amorphous freezing temperature and the electric field parameters.

[0049] Based on the amorphous frozen storage temperature of the meat determined in step S3 and the electric field parameters determined in step S4, the meat is subjected to electric field assisted storage, so that the meat can be amorphous frozen at the determined amorphous frozen storage temperature and the quality requirements can be guaranteed.

[0050] The meat amorphous frozen storage intelligent preservation method provided by the present invention obtains the initial freshness parameter value, target shelf life, comprehensive quality evaluation threshold and meat type of meat to be stored, and obtains the amorphous temperature zone for realizing amorphous frozen storage of meat, inputs the initial freshness parameter value, target shelf life and comprehensive quality evaluation threshold into a amorphous frozen storage critical temperature decision model corresponding to the meat type, outputs the amorphous frozen storage critical temperature, which is the highest temperature required to ensure that the meat reaches the target shelf life, determines the amorphous frozen storage temperature of the meat according to the amorphous frozen storage critical temperature output by the amorphous frozen storage critical temperature decision model, determines the electric field parameters corresponding to the amorphous frozen storage temperature according to the amorphous frozen storage temperature and the amorphous frozen storage critical temperature data set, performs electric field-assisted storage on the meat based on the amorphous frozen storage temperature and the electric field parameters of the meat, breaks the boundaries of traditional freezing and refrigeration temperature zones, broadens the amorphous temperature zone, avoids the quality deterioration of meat due to freezing, and realizes the intelligent preservation of frozen meat with cold quality.

[0051] According to a meat amorphous frozen intelligent preservation method provided by the present invention, the process of determining the amorphous temperature zone includes: constructing an amorphous temperature data set of meat samples of the meat type; wherein the amorphous temperature data set includes electric field parameters and corresponding amorphous temperatures; taking the electric field parameters as independent variables and the amorphous temperature as dependent variable, obtaining an amorphous temperature prediction equation through fitting processing; solving the minimum temperature value of the amorphous temperature prediction equation; using the minimum temperature value as the lowest amorphous temperature point for the meat of the meat type to achieve amorphous frozen storage; using the supercooling temperature point of the meat of the meat type under the condition of no electric field as the upper limit temperature and the lowest amorphous temperature point as the lower limit temperature to determine the amorphous temperature zone for the meat to achieve amorphous frozen storage.

[0052] Since the experiment can only cover part of the discrete data, the accuracy of determining the a-crystallization temperature zone for a-crystallization frozen storage of meat based only on experimental data is slightly insufficient. In order to improve the accuracy of the a-crystallization temperature zone, the law of the a-crystallization temperature zone can be captured based on experimental data, and the lower limit temperature of the a-crystallization temperature zone can be determined thereby, so as to determine the a-crystallization temperature zone more accurately.

[0053] Determine the amorphous temperature zone based on the type of meat. Meat can be divided according to different standards, such as different types of livestock, such as pork and beef. On this basis, it can also be further divided according to different parts of the meat.

[0054] A crystallization-free temperature data set of meat samples of a certain meat category is constructed; wherein the crystallization-free temperature data set includes electric field parameters and corresponding crystallization temperatures; the electric field parameters are used as independent variables, the crystallization-free temperature is used as the dependent variable, and a crystallization-free temperature prediction equation is obtained through fitting processing; the minimum temperature value of the crystallization-free temperature prediction equation is solved as the lowest crystallization-free temperature point for the meat of this meat category to achieve crystallization-free frozen storage; the supercooling temperature point of the meat of this meat category under the condition of no electric field is used as the upper limit temperature, and the lowest crystallization-free temperature point is used as the lower limit temperature, to determine the crystallization temperature zone for the meat to achieve crystallization-free frozen storage.

[0055] The lower limit of the amorphous temperature zone determined based on this method may be lower than the lower limit of the temperature in the amorphous frozen storage critical temperature data set. The relevant data can be further supplemented through experiments.

[0056] The intelligent fresh-keeping method for meat amorphous frozen storage provided by the present invention constructs amorphous temperature data sets of meat samples of meat types; wherein the amorphous temperature data sets include electric field parameters and corresponding amorphous temperatures; takes the electric field parameters as independent variables and the amorphous temperature as dependent variable, and obtains amorphous temperature prediction equation through fitting processing; solves the minimum temperature value of the amorphous temperature prediction equation; uses the minimum temperature value as the lowest amorphous temperature point for meat types to achieve amorphous frozen storage; uses the supercooled temperature point of meat types under electric field-free conditions as the upper limit temperature and the lowest amorphous temperature point as the lower limit temperature to determine the amorphous temperature zone for meat types to achieve amorphous frozen storage, thereby improving the accuracy of the amorphous temperature zone.

[0057] According to a meat non-crystallization frozen intelligent preservation method provided by the present invention, before obtaining the initial freshness parameter value, target shelf life, comprehensive quality evaluation threshold and meat type of the meat to be stored, the method also includes: obtaining the comprehensive quality restriction threshold control array of the meat; wherein the comprehensive quality restriction threshold control array includes quality parameter limiting conditions of at least one quality parameter, and the quality parameter limiting conditions include quality parameter thresholds and the relationship between quality parameter values ​​and the quality parameter thresholds; and performing weighted summation on the quality parameter thresholds of the at least one quality parameter to obtain the comprehensive quality evaluation threshold.

[0058] Meat products include multiple quality parameters, and corresponding quality parameter limiting conditions can be set for each quality parameter. When monitoring the quality of meat products, it can be set that only when each quality parameter satisfies the corresponding quality parameter limiting conditions can the meat quality be determined to meet the requirements.

[0059] A comprehensive quality restriction threshold control array is determined in advance according to the quality parameter restriction conditions of different quality parameters. The comprehensive quality restriction threshold control array includes the quality parameter restriction condition of at least one quality parameter, and the quality parameter restriction condition includes the quality parameter threshold and the relationship between the quality parameter value and the quality parameter threshold. When obtaining the comprehensive quality evaluation threshold, the quality parameter threshold of at least one quality parameter can be weighted and summed to obtain the comprehensive quality evaluation threshold.

[0060] The meat non-crystallization frozen storage intelligent preservation method provided by the present invention obtains the comprehensive quality restriction threshold control array of the meat, the comprehensive quality restriction threshold control array includes the quality parameter limiting condition of at least one quality parameter, the quality parameter limiting condition includes the quality parameter threshold and the relationship between the quality parameter value and the quality parameter threshold, and the quality parameter threshold of at least one quality parameter is weightedly summed to obtain the comprehensive quality evaluation threshold, thereby improving the accuracy of the comprehensive quality evaluation threshold.

[0061] According to a meat amorphous frozen storage intelligent preservation method provided by the present invention, the method also includes: in the process of constructing the amorphous frozen storage critical temperature data set, for each data, as long as the quality parameter value of any of the quality parameters does not meet the corresponding quality parameter limitation condition, the shelf life is determined according to the current time.

[0062] The shelf life (i.e., time dimension) of different meats depends on the muscle water supercooling point under different electric field conditions, and is also subject to the meat quality parameters Qmeat (shear force, viscoelasticity, bulk water, color, total bacterial count, TVB-N, TBARS, etc.). According to the needs of intelligent decision-making for quality control, a comprehensive quality restriction threshold control array for non-crystallized frozen storage of different types of meat is set, and the shelf life (days) is determined according to the "earliest" principle. As long as one of the measured values ​​of the quality indicators in the comprehensive quality restriction threshold control array first triggers the set threshold, storage ends. Ensure the quality of frozen meat is chilled and fresh (the comprehensive quality of non-crystallized frozen storage reaches more than 90% of the quality of fresh meat).

[0063] For example, when chicken is kept at -3.5℃, the total colony count reaches 10 at 20 days. 6 CFU / g, triggering the total colony count indicator of the comprehensive quality restrictive threshold control array, and the shelf life is determined to be 20 days based on the "earliest" principle. Chicken meat at -4.5℃, TBARS reached 0.4mg MDA / kg at 28 days, triggering the TBARS indicator of the comprehensive quality restrictive threshold control array, and the shelf life is determined to be 28 days based on the "earliest" principle.

[0064] In the process of constructing the critical temperature data set for non-crystallization frozen storage, the determination of the shelf life meets the "earliest" principle. For each piece of data, as long as the quality parameter value of any quality parameter does not meet the corresponding quality parameter limitation condition, the shelf life is determined based on the current moment. That is, the time from the beginning of the shelf life calculation to the current moment is the shelf life.

[0065] The meat non-crystallization frozen storage intelligent preservation method provided by the present invention improves the accuracy of shelf life determination by determining the shelf life according to the current moment for each piece of data during the process of constructing a non-crystallization frozen storage critical temperature data set as long as the quality parameter value of any quality parameter does not meet the corresponding quality parameter limiting condition.

[0066] According to a meat non-crystallization frozen storage intelligent preservation method provided by the present invention, the quality parameter threshold is set based on a preset percentage of the corresponding quality parameter value of the fresh meat.

[0067] The present invention realizes the intelligent preservation of frozen meat quality and freshness, and can set each quality parameter threshold based on the preset percentage of the corresponding quality parameter value of the fresh meat. For example, the quality parameter threshold is set to 90% of the quality parameter value of the fresh meat.

[0068] The meat non-crystallization frozen storage intelligent preservation method provided by the present invention improves the effect of meat non-crystallization intelligent preservation by setting the quality parameter threshold value based on the preset percentage of the corresponding quality parameter value of the fresh meat.

[0069] According to a meat amorphous freezing intelligent preservation method provided by the present invention, after the meat is subjected to electric field assisted storage based on the amorphous freezing temperature and the electric field parameters, the method further includes: periodically obtaining the prediction result of the quality parameter value of at least one quality parameter; in response to the prediction result of the quality parameter value of any one of the quality parameters not satisfying the corresponding quality parameter limiting condition, ending the storage of the meat.

[0070] Figure 3 The figure is a schematic diagram of the intelligent decision-making process of the meat non-crystallization frozen intelligent preservation method provided by the present invention. The intelligent decision-making process diagram is designed in combination with the comprehensive quality restriction threshold control array: (texture, moisture, color, physical and chemical quality). Polling and monitoring are performed on each quality parameter to determine whether it meets the corresponding quality parameter limiting condition. If a quality parameter does not meet the corresponding quality parameter limiting condition, it means that the non-crystallization frozen storage cannot be continued, and the storage needs to be terminated or further processed.

[0071] Among them, when polling and monitoring each quality parameter, the predicted result of the quality parameter value of at least one quality parameter can be periodically obtained, and the quality parameter value of each quality parameter can be compared with its corresponding quality parameter threshold value to determine whether the quality parameter value meets the corresponding quality parameter limitation condition. If the predicted result of the quality parameter value of any quality parameter does not meet the corresponding quality parameter limitation condition, the storage of the meat is terminated.

[0072] The meat amorphous frozen intelligent preservation method provided by the present invention periodically obtains the prediction result of the quality parameter value of at least one quality parameter; in response to the predicted result of the quality parameter value of any quality parameter failing to meet the corresponding quality parameter limitation condition, the storage of the meat is terminated, thereby further improving the effect of the meat amorphous intelligent preservation.

[0073] According to a meat amorphous frozen intelligent preservation method provided by the present invention, the method of obtaining the prediction result of the quality parameter value of the at least one quality parameter includes: inputting the amorphous frozen storage temperature, the initial freshness parameter value, the storage time of the meat and the electric field parameter into the quality parameter prediction model corresponding to each of the quality parameters, and outputting the prediction result of the quality parameter value of the quality parameter; wherein the quality parameter prediction model is trained with the amorphous frozen storage temperature, the initial freshness parameter value, the storage time and the electric field parameter of the meat sample as input data, and with the quality parameter value corresponding to the quality parameter after the storage time ends as output data.

[0074] For each quality parameter, a corresponding quality parameter prediction model is established to predict the quality parameter value of the quality parameter. The quality parameter prediction model does not need to consider the shelf life and quality parameter threshold when predicting the quality parameter value. The non-crystallization frozen storage temperature, initial freshness parameter value, storage time and electric field parameter of the meat sample are used as input data, and the quality parameter value corresponding to the quality parameter under the storage time is used as output data. After training, the quality parameter prediction model corresponding to each quality parameter is obtained.

[0075] The establishment of a quality parameter prediction model requires a large amount of data. Based on the database of different meat amorphous temperature under different electric field parameters, different temperature points are selected to measure the dynamic changes in meat quality at different storage times (such as 1, 3, 5, 7... days, etc.) at this temperature point.

[0076] The following are examples of how quality parameters are obtained:

[0077] Shear force and elasticity measurement: The shear force of the sample was measured by the Warner-Bratzler method. The meat sample was cut into 3 cm × 1 cm × 1 cm meat samples parallel to the muscle fiber direction, and the shear force value of the meat sample was measured using a physical property tester. The shear speed was 1.5 mm / s and the shear distance was 40 mm. The elasticity of the sample was measured using the TA.XT2 physical property tester using the texture profile analysis (TPA) mode. The sample was cut into 1 cm × 1 cm × 1 cm samples and measured using a physical property tester at room temperature. The pre-test rate was 2 mm / s, the test rate was 1 mm / s, the post-test rate was 1 mm / s, the trigger force was 5 g, the sample height was 1 cm, the compression ratio was 75%, the measurement interval was 5 s, and the probe model was P / 75. Each sample test was repeated 5 times, and the results were averaged.

[0078] Determination of bulk water: The stored meat samples were cut into 2 cm × 2 cm × 3 cm pieces, and the parameters of nuclear magnetic resonance were set as follows: main frequency of 23 MHz, offset frequency of 286.781 3 kHz, 90° pulse time of 17 μs, 180° pulse time of 35 μs, number of sampling points of 54996, repetition time of 3000 ms, accumulation times of 4 times, and echo number of 2000. The samples were placed in a low-temperature detection tube with a diameter of 25 mm, and the nuclear magnetic resonance imaging system spin echo imaging sequence was used to measure the hydrogen proton density of the meat samples. The parameters were set as follows: repetition time of 2000 ms, repetition times of 4 times, longitudinal relaxation time of 20 ms, and the spin echo time of 20 ms was selected according to the relaxation time T2 measured by the CPMG sequence.

[0079] Color measurement: Take a meat sample and place it in the measuring tool provided by the colorimeter. Calibrate it with a white board, place the sample directly under the light source, and read the value displayed by the colorimeter. (brightness), (Redness), (yellowness), calculate the color parameters according to the following formula :

[0080]

[0081] in, , , They represent the brightness, redness and yellowness of fresh meat respectively.

[0082] Determination of total colony count: Determine according to the method in GB4789.2-2016.

[0083] TVB-N determination: Determine the volatile basic nitrogen content in the sample with reference to the semi-micro nitrogen determination method in GB5009.228-2016.

[0084] TBARS determination: Determine the thiobarbituric acid content in the sample by referring to the spectrophotometric method in GB / T5009.181-2016.

[0085] Histamine determination: refer to KJ 202102 Rapid detection of histamine in aquatic products for determination.

[0086] During the storage process of meat, when obtaining the predicted result of the quality parameter value of at least one quality parameter, the meat's amorphous frozen storage temperature, initial freshness parameter value, meat storage time and electric field parameters are respectively input into the quality parameter prediction model corresponding to each quality parameter, and the predicted result of the quality parameter value of the quality parameter is output.

[0087] The meat amorphous frozen storage intelligent preservation method provided by the present invention inputs the meat amorphous frozen storage temperature, initial freshness parameter value, storage time and electric field parameters into the quality parameter prediction model corresponding to each quality parameter, outputs the prediction result of the quality parameter value of the quality parameter, thereby improving the accuracy of the prediction result of the quality parameter value.

[0088] Figure 4 This is the second flow chart of the meat non-crystallization frozen storage intelligent preservation method provided by the present invention. Figure 4 As shown, based on the above steps S1-S5, the method further includes:

[0089] Step S6, in response to obtaining the crystallization warning information of the meat, performing a crystal ablation operation by applying a preset high-frequency and high-voltage alternating electric field, and after confirming the crystal ablation, re-executing the action of performing electric field assisted storage on the meat based on the amorphous freezing temperature and the electric field parameters.

[0090] In the actual amorphous frozen storage process, meat samples freeze due to uncertain factors such as the non-uniformity of meat samples and improper operation. The ice crystal formation state of fresh meat is monitored in real time, and crystallization warning information is generated when ice crystal formation or the hidden danger of ice crystal formation is found. If the crystallization warning information of the meat is obtained, the crystal ablation operation is performed by applying a preset high-frequency and high-voltage alternating electric field. After confirming the crystal ablation, the action of electric field-assisted storage of the meat based on the amorphous frozen storage temperature and electric field parameters of the meat is re-executed (step S5 is re-executed). That is, the meat is stored again according to the previously determined electric field parameters and amorphous frozen storage temperature.

[0091] The intelligent meat preservation method for amorphous freezing provided by the present invention responds to the crystallization warning information of the meat, performs a crystal ablation operation by applying a preset high-frequency and high-voltage alternating electric field, and after confirming the crystal ablation, re-executes the action of electric field-assisted storage of the meat based on the amorphous freezing temperature and electric field parameters of the meat, thereby improving the robustness and stability of the amorphous freezing process technology.

[0092] According to a meat non-crystallization frozen intelligent preservation method provided by the present invention, the method further includes: in response to detecting through the temperature sensor that the temperature rise change rate exceeds a set range, generating the crystallization warning information.

[0093] Since meat samples release latent heat when they freeze, the temperature of meat samples rises. Through online real-time temperature monitoring, the temperature sudden change jump signal can be captured, and intelligent decision-making and judgment can be made whether ice crystals (freezing) appear. Specifically, if the temperature sensor detects that the temperature rise rate exceeds the set range (such as the temperature of the meat product rises by more than 1 degree within 10 seconds), a crystallization warning message will be generated.

[0094] During the crystal-free frozen storage process, a low-frequency, low-voltage alternating electric field is continuously applied to inhibit water molecules from joining the ice tray to form stable crystal nuclei. Thermal imaging detects the release of latent heat caused by accidental freezing and immediately feeds back to the control system. The control system applies a high-frequency, high-voltage alternating electric field to the meat to dissolve the accidental ice crystal nuclei at the nucleation stage, achieving long-term stable crystal-free frozen storage and driving the frozen quality of meat to be cold and fresh. After the ice crystals are eliminated, the electric field parameters and the crystal-free temperature are restored to the original setting for storage.

[0095] For example, chicken is frozen without crystallization at -4.6℃ under the electric field conditions of 220V voltage, 1100V / m field strength and 300Hz frequency. If the temperature of the meat sample abnormally rises to -1.5℃ (freezing point), the system will judge that abnormal freezing has occurred, and will apply high-voltage and high-frequency electric field to melt ice crystals, inhibit the release of latent heat, and gradually adjust the abnormal meat sample temperature back to the set temperature for the freezing without crystallization (-4.6℃), and continue to be frozen without crystallization to preserve freshness.

[0096] The temperature sensor can detect that the temperature rise rate returns to the set range to determine the crystal ablation.

[0097] The meat non-crystallization frozen storage intelligent preservation method provided by the present invention generates crystallization warning information in response to temperature field changes detected by a temperature sensor, thereby improving the reliability of the generation of crystallization warning information.

[0098] The meat amorphous frozen storage intelligent fresh-keeping system provided by the present invention is described below. The meat amorphous frozen storage intelligent fresh-keeping system described below and the meat amorphous frozen storage intelligent fresh-keeping method described above can be referred to each other.

[0099] Figure 5 Schematic diagram of the structure of the meat non-crystallization frozen storage intelligent fresh-keeping system provided by the present invention. Figure 5 As shown, the system includes an acquisition module 10, a non-crystallized frozen storage critical temperature decision module 20, a non-crystallized frozen storage temperature determination module 30, an electric field parameter determination module 40 and a frozen storage processing module 50, wherein: the acquisition module 10 is used to: obtain the initial freshness parameter value, target shelf life, comprehensive quality evaluation threshold and meat type of the meat to be stored, and obtain the non-crystallized temperature zone for the meat to achieve non-crystallized frozen storage; the non-crystallized frozen storage critical temperature decision module 20 is used to: input the initial freshness parameter value, the target shelf life and the comprehensive quality evaluation threshold into the non-crystallized frozen storage critical temperature decision model corresponding to the meat type, and output the non-crystallized frozen storage critical temperature; wherein the non-crystallized frozen storage critical temperature is the highest temperature required to ensure that the meat reaches the target shelf life; the non-crystallized frozen storage critical temperature decision model is obtained by training samples constructed based on the non-crystallized frozen storage critical temperature data set corresponding to the meat type, and the non-crystallized frozen storage critical temperature data set includes the initial freshness parameter value, the target shelf life and the comprehensive quality evaluation threshold into the non-crystallized frozen storage critical temperature decision model corresponding to the meat type, and output the non-crystallized frozen storage critical temperature. The input data of the decision model for the critical temperature of the amorphous frozen storage include the initial freshness parameter value, the shelf life and the comprehensive quality evaluation threshold value, and the output data of the decision model for the critical temperature of the amorphous frozen storage include the critical temperature of the amorphous frozen storage; the amorphous frozen storage temperature determination module 30 is used to: determine the amorphous frozen storage temperature of the meat product according to the critical temperature of the amorphous frozen storage output by the decision model for the critical temperature of the amorphous frozen storage; wherein the amorphous frozen storage temperature is lower than or equal to the critical temperature of the amorphous frozen storage and higher than or equal to the lower limit temperature of the amorphous temperature zone; the electric field parameter determination module 40 is used to: determine the electric field parameters corresponding to the amorphous frozen storage temperature according to the amorphous frozen storage temperature and the critical temperature data set of the amorphous frozen storage; the frozen storage processing module 50 is used to: perform electric field assisted storage on the meat product based on the amorphous frozen storage temperature and the electric field parameters.

[0100] The meat amorphous frozen storage intelligent fresh-keeping system provided by the present invention obtains the initial freshness parameter value, target shelf life, comprehensive quality evaluation threshold and meat type of meat to be stored, and obtains the amorphous temperature zone for realizing amorphous frozen storage of meat, inputs the initial freshness parameter value, target shelf life and comprehensive quality evaluation threshold into a crystallization-free frozen storage critical temperature decision model corresponding to the meat type, outputs the crystallization-free frozen storage critical temperature, which is the highest temperature required to ensure that the meat reaches the target shelf life, determines the amorphous frozen storage temperature of the meat according to the crystallization-free frozen storage critical temperature output by the crystallization-free frozen storage critical temperature decision model, determines the electric field parameters corresponding to the crystallization-free frozen storage temperature according to the crystallization-free frozen storage temperature and the crystallization-free frozen storage critical temperature data set, performs electric field-assisted storage on the meat based on the crystallization-free frozen storage temperature and the electric field parameters of the meat, breaks the boundaries of traditional freezing and refrigeration temperature zones, broadens the amorphous temperature zone, avoids the quality deterioration of meat due to freezing, and realizes the intelligent fresh-keeping of frozen meat with cold quality.

[0101] Figure 6 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 6As shown, the electronic device may include: a processor (processor) 410 , a communication interface (Communications Interface) 420 , a memory (memory) 430 and a communication bus 440 , wherein the processor 410 , the communication interface 420 , and the memory 430 communicate with each other through the communication bus 440 . The processor 410 can call the logic instructions in the memory 430 to execute the intelligent preservation method for amorphous frozen storage of meat, which method includes: obtaining the initial freshness parameter value, target shelf life, comprehensive quality evaluation threshold and meat type of the meat to be stored, and obtaining the amorphous temperature zone for the meat to achieve amorphous frozen storage; inputting the initial freshness parameter value, the target shelf life and the comprehensive quality evaluation threshold into the amorphous frozen storage critical temperature decision model corresponding to the meat type, and outputting the amorphous frozen storage critical temperature; wherein the amorphous frozen storage critical temperature is the maximum temperature required to ensure that the meat reaches the target shelf life; the amorphous frozen storage critical temperature decision model is obtained by training with training samples constructed based on the amorphous frozen storage critical temperature data set corresponding to the meat type, and the amorphous frozen storage critical temperature data set includes the initial freshness parameter value of the meat sample , shelf life, comprehensive quality evaluation threshold and corresponding amorphous frozen storage critical temperature and electric field parameters; the input data of the amorphous frozen storage critical temperature decision model training includes the initial freshness parameter value, the shelf life and the comprehensive quality evaluation threshold, and the output data of the amorphous frozen storage critical temperature decision model training includes the amorphous frozen storage critical temperature; the amorphous frozen storage temperature of the meat is determined according to the amorphous frozen storage critical temperature output by the amorphous frozen storage critical temperature decision model; wherein the amorphous frozen storage temperature is lower than or equal to the amorphous frozen storage critical temperature and higher than or equal to the lower limit temperature of the amorphous temperature zone; the electric field parameters corresponding to the amorphous frozen storage temperature are determined according to the amorphous frozen storage temperature and the amorphous frozen storage critical temperature data set; the meat is subjected to electric field assisted storage based on the amorphous frozen storage temperature and the electric field parameters.

[0102] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0103] On the other hand, the present invention also provides a computer program product, which includes a computer program, which can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the meat amorphous frozen storage intelligent preservation method provided by the above-mentioned methods, the method comprising: obtaining an initial freshness parameter value, a target shelf life, a comprehensive quality evaluation threshold and a meat type to be stored, and obtaining an amorphous temperature zone for the meat to achieve amorphous frozen storage; inputting the initial freshness parameter value, the target shelf life and the comprehensive quality evaluation threshold into an amorphous frozen storage critical temperature decision model corresponding to the meat type, and outputting an amorphous frozen storage critical temperature; wherein the amorphous frozen storage critical temperature is the highest temperature required to ensure that the meat reaches the target shelf life; the amorphous frozen storage critical temperature decision model is a training sample training based on a amorphous frozen storage critical temperature data set corresponding to the meat type. The obtained amorphous frozen storage critical temperature data set includes the initial freshness parameter value, shelf life, comprehensive quality evaluation threshold and corresponding amorphous frozen storage critical temperature and electric field parameters of the meat sample; the input data when training the amorphous frozen storage critical temperature decision model includes the initial freshness parameter value, the shelf life and the comprehensive quality evaluation threshold, and the output data when training the amorphous frozen storage critical temperature decision model includes the amorphous frozen storage critical temperature; the amorphous frozen storage temperature of the meat is determined according to the amorphous frozen storage critical temperature output by the amorphous frozen storage critical temperature decision model; wherein the amorphous frozen storage temperature is lower than or equal to the amorphous frozen storage critical temperature and higher than or equal to the lower limit temperature of the amorphous temperature zone; the electric field parameters corresponding to the amorphous frozen storage temperature are determined according to the amorphous frozen storage temperature and the amorphous frozen storage critical temperature data set; the meat is subjected to electric field assisted storage based on the amorphous frozen storage temperature and the electric field parameters.

[0104] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the meat amorphous frozen storage intelligent preservation method provided by the above-mentioned methods, the method comprising: obtaining an initial freshness parameter value, a target shelf life, a comprehensive quality evaluation threshold and a meat type to be stored, and obtaining an amorphous temperature zone for the meat to achieve amorphous frozen storage; inputting the initial freshness parameter value, the target shelf life and the comprehensive quality evaluation threshold into an amorphous frozen storage critical temperature decision model corresponding to the meat type, and outputting an amorphous frozen storage critical temperature; wherein the amorphous frozen storage critical temperature is the highest temperature required to ensure that the meat reaches the target shelf life; the amorphous frozen storage critical temperature decision model is obtained by training based on a training sample constructed based on a amorphous frozen storage critical temperature data set corresponding to the meat type, and the amorphous frozen storage critical temperature The data set includes the initial freshness parameter value, shelf life, comprehensive quality evaluation threshold and corresponding amorphous frozen storage critical temperature and electric field parameters of the meat sample; the input data when training the amorphous frozen storage critical temperature decision model includes the initial freshness parameter value, the shelf life and the comprehensive quality evaluation threshold, and the output data when training the amorphous frozen storage critical temperature decision model includes the amorphous frozen storage critical temperature; the amorphous frozen storage temperature of the meat is determined according to the amorphous frozen storage critical temperature output by the amorphous frozen storage critical temperature decision model; wherein the amorphous frozen storage temperature is lower than or equal to the amorphous frozen storage critical temperature and higher than or equal to the lower limit temperature of the amorphous temperature zone; the electric field parameters corresponding to the amorphous frozen storage temperature are determined according to the amorphous frozen storage temperature and the amorphous frozen storage critical temperature data set; the meat is subjected to electric field assisted storage based on the amorphous frozen storage temperature and the electric field parameters.

[0105] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0106] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0107] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for intelligent preservation of meat by non-crystallization freezing, characterized in that: include: Obtaining the initial freshness parameter value, target shelf life, comprehensive quality evaluation threshold and meat type of the meat to be stored, and obtaining the amorphous temperature zone for achieving amorphous frozen storage of the meat; The process of determining the amorphous temperature zone includes: constructing an amorphous temperature data set of meat samples of the meat category; wherein the amorphous temperature data set includes electric field parameters and corresponding amorphous temperatures; taking the electric field parameters as independent variables and the amorphous temperature as dependent variables, obtaining an amorphous temperature prediction equation through fitting processing; solving the minimum temperature value of the amorphous temperature prediction equation; taking the minimum temperature value as the lowest amorphous temperature point for the meat of the meat category to achieve amorphous frozen storage; taking the supercooling temperature point of the meat of the meat category under the condition of no electric field as the upper limit temperature and the lowest amorphous temperature point as the lower limit temperature, determining the amorphous temperature zone for the meat to achieve amorphous frozen storage; The initial freshness parameter value, the target shelf life and the comprehensive quality evaluation threshold are input into the amorphous frozen storage critical temperature decision model corresponding to the meat type, and the amorphous frozen storage critical temperature is output; wherein the amorphous frozen storage critical temperature is the highest temperature required to ensure that the meat reaches the target shelf life; the amorphous frozen storage critical temperature decision model is obtained by training with training samples constructed based on the amorphous frozen storage critical temperature data set corresponding to the meat type, and the amorphous frozen storage critical temperature data set includes the initial freshness parameter value, shelf life, comprehensive quality evaluation threshold and the corresponding amorphous frozen storage critical temperature and electric field parameters of the meat samples; the input data for training the amorphous frozen storage critical temperature decision model includes the initial freshness parameter value, the shelf life and the comprehensive quality evaluation threshold, and the output data for training the amorphous frozen storage critical temperature decision model includes the amorphous frozen storage critical temperature; Determining the amorphous frozen storage temperature of the meat product according to the amorphous frozen storage critical temperature output by the amorphous frozen storage critical temperature decision model; wherein the amorphous frozen storage temperature is lower than or equal to the amorphous frozen storage critical temperature and higher than or equal to the lower limit temperature of the amorphous temperature zone; Determining the electric field parameter corresponding to the amorphous frozen storage temperature according to the amorphous frozen storage temperature and the amorphous frozen storage critical temperature data set; The meat is subjected to electric field assisted storage based on the amorphous freezing temperature and the electric field parameters; in response to the temperature sensor detecting that the temperature rise rate exceeds a set range, a crystallization warning message is generated; in response to obtaining the crystallization warning message of the meat, a crystallization ablation operation is performed by applying a preset high-frequency and high-voltage alternating electric field, and after confirming the crystal ablation, the action of performing electric field assisted storage of the meat based on the amorphous freezing temperature and the electric field parameters is re-executed.

2. The meat non-crystallization frozen storage intelligent preservation method according to claim 1, characterized in that: Before obtaining the initial freshness parameter value, target shelf life, comprehensive quality evaluation threshold and meat type of the meat to be stored, the method further includes: Obtaining a comprehensive quality restriction threshold control array of the meat product; wherein the comprehensive quality restriction threshold control array includes a quality parameter restriction condition of at least one quality parameter, and the quality parameter restriction condition includes a quality parameter threshold and a relationship between a quality parameter value and the quality parameter threshold; The comprehensive quality evaluation threshold is obtained by weighted summing the quality parameter thresholds of the at least one quality parameter.

3. The meat non-crystallization frozen storage intelligent preservation method according to claim 2, characterized in that: The method further comprises: In the process of constructing the amorphous frozen storage critical temperature data set, for each piece of data, as long as the quality parameter value of any of the quality parameters does not meet the corresponding quality parameter limiting condition, the shelf life is determined according to the current moment.

4. The meat non-crystallization frozen storage intelligent preservation method according to claim 2, characterized in that: The quality parameter threshold is set based on a preset percentage of the corresponding quality parameter value of the fresh meat.

5. The meat non-crystallization frozen storage intelligent preservation method according to claim 2, characterized in that: After the meat is subjected to electric field-assisted storage based on the amorphous freezing temperature and the electric field parameters, the method further includes: Periodically obtaining a prediction result of a quality parameter value of the at least one quality parameter; In response to the prediction result of the quality parameter value of any one of the quality parameters failing to satisfy the corresponding quality parameter limiting condition, the storage of the meat product is terminated.

6. The meat non-crystallization frozen storage intelligent preservation method according to claim 5, characterized in that: The obtaining a prediction result of a quality parameter value of the at least one quality parameter includes: Inputting the amorphous frozen storage temperature, the initial freshness parameter value, the storage time of the meat product and the electric field parameter into the quality parameter prediction model corresponding to each of the quality parameters, and outputting the prediction result of the quality parameter value of the quality parameter; The quality parameter prediction model is trained using the meat sample's amorphous frozen storage temperature, initial freshness parameter value, storage time and electric field parameters as input data, and the quality parameter value corresponding to the quality parameter after the storage time ends as output data.

7. An intelligent fresh-keeping system for meat without crystallization and freezing, characterized in that: include: An acquisition module is used to: acquire the initial freshness parameter value, target shelf life, comprehensive quality evaluation threshold and meat type of the meat to be stored, and acquire the amorphous temperature zone for achieving amorphous frozen storage of the meat; The process of determining the amorphous temperature zone includes: constructing an amorphous temperature data set of meat samples of the meat category; wherein the amorphous temperature data set includes electric field parameters and corresponding amorphous temperatures; taking the electric field parameters as independent variables and the amorphous temperature as dependent variables, obtaining an amorphous temperature prediction equation through fitting processing; solving the minimum temperature value of the amorphous temperature prediction equation; taking the minimum temperature value as the lowest amorphous temperature point for the meat of the meat category to achieve amorphous frozen storage; taking the supercooling temperature point of the meat of the meat category under the condition of no electric field as the upper limit temperature and the lowest amorphous temperature point as the lower limit temperature, determining the amorphous temperature zone for the meat to achieve amorphous frozen storage; The amorphous frozen storage critical temperature decision module is used to: input the initial freshness parameter value, the target shelf life and the comprehensive quality evaluation threshold into the amorphous frozen storage critical temperature decision model corresponding to the meat type, and output the amorphous frozen storage critical temperature; wherein the amorphous frozen storage critical temperature is the highest temperature required to ensure that the meat reaches the target shelf life; the amorphous frozen storage critical temperature decision model is obtained by training with training samples constructed based on the amorphous frozen storage critical temperature data set corresponding to the meat type, and the amorphous frozen storage critical temperature data set includes the initial freshness parameter value, shelf life, comprehensive quality evaluation threshold and the corresponding amorphous frozen storage critical temperature and electric field parameters of the meat sample; the input data when training the amorphous frozen storage critical temperature decision model includes the initial freshness parameter value, the shelf life and the comprehensive quality evaluation threshold, and the output data when training the amorphous frozen storage critical temperature decision model includes the amorphous frozen storage critical temperature; A crystallization-freezing temperature determination module is used to: determine the crystallization-freezing temperature of the meat product according to the crystallization-freezing critical temperature output by the crystallization-freezing critical temperature decision model; wherein the crystallization-freezing temperature is lower than or equal to the crystallization-freezing critical temperature and higher than or equal to the lower limit temperature of the crystallization temperature zone; An electric field parameter determination module, used to: determine the electric field parameter corresponding to the amorphous frozen storage temperature according to the amorphous frozen storage temperature and the amorphous frozen storage critical temperature data set; The frozen storage processing module is used to: perform electric field assisted storage of the meat product based on the amorphous frozen storage temperature and the electric field parameters; generate crystallization warning information in response to detecting that the temperature rise change rate exceeds a set range through the temperature sensor; in response to obtaining the crystallization warning information of the meat product, perform a crystallization ablation operation by applying a preset high-frequency and high-voltage alternating electric field, and after confirming the crystal ablation, re-execute the action of performing electric field assisted storage of the meat product based on the amorphous frozen storage temperature and the electric field parameters.

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