An automated production method for fish solubles preparation

Abstract

The application relates to the technical field of automation production, and discloses an automatic production method for fish solubles preparation, which comprises the following steps: confirming an automatic production system comprising a data fitting unit, a parameter input unit and an automatic production unit; confirming to receive a data fitting instruction from the data fitting unit; confirming a fitting database based on the data fitting instruction; searching for a fermentation enzyme type set and a raw material fish type set in the fitting database; sending the fermentation enzyme type set and the raw material fish type set to an initiating end of an automatic production instruction; receiving a target fermentation enzyme type and a target raw material fish type selected by a user from the fermentation enzyme type set and the raw material fish type set by using the parameter input unit; and searching for a target production parameter group in the fitting database by using the target fermentation enzyme type and the target raw material fish type. The application mainly aims to solve the problems of inaccurate parameter setting during fish solubles production and energy waste during production of fish solubles.

Description

TECHNICAL FIELD

[0001] The present application relates to an automatic production method for fish solubles preparation, and belongs to the technical field of automatic production. BACKGROUND

[0002] Fish solubles, as a high-quality animal protein source, has a wide range of applications in aquatic feed, pet food and other fields. With the increasing frequency of fish solubles use, more and more fish solubles are produced with inaccurate parameter settings, resulting in a large amount of resources being wasted. Therefore, how to accurately set the parameters of fish solubles during production has become a problem to be solved.

[0003] The existing method for setting the parameters of fish solubles during production mainly includes: fish solubles production personnel setting the parameters of fish solubles during production based on their own experience.

[0004] Although the above method can achieve the setting of the parameters of fish solubles during production, it is difficult to set parameters that meet each raw material when setting the production parameters of fish solubles. In addition, due to the differences in experience of fish solubles production personnel, the parameters of fish solubles during production are not accurately set, which further leads to the problem of resource waste during the production of fish solubles. SUMMARY

[0005] The present application provides an automatic production method for fish solubles preparation, device and computer readable storage medium, which mainly aims to solve the problems of inaccurate parameter setting during fish solubles production and energy waste during fish solubles production.

[0006] To achieve the above purpose, the present application provides an automatic production method for fish solubles preparation, which comprises:

[0007] receiving an automatic production instruction, and confirming an automatic production system based on the automatic production instruction, wherein the automatic production system comprises a data fitting unit, a parameter input unit and an automatic production unit;

[0008] confirming a data fitting instruction received from the data fitting unit, and confirming a fitting database based on the data fitting instruction;

[0009] retrieving a set of fermentation enzyme types and a set of raw material fish types from the fitting database, and sending the set of fermentation enzyme types and the set of raw material fish types to the initiator of the automatic production instruction; receiving a target fermentation enzyme type and a target raw material fish type selected by a user from the set of fermentation enzyme types and the set of raw material fish types by using the parameter input unit;

[0010] retrieving a target production parameter group from the fitting database by using the target fermentation enzyme type and the target raw material fish type;

[0011] confirming receiving an automation production instruction from the automatic production unit, and implementing the automation production of the fish solubility pulp based on the automation production instruction and the target production parameter set.

[0012] Optionally, the confirming the fitting database based on the data fitting instruction comprises:

[0013] obtaining an initial raw material fish set for producing the fish solubility pulp, wherein the initial raw material fish set comprises a plurality of initial raw material fishes, and obtaining a fish identification model set based on the data fitting instruction, wherein the fish identification model set comprises a plurality of fish identification models;

[0014] sequentially performing the following operations on the initial raw material fishes in the initial raw material fish set:

[0015] obtaining an identification species set by using the initial raw material fishes and the fish identification model set, wherein the identification species set comprises a plurality of fish identification species, and each fish identification species corresponds to one fish identification model;

[0016] respectively counting the number of fish identification species in the identification species set according to the fish identification species, to obtain an identification species number set, wherein the identification species number set comprises one or more identification species numbers;

[0017] performing the following operations on each identification species number in the one or more identification species numbers:

[0018] performing an identification operation on the identification species number by using the fish identification species corresponding to the identification species number, to obtain an identified identification species;

[0019] obtaining an identified identification species set by aggregating the identified identification species, performing a sorting operation on the identified identification species in the identified identification species set in descending order of the identification species number, to obtain an identified identification sequence;

[0020] extracting a first identified identification species and a second identified identification species from the identified identification sequence, calculating an absolute difference value between the identification species number corresponding to the first identified identification species and the identification species number corresponding to the second identified identification species, to obtain an evaluation difference value;

[0021] comparing the evaluation difference value with a preset evaluation threshold value;

[0022] if the evaluation difference value is greater than or equal to the evaluation threshold value, confirming that the species of the initial raw material fish is the fish identification species corresponding to the first identified identification species;

[0023] if the evaluation difference value is less than the evaluation threshold value, discarding the initial raw material fish;

[0024] collecting initial raw fish according to fish identification species to obtain one or more target raw fish sets;

[0025] confirming a fitting database based on the one or more target raw fish sets.

[0026] Optionally, the confirming a fitting database based on the one or more target raw fish sets comprises:

[0027] performing the following operations on each of the one or more target raw fish sets:

[0028] performing a crushing operation on the target raw fish set to obtain an initial crushed raw material set, performing a screening operation on the initial crushed raw material set by using a pre-constructed raw material screening machine to obtain a first screened raw material set and a second screened raw material set;

[0029] performing a weighing operation on the first screened raw material set and the second screened raw material set respectively to obtain a first screened quality and a second screened quality;

[0030] calculating a quality threshold value by using a preset proportion value and the second screened quality, wherein the quality threshold value is a product of the second screened quality and the proportion value, and comparing the quality threshold value with the first screened quality;

[0031] if the first screened quality is greater than the quality threshold value, taking the first screened raw material set as the target raw fish set, and returning to the crushing operation on the target raw fish set until the first screened quality is less than or equal to the quality threshold value;

[0032] if the first screened quality is less than or equal to the quality threshold value, collecting the first screened raw material set and the second screened raw material set to obtain a first crushed raw material set;

[0033] dividing the first crushed raw material set into a plurality of second crushed raw material sets by using a preset quality threshold value, wherein the quality corresponding to each second crushed raw material set is the quality threshold value;

[0034] performing the following operations on each of the plurality of second crushed raw material sets:

[0035] introducing the second crushed raw material set into a pre-constructed storage tank, introducing water with a preset volume threshold value into the storage tank to obtain an initial hydrolysis liquid, introducing the initial hydrolysis liquid into a pre-constructed cooking tank, and performing a cooking operation on the initial hydrolysis liquid by using the cooking tank with the initial hydrolysis liquid to obtain a target hydrolysis liquid;

[0036] performing a pressing operation on the target hydrolysis liquid to obtain an initial fish juice, performing a degreasing operation on the initial fish juice to obtain a fish soup raw material liquid;

[0037] The fish solubilized pulp stock solutions are aggregated to obtain a plurality of fish solubilized pulp stock solutions, and a fitting database is identified based on the plurality of fish solubilized pulp stock solutions.

[0038] Optionally, the identifying the fitting database based on the plurality of fish solubilized pulp stock solutions comprises:

[0039] A plurality of fish solubilized pulp stock solution groups are obtained using a preset grouping threshold and the plurality of fish solubilized pulp stock solutions, wherein the fish solubilized pulp stock solution groups each include a plurality of fish solubilized pulp stock solutions, and the number of the plurality of fish solubilized pulp stock solutions corresponds to the grouping threshold.

[0040] A set of protease species for enzymolysis is obtained, wherein the set of protease species includes a plurality of proteases.

[0041] For each of the plurality of proteases, the following operations are performed:

[0042] A set of parameter ranges is obtained based on the proteases, wherein the set of parameter ranges includes a temperature range, a pH range, a protease concentration range, and an enzymolysis time range.

[0043] A plurality of first temperature values are extracted from the temperature range using a preset first temperature division value, and a plurality of first pH values, a plurality of first protease concentration values, and a plurality of first enzymolysis times are obtained based on the pH range, the protease concentration range, and the enzymolysis time range, respectively.

[0044] In a combined form, a plurality of first experimental parameter groups are obtained using the plurality of first temperature values, the plurality of first pH values, the plurality of first protease concentration values, and the plurality of first enzymolysis times, wherein the first experimental parameter groups each include a first temperature value, a first pH value, a first protease concentration value, and a first enzymolysis time.

[0045] A plurality of first target experimental groups are obtained using the plurality of first experimental parameter groups and the plurality of fish solubilized pulp stock solution groups, wherein the first target experimental groups each include a first experimental parameter group and a fish solubilized pulp stock solution group, and the first experimental parameter group and the fish solubilized pulp stock solution group correspond to each other.

[0046] A fitting database is identified based on the plurality of first target experimental groups.

[0047] Optionally, the identifying the fitting database based on the plurality of first target experimental groups comprises:

[0048] For each of the plurality of first target experimental groups, the following operations are performed:

[0049] A set of initial pH values is obtained based on a fish solubilized pulp stock solution group corresponding to the first target experimental group, wherein the set of initial pH values includes a plurality of initial pH values, and each initial pH value corresponds to a fish solubilized pulp stock solution.

[0050] acquire an initial pH variance from the initial pH set, wherein the initial pH variance is a variance of the plurality of initial pH values in the initial pH set;

[0051] compare the initial pH variance with a preset pH variance threshold, and if the initial pH variance is greater than the pH variance threshold, perform the following operation on each initial pH value in the initial pH set:

[0052] acquire a screening pH set from the initial pH set and the initial pH value, wherein the screening pH set is a complement set of the initial pH value in the initial pH set;

[0053] calculate an evaluation pH value based on the initial pH value and the screening pH set, and the calculation formula is as follows:

[0054]

[0055] wherein, P i represents the evaluation pH value corresponding to the i-th initial pH value in the initial pH set, p i represents the i-th initial pH value in the initial pH set, q j represents the j-th initial pH value in the screening pH set, and n represents the total number of initial pH values in the screening pH set;

[0056] aggregate the evaluation pH values to obtain an evaluation pH value set, extract a removal pH value from the evaluation pH value set, wherein the removal pH value is the largest evaluation pH value in the evaluation pH value set, remove the initial pH value corresponding to the removal pH value from the initial pH set to obtain an updated pH set, take the updated pH set as the initial pH set, return to the step of acquiring the initial pH variance from the initial pH set, and repeat until the initial pH variance is less than or equal to the pH variance threshold;

[0057] record the number of removal pH values to obtain a removal number, and compare the removal number with a preset removal threshold;

[0058] if the removal number is greater than the removal threshold, acquire a third target experiment group from the first target experiment group corresponding to the first experiment parameter group, take the third target experiment group as the first target experiment group, and return to the step of acquiring the initial pH set from the fish soluble pulp stock solution group corresponding to the first target experiment group;

[0059] if the removal number is less than or equal to the removal threshold, confirm that the first target experiment group is a second target experiment group, aggregate the second target experiment groups to obtain a plurality of second target experiment groups, and confirm a fitting database based on the plurality of second target experiment groups.

[0060] Optionally, the confirming the fitting database based on the plurality of second target experimental groups comprises:

[0061] The following operations are performed on each of the plurality of second target experimental groups:

[0062] The following operations are performed on each of the plurality of fish solubles raw material liquids corresponding to the second target experimental group:

[0063] An adjusted fish solubles raw material liquid is obtained using the first pH value and the fish solubles raw material liquid corresponding to the second target experimental group, and an enzymatic hydrolysis operation is performed on the adjusted fish solubles raw material liquid based on the first temperature value, the first protease concentration value, and the first enzymatic hydrolysis time corresponding to the second target experimental group, to obtain an enzymatic hydrolysis raw material liquid;

[0064] An acid-soluble protein content is obtained using the pre-constructed acid-soluble protein content detection method and the enzymatic hydrolysis raw material liquid, and the acid-soluble protein contents are summarized to obtain an acid-soluble protein content set;

[0065] An average acid-soluble protein content is obtained from the acid-soluble protein content set, wherein the average acid-soluble protein content is the average of the plurality of acid-soluble protein contents in the acid-soluble protein content set;

[0066] The average acid-soluble protein contents are summarized to obtain an average acid-soluble protein content set, and the average acid-soluble protein contents in the average acid-soluble protein content set are sorted in descending order of the average acid-soluble protein contents to obtain an acid-soluble protein content sequence;

[0067] A target acid-soluble protein sequence is obtained based on the acid-soluble protein content sequence and a pre-set acid-soluble protein threshold value, wherein the target acid-soluble protein sequence includes a plurality of target acid-soluble protein contents, and the target acid-soluble protein contents are greater than or equal to the acid-soluble protein threshold value, and the fitting database is confirmed using the target acid-soluble protein sequence.

[0068] Optionally, the confirming the fitting database based on the plurality of second target experimental groups comprises:

[0069] The following operations are performed on each of the plurality of target acid-soluble protein contents in the target acid-soluble protein sequence:

[0070] A comprehensive evaluation value is calculated based on the target acid-soluble protein content and a pre-constructed comprehensive evaluation relationship, wherein the comprehensive evaluation relationship is as follows:

[0071]

[0072] wherein Z represents the comprehensive evaluation value, m represents the target acid-soluble protein content, a, τ, and β are all pre-set coefficients, and e phrepresents the unit energy consumption in adjusting the pH value, c1 represents the pH value corresponding to the first pH value, v0 represents the volume of the fish solubles raw material liquid, c2 represents the pH value corresponding to the initial pH value of the fish solubles raw material liquid, e(t, r) represents the energy consumption required when the temperature during the enzymatic hydrolysis operation is the first temperature value and the time during the enzymatic hydrolysis operation is the first enzymatic hydrolysis time, wherein t represents the first enzymatic hydrolysis time, and r represents the first temperature value, e o represents the energy consumption required when the concentration of the configured protease is the first protease concentration value;

[0073] aggregate the comprehensive evaluation values to obtain a comprehensive evaluation value set, and determine a target enzymatic hydrolysis parameter group based on the comprehensive evaluation value set, wherein the target enzymatic hydrolysis parameter group is the first experimental parameter group corresponding to the maximum comprehensive evaluation value in the comprehensive evaluation value set;

[0074] determine the fitting database by using the target enzymatic hydrolysis parameter group.

[0075] Optionally, the step of determining the fitting database by using the target enzymatic hydrolysis parameter group comprises:

[0076] introduce the enzymatic hydrolysis raw material liquid corresponding to the target enzymatic hydrolysis parameter group into a pre-constructed vacuum concentration tank, perform a vacuum concentration operation on the enzymatic hydrolysis raw material liquid by using the vacuum concentration tank into which the enzymatic hydrolysis raw material liquid is introduced, and obtain a raw liquid concentration group time sequence by using a pre-constructed concentration detector set, a pre-set detection time interval, and the enzymatic hydrolysis raw material liquid in the vacuum concentration operation, wherein the concentration detector set comprises a plurality of concentration detectors, the raw liquid concentration group time sequence comprises a plurality of raw liquid concentration groups, and each raw liquid concentration group comprises a plurality of raw liquid detection concentrations, wherein each raw liquid detection concentration corresponds to one of the concentration detectors.

[0077] perform the following operations on each raw liquid concentration group in the raw liquid concentration group time sequence:

[0078] calculate a detection concentration value by using the raw liquid concentration group and a pre-constructed concentration evaluation relationship, and compare the detection concentration value with a pre-set detection concentration threshold value.

[0079] if the detection concentration value is less than the detection concentration threshold value, obtain a vacuum concentration time by using the start time and a termination time corresponding to the detection concentration value, and determine the fitting database based on the vacuum concentration time.

[0080] Optionally, the concentration evaluation relationship is as follows:

[0081]

[0082] wherein Y represents the detection concentration value, x krepresents the kth stock solution detection concentration in the plurality of stock solution detection concentrations, d represents a total of d stock solution detection concentrations, ω k represents the kth preset coefficient, and σ represents the variance of the plurality of stock solution detection concentrations.

[0083] Optionally, the fitting database is confirmed based on the vacuum concentration time, and the fitting database comprises:

[0084] The fish species, the protease, and the vacuum concentration time corresponding to the target enzymolysis parameter group are associated with the target enzymolysis parameter group, to obtain a production parameter group.

[0085] The production parameter groups are summarized to obtain a production parameter group set, and a fitting database is constructed based on the production parameter group set.

[0086] To solve the above problems, the present application further provides an electronic device, which comprises:

[0087] at least one processor; and

[0088] a memory in communication connection with the at least one processor; wherein

[0089] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to implement the above-mentioned automatic production method for fish soluble pulp preparation.

[0090] To solve the above problems, the present application further provides a computer readable storage medium, which stores at least one instruction, and the at least one instruction is executed by a processor in an electronic device to implement the above-mentioned automatic production method for fish soluble pulp preparation.

[0091] Compared with the problems described in the background art, the application identifies the data fitting instruction from the data fitting unit, and identifies the fitting database based on the data fitting instruction. It can be seen that the application screens different types of fish when identifying the fitting database, and then uses the same type of fish to fit the parameters required for fish solubility in production, which can improve the accuracy of obtaining the fitting database. When using the same type of fish, the fish is broken to a predetermined proportion, i.e. a first set of broken raw materials is obtained. It can be seen that the application considers that the volume of the fish may affect the accuracy of identifying the parameters required for fish solubility in production, and then the first set of broken raw materials can improve the accuracy of obtaining the parameters for fish solubility production. Then, in a combined form, a plurality of first temperature values, a plurality of first pH values, a plurality of first protease concentration values and a plurality of first enzymolysis time values are used to obtain a plurality of first experimental parameter groups. It can be seen that the application considers that the protease suitable for different types of fish and the optimal temperature, optimal pH, optimal concentration value of the protease are different. Therefore, by obtaining a plurality of first experimental parameter groups, more accurate parameters can be obtained. The application calculates a comprehensive evaluation value based on the target acid-soluble protein content and the pre-constructed comprehensive evaluation relationship, and identifies the target enzymolysis parameter group based on the comprehensive evaluation value set. The target enzymolysis parameter group is the first experimental parameter group corresponding to the maximum comprehensive evaluation value in the comprehensive evaluation value set. It can be seen that the application uses the target acid-soluble protein content for evaluating the quality of fish solubility and the required energy consumption to identify the target enzymolysis parameter group in the comprehensive evaluation value set. When using the target enzymolysis parameter group to prepare fish solubility, not only can the quality requirements for preparing fish solubility be met, but also the energy consumption required for preparing fish solubility can be reduced. The start time and the end time are used to obtain the vacuum concentration time. It can be seen that the application also considers the time required for the vacuum concentration stage, and thus improves the automation degree of fish solubility production. In the fitting database, the fermentation enzyme type set and the raw material fish type set are retrieved, and the fermentation enzyme type set and the raw material fish type set are sent to the initiator of the automatic production instruction. The target fermentation enzyme type and the target raw material fish type selected by the user from the fermentation enzyme type set and the raw material fish type set are received by the parameter input unit. The target production parameter group is retrieved in the fitting database by using the target fermentation enzyme type and the target raw material fish type. By selecting parameters by the user, the parameters required for producing fish solubility under different conditions are obtained, and thus the accuracy of setting parameters for fish solubility production is improved. Therefore, the automatic production method, device, electronic equipment and computer readable storage medium for fish solubility preparation provided by the application mainly aim to solve the problems of inaccurate parameter setting for fish solubility production and energy consumption waste in producing fish solubility. BRIEF DESCRIPTION OF DRAWINGS

[0092] Figure 1 The flowchart of the automatic production method for fish solubility preparation provided by an embodiment of the application;

[0093] Figure 2 A structural schematic diagram of an electronic device for implementing the automatic production method for fish solubles preparation is provided in an embodiment of the present application.

[0094] The purposes, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0095] It should be understood that the specific embodiments described herein are merely illustrative of the present application and do not limit the present application.

[0096] An automatic production method for fish solubles preparation is provided in the embodiments of the present application. The execution subject of the automatic production method for fish solubles preparation includes, but is not limited to, at least one of electronic devices such as a server and a terminal, which can be configured to execute the method provided in the embodiments of the present application. In other words, the automatic production method for fish solubles preparation can be executed by software or hardware installed in a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0097] Embodiment 1

[0098] Referring to Figure 1 A flowchart of the automatic production method for fish solubles preparation is provided in an embodiment of the present application. In the embodiment, the automatic production method for fish solubles preparation includes:

[0099] S1, receiving an automatic production instruction, and confirming an automatic production system based on the automatic production instruction, wherein the automatic production system includes a data fitting unit, a parameter input unit and an automatic production unit.

[0100] It should be explained that the automatic production instruction is an instruction issued by a fish solubles production personnel. The automatic production system refers to an APP or a small program used to jointly control automatic production equipment to realize automatic production of fish solubles, and the automatic production system includes a data fitting unit, a parameter input unit and an automatic production unit. The application of specific units will be described in subsequent embodiments. The main purpose of the embodiments of the present application is to realize automatic production of fish solubles, improve the accuracy of parameters required during production of fish solubles, and reduce the energy consumption required during automatic production of fish solubles.

[0101] For example, Xiao Zhang is the person in charge of a fish solubles production line. In order to realize automatic production of fish solubles and reduce the energy consumption required during production, Xiao Zhang issues the automatic production instruction and confirms the automatic production system.

[0102] S2, confirming a fitting database based on the data fitting instruction.

[0103] It can be understood that the fitting database based on the data fitting instruction includes:

[0104] Obtaining an initial raw material fish set for producing fish slurry, wherein the initial raw material fish set includes a plurality of initial raw material fish, and obtaining a fish identification model set based on the data fitting instruction, wherein the fish identification model set includes a plurality of fish identification models;

[0105] In sequence, the initial raw material fish in the initial raw material fish set is executed as follows:

[0106] Using the initial raw material fish and the fish identification model set to obtain an identification species set, wherein the identification species set includes a plurality of fish identification species, and the fish identification species corresponds to the fish identification model one by one;

[0107] According to the fish identification species, the number of fish identification species in the identification species set is counted respectively to obtain an identification species number set, wherein the identification species number set includes one or more identification species numbers;

[0108] For each identification species number in the one or more identification species numbers, the following operation is performed:

[0109] Using the fish identification species corresponding to the identification species number to perform an identification operation on the identification species number to obtain an identified identification species;

[0110] Summarizing the identified identification species to obtain an identified identification species set, and performing a sorting operation on the identified identification species in the identified identification species set in descending order of the identification species number to obtain an identification sequence;

[0111] Extracting the first identified identification species and the second identified identification species in the identification sequence, and calculating the absolute difference between the identification species number corresponding to the first identified identification species and the identification species number corresponding to the second identified identification species to obtain an evaluation difference value;

[0112] Comparing the evaluation difference value with a preset evaluation threshold value;

[0113] If the evaluation difference value is greater than or equal to the evaluation threshold value, it is confirmed that the species of the initial raw material fish is the fish identification species corresponding to the first identified identification species;

[0114] If the evaluation difference value is less than the evaluation threshold value, the initial raw material fish is rejected;

[0115] According to the fish identification category, the initial raw material fish is summarized to obtain one or more target raw material fish sets;

[0116] Based on the one or more target raw material fish sets, a fitting database is confirmed.

[0117] It should be explained that the initial raw material fish refers to the raw material for producing fish solubles, i.e. fish. The fish identification model refers to a model capable of identifying the species of fish. Optionally, YOLOv5s is used as the fish identification model, and other technologies can achieve the same effect, which will not be described here. Fish identification category refers to the result of species identification of the initial raw material fish by the fish identification model.

[0118] It can be understood that different fish identification models correspond to different structures or training processes, so when different fish identification models are used to identify the species of the same fish, different results may be produced. Since the fish identification model cannot achieve 100% correct identification of the species of fish, when the evaluation difference is greater than or equal to the evaluation threshold, it is considered that the result of species identification of the initial raw material fish is reliable, and when the evaluation difference is less than the evaluation threshold, it is considered that the result of species identification of the initial raw material fish is not reliable. The reason for the evaluation difference being less than the evaluation threshold may be that the initial raw material fish is rotten, damaged, etc., resulting in inaccurate species identification of the initial raw material fish. Therefore, the initial raw material fish needs to be removed to improve the safety of the produced fish solubles. The purpose of removing the initial raw material fish when confirming the fitting database is to improve the accuracy of the data in the fitting database.

[0119] For example, the evaluation threshold is 2, the fish identification model set includes 5 fish identification models, and the result of identifying the initial raw material fish by the fish identification model set is: grass carp, grass carp, grass carp, bighead carp and carp. According to the fish identification category, the number of fish identification categories in the identification category set is counted to obtain three identification category numbers, which are 3, 1 and 1 respectively. The fish identification categories corresponding to the identification category numbers are identified by the identification category numbers, which can be identified as 1-bighead carp, 1-carp and 3-grass carp respectively. The identification category set is composed of 1-bighead carp, 1-carp and 3-grass carp. The identification categories are sorted in descending order of identification category number to obtain the identification sequence of 3-grass carp, 1-bighead carp and 1-carp. The evaluation difference is 2 based on the identification sequence, and the species of the initial raw material fish is confirmed to be grass carp when the evaluation difference is greater than or equal to the evaluation threshold.

[0120] Further, the fitting database is confirmed based on the one or more target raw material fish sets, which includes:

[0121] performing a crushing operation on each of the one or more target raw material fish sets to obtain an initial crushed raw material set, performing a screening operation on the initial crushed raw material set by using a pre-constructed raw material screening machine to obtain a first screened raw material set and a second screened raw material set;

[0122] performing a crushing operation on each of the one or more target raw material fish sets to obtain an initial crushed raw material set, performing a screening operation on the initial crushed raw material set by using a pre-constructed raw material screening machine to obtain a first screened raw material set and a second screened raw material set;

[0123] performing a crushing operation on each of the one or more target raw material fish sets to obtain an initial crushed raw material set, performing a screening operation on the initial crushed raw material set by using a pre-constructed raw material screening machine to obtain a first screened raw material set and a second screened raw material set;

[0124] performing a crushing operation on each of the one or more target raw material fish sets to obtain an initial crushed raw material set, performing a screening operation on the initial crushed raw material set by using a pre-constructed raw material screening machine to obtain a first screened raw material set and a second screened raw material set;

[0125] performing a crushing operation on each of the one or more target raw material fish sets to obtain an initial crushed raw material set, performing a screening operation on the initial crushed raw material set by using a pre-constructed raw material screening machine to obtain a first screened raw material set and a second screened raw material set;

[0126] performing a crushing operation on each of the one or more target raw material fish sets to obtain an initial crushed raw material set, performing a screening operation on the initial crushed raw material set by using a pre-constructed raw material screening machine to obtain a first screened raw material set and a second screened raw material set;

[0127] performing a crushing operation on each of the one or more target raw material fish sets to obtain an initial crushed raw material set, performing a screening operation on the initial crushed raw material set by using a pre-constructed raw material screening machine to obtain a first screened raw material set and a second screened raw material set;

[0128] performing a crushing operation on each of the one or more target raw material fish sets to obtain an initial crushed raw material set, performing a screening operation on the initial crushed raw material set by using a pre-constructed raw material screening machine to obtain a first screened raw material set and a second screened raw material set;

[0129] performing a crushing operation on each of the one or more target raw material fish sets to obtain an initial crushed raw material set, performing a screening operation on the initial crushed raw material set by using a pre-constructed raw material screening machine to obtain a first screened raw material set and a second screened raw material set;

[0130] performing a crushing operation on each of the one or more target raw material fish sets to obtain an initial crushed raw material set, performing a screening operation on the initial crushed raw material set by using a pre-constructed raw material screening machine to obtain a first screened raw material set and a second screened raw material set;

[0131] performing a crushing operation on each of the one or more target raw material fish sets to obtain an initial crushed raw material set, performing a screening operation on the initial crushed raw material set by using a pre-constructed raw material screening machine to obtain a first screened raw material set and a second screened raw material set;

[0132] It should be understood that the purpose of performing the crushing operation on the target raw material fish set is to increase the contact area of the initial crushed raw material set with water during the cooking process, thereby improving the efficiency of cooking the initial crushed raw material set. Optionally, a fish crusher is used to perform the crushing operation on the target raw material fish set to obtain the initial crushed raw material set. Optionally, a vibrating screen is used to perform the screening operation on the initial crushed raw material set, and other technologies can achieve the same effect, which will not be repeated here.

[0133] It can be understood that the first screened raw material set is the initial crushed raw material that cannot be screened, and the second screened raw material set refers to the initial crushed raw material that can be screened. Optionally, a pressure sensor is used to perform a weighing operation on the first screened raw material set and the second screened raw material set respectively to obtain the first screened mass and the second screened mass, and other technologies can achieve the same effect, which will not be repeated here. The purpose of comparing the mass threshold with the first screened mass is to verify whether the crushing process of the target raw material fish set meets the requirements. When the first screened mass is less than or equal to the mass threshold, it indicates that the crushing degree of the target raw material fish set is sufficient, i.e., it meets the crushing requirements, otherwise. Optionally, a steel-lined polyethylene storage tank is used as the storage tank, and other technologies can achieve the same effect, which will not be repeated here. The purpose of introducing the second crushed raw material set into the storage tank is to configure the second crushed raw material set as the initial hydrolysate that can be used for cooking according to the mass threshold. Optionally, a steam-heated cooking tank is used as the cooking tank, and other technologies can achieve the same effect, which will not be repeated here. The cooking operation refers to the process of heating the initial hydrolysate to boiling, and the technology of the cooking operation is a prior art, which will not be repeated here.

[0134] It should be understood that the purpose of performing the cooking operation on the initial hydrolysate is to prepare for subsequent enzymatic hydrolysis, and during the cooking process, water-soluble proteins, amino acids and other components of fish species can be extracted to provide more abundant raw materials for subsequent production of fish solubles, thereby improving the utilization rate of the initial hydrolysate and avoiding the problem of resource waste caused by low utilization rate of the initial hydrolysate. Optionally, a screw press is used to perform a pressing operation on the target hydrolysate, and other technologies can achieve the same effect, which will not be repeated here. The purpose of performing the pressing operation on the target hydrolysate is to extract the liquid in the target hydrolysate, which is the initial fish juice. Optionally, a centrifugal separation method is used to perform a degreasing operation on the initial fish juice, and other technologies can achieve the same effect, which will not be repeated here. The degreasing operation refers to the operation of removing fat from the initial fish juice.

[0135] Further, the fitting database is confirmed based on the plurality of fish solubles raw material liquids, comprising:

[0136] A plurality of fish solubilized slurry raw material groups are obtained by using a preset grouping threshold and a plurality of fish solubilized slurry raw materials, wherein the fish solubilized slurry raw material group includes a plurality of fish solubilized slurry raw materials, and the number of the plurality of fish solubilized slurry raw materials corresponds to the grouping threshold;

[0137] A set of protease species for enzymolysis is obtained, wherein the set of protease species includes a plurality of proteases;

[0138] For each of the plurality of proteases, the following operations are performed:

[0139] A set of parameter ranges is obtained based on the protease, wherein the set of parameter ranges includes a temperature range, a pH range, a protease concentration range, and an enzymolysis time range;

[0140] A plurality of first temperature values are extracted from the temperature range using a preset first temperature division value, and a plurality of first pH values, a plurality of first protease concentration values, and a plurality of first enzymolysis times are obtained based on the pH range, the protease concentration range, and the enzymolysis time range, respectively;

[0141] A plurality of first experimental parameter groups are obtained in a combined form using the plurality of first temperature values, the plurality of first pH values, the plurality of first protease concentration values, and the plurality of first enzymolysis times, wherein the first experimental parameter group includes a first temperature value, a first pH value, a first protease concentration value, and a first enzymolysis time;

[0142] A plurality of first target experimental groups are obtained using the plurality of first experimental parameter groups and the plurality of fish solubilized slurry raw material groups, wherein the first target experimental group includes a first experimental parameter group and a fish solubilized slurry raw material group, and the first experimental parameter group and the fish solubilized slurry raw material group correspond one-to-one;

[0143] A fitting database is confirmed according to the plurality of first target experimental groups.

[0144] It can be understood that the purpose of dividing the plurality of fish solubilized slurry raw materials into a plurality of fish solubilized slurry raw material groups using the grouping threshold is to improve the accuracy of subsequent testing of protease activity and to avoid the problem of inaccurate confirmation of the best parameters corresponding to protease activity due to accidental factors. The protease refers to a protease used for enzymolysis of fish solubilized slurry. Optionally, the protease is neutral protease, alkaline protease, etc.

[0145] It should be explained that the temperature range, the pH range, the protease concentration range, and the enzymolysis time range all refer to the temperature range, the pH range, the concentration range, and the time range in which a certain protease can perform enzymolysis, and the pH range can be represented by the pH value. In general, the temperature range, the pH range, the protease concentration range, and the enzymolysis time range can be obtained according to experience.

[0146] It should be understood that the first temperature division value refers to a value for uniformly extracting a plurality of first temperature values in a temperature range. For example, the temperature range is 30-40 degrees Celsius, and the first temperature division value is 11, so that 11 first temperature values can be extracted in the temperature range by using the first temperature division value, wherein the 11 first temperature values are 30 degrees Celsius, 31 degrees Celsius, 32 degrees Celsius, 33 degrees Celsius, 34 degrees Celsius, 35 degrees Celsius, 36 degrees Celsius, 37 degrees Celsius, 38 degrees Celsius, 39 degrees Celsius and 40 degrees Celsius. The method for obtaining a plurality of first pH values, a plurality of first protease concentration values and a plurality of first enzymolysis time based on the pH range, the protease concentration range and the enzymolysis time range is the same as the method for extracting a plurality of first temperature values in the temperature range by using the first temperature division value, and the same effect can be achieved, which will not be described here.

[0147] For example, the number of first temperature values is 2, the number of first pH values is 2, the number of first protease concentration values is 2, and the number of first enzymolysis time is 2, so that 16 first experimental parameter groups can be obtained in a combined manner.

[0148] It should be noted that the fitting database is confirmed according to the plurality of first target experimental groups, comprising:

[0149] The following operations are performed on each of the plurality of first target experimental groups:

[0150] An initial pH set is obtained based on the fish solubles raw material liquid group corresponding to the first target experimental group, wherein the initial pH set comprises a plurality of initial pH values, and each initial pH value corresponds to a fish solubles raw material liquid;

[0151] An initial pH variance is obtained by using the initial pH set, wherein the initial pH variance is the variance of the plurality of initial pH values in the initial pH set;

[0152] The initial pH variance is compared with a preset pH variance threshold value, and if the initial pH variance is greater than the pH variance threshold value, the following operations are performed on each initial pH value in the initial pH set:

[0153] A screening pH set is obtained by using the initial pH set and the initial pH value, wherein the screening pH set is the complement of the initial pH value in the initial pH set;

[0154] An evaluation pH value is calculated based on the initial pH value and the screening pH set, and the calculation formula is as follows:

[0155]

[0156] Wherein, P irepresents an evaluation pH value corresponding to the i-th initial pH value in the initial pH set, p i represents the i-th initial pH value in the initial pH set, q j represents the j-th initial pH value in the screening pH set, n represents the number of initial pH values in the screening pH set;

[0157] The evaluation pH values are summarized to obtain an evaluation pH value set, and a removal pH value is extracted from the evaluation pH value set, wherein the removal pH value is the largest evaluation pH value in the evaluation pH value set, and the initial pH value corresponding to the removal pH value is removed from the initial pH set to obtain an updated pH set. The updated pH set is used as the initial pH set, and the step of obtaining the initial pH variance from the initial pH set is returned until the initial pH variance is less than or equal to the pH variance threshold.

[0158] The number of removal pH values is recorded to obtain a removal number, and the removal number is compared with a preset removal threshold.

[0159] If the removal number is greater than the removal threshold, a third target experiment group is obtained using a first experiment parameter group corresponding to a first target experiment group, the third target experiment group is used as the first target experiment group, and the step of obtaining the initial pH set based on the fish slurry raw material liquid group corresponding to the first target experiment group is returned.

[0160] If the removal number is less than or equal to the removal threshold, the first target experiment group is confirmed as a second target experiment group, and a plurality of second target experiment groups are obtained by summarizing the second target experiment group. The fitting database is confirmed based on the plurality of second target experiment groups.

[0161] It should be explained that the initial pH value is the pH value of the fish slurry raw material liquid. Optionally, the initial pH value of the fish slurry raw material liquid is tested by using a pH meter, and other technologies can also achieve the same effect, which will not be described here. When the initial pH variance is greater than the pH variance threshold, it indicates that there may be fish that has deteriorated in the fish slurry raw material liquid. The difference between the fish recognition model and the fish recognition model is that the fish recognition model mostly recognizes fish by the appearance of the fish, and the same fish may be deteriorated without damage to the appearance.

[0162] It can be understood that the evaluation pH value can evaluate the deviation degree of the initial pH value from the mean value corresponding to the plurality of initial pH values in the screening pH set. The larger the evaluation pH value is, the greater the deviation degree of the initial pH value corresponding to the evaluation pH value is, that is, the greater the possibility of deteriorated or misidentified fish of the same species in the evaluation pH value is.

[0163] It should be understood that when the number of rejections is greater than or equal to the rejection threshold, it indicates that there are a large number of deteriorated or misidentified fish of the same species in the first target experimental group. Therefore, using the first target experimental group for experiments will lead to inaccurate experimental results or experimental results with randomness. For specific experimental steps, please refer to the subsequent embodiments. The way of obtaining the third target experimental group using the first experimental parameter group corresponding to the first target experimental group is the same as the way of obtaining the first target experimental group using the first experimental parameter group, and can achieve the same effect. Here, it is not repeated.

[0164] Further, the fitting database is confirmed based on the plurality of second target experimental groups, comprising:

[0165] The following operations are performed on each of the plurality of second target experimental groups:

[0166] The following operations are performed on each of the plurality of fish solubles raw material liquids corresponding to the second target experimental group:

[0167] The adjusted fish solubles raw material liquid is obtained using the first pH value corresponding to the second target experimental group and the fish solubles raw material liquid. The enzyme hydrolysis operation is performed on the adjusted fish solubles raw material liquid based on the first temperature value, the first protease concentration value and the first enzyme hydrolysis time corresponding to the second target experimental group, to obtain the enzyme hydrolysis raw material liquid;

[0168] The acid-soluble protein content is obtained using the pre-constructed acid-soluble protein content detection method and the enzyme hydrolysis raw material liquid. The acid-soluble protein content is summarized to obtain an acid-soluble protein content set;

[0169] The acid-soluble protein content mean value is obtained according to the acid-soluble protein content set, wherein the acid-soluble protein content mean value is the mean value of the plurality of acid-soluble protein contents in the acid-soluble protein content set;

[0170] The acid-soluble protein content mean value set is obtained by summarizing the acid-soluble protein content mean values. The acid-soluble protein content mean values in the acid-soluble protein content mean value set are sorted in descending order of the acid-soluble protein content mean values to obtain an acid-soluble protein content sequence;

[0171] The target acid-soluble protein sequence is obtained based on the acid-soluble protein content sequence and a pre-set acid-soluble protein threshold value, wherein the target acid-soluble protein sequence includes a plurality of target acid-soluble protein contents, and the target acid-soluble protein content is greater than or equal to the acid-soluble protein threshold value. The fitting database is confirmed using the target acid-soluble protein sequence.

[0172] It can be understood that the acid-soluble protein content detection method is a method capable of detecting the acid-soluble protein content in the enzymatic raw material liquid. Alternatively, the Kjeldahl method can be used as the acid-soluble protein content detection method, and other technologies can also achieve the same effect, which will not be described here. Acid-soluble protein refers to protein that can be dissolved under acidic conditions, mainly protein hydrolysate with low molecular weight, wherein the protein hydrolysate includes peptides and free amino acids. The acid-soluble protein content refers to the content of acid-soluble protein. The first pH value and the fish solubles raw material liquid are used to obtain the adjusted fish solubles raw material liquid, which refers to adjusting the pH of the fish solubles raw material liquid to the first pH value. For example, the pH of the fish solubles raw material liquid is 8, and the first pH value is 6. The pH of the fish solubles raw material liquid is adjusted to 6 by adding an acidic solution to the fish solubles raw material liquid, and the adjusted fish solubles raw material liquid is obtained.

[0173] It should be explained that the higher the average acid-soluble protein content is, the better the effect of enzymolysis is. By setting the acid-soluble protein threshold, the target acid-soluble protein content meeting the requirements can be screened from the acid-soluble protein content sequence.

[0174] It should be understood that the target acid-soluble protein sequence is used to confirm the fitting database, which includes:

[0175] The following operations are performed on each target acid-soluble protein content in the target acid-soluble protein sequence:

[0176] Based on the target acid-soluble protein content and the pre-constructed comprehensive evaluation relationship, a comprehensive evaluation value is calculated, wherein the comprehensive evaluation relationship is as follows:

[0177]

[0178] Wherein, Z represents the comprehensive evaluation value, m represents the target acid-soluble protein content, α, τ, β are all preset coefficients, e ph represents the unit energy consumption when adjusting the pH value, c1 represents the pH value corresponding to the first pH value, v0 represents the volume of the fish solubles raw material liquid, c2 represents the pH value corresponding to the initial pH value of the fish solubles raw material liquid, e(t, r) represents the energy consumption required when the temperature during the enzymolysis operation is the first temperature value and the time during the enzymolysis operation is the first enzymolysis time, wherein t represents the first enzymolysis time, r represents the first temperature value, e o represents the energy consumption required when the concentration of the protease is the first protease concentration value;

[0179] The comprehensive evaluation values are summarized to obtain a comprehensive evaluation value set, and a target enzymolysis parameter group is confirmed based on the comprehensive evaluation value set, wherein the target enzymolysis parameter group is the first experimental parameter group corresponding to the maximum comprehensive evaluation value in the comprehensive evaluation value set;

[0180] Confirming the fitting database by using the target enzymolysis parameter group.

[0181] It should be understood that the greater the comprehensive evaluation value indicates the better the effect of enzymolysis on the fish slurry raw material liquid and the less the energy consumption required. The unit energy consumption during pH adjustment is related to the solvent used during pH adjustment and its concentration. Alternatively, using a certain concentration of citric acid as the solvent used during pH adjustment, the unit energy consumption during pH adjustment is the unit energy consumption generated when the certain concentration of citric acid is configured, and the unit energy consumption is related to the volume. Alternatively, a plurality of energy consumption values when the temperature during enzymolysis operation is maintained at a first temperature value and the time during enzymolysis operation is a first enzymolysis time are obtained by constructing repetitive experiments, and the average of the plurality of energy consumption values is obtained, thereby obtaining the energy consumption required when the temperature during enzymolysis operation is maintained at a first temperature value and the time during enzymolysis operation is a first enzymolysis time. Other technologies can achieve the same effect, and details are not repeated here. Alternatively, the method for obtaining the energy consumption required when the concentration of protease is configured to a first protease concentration value is the same as the method for obtaining the energy consumption required when the temperature during enzymolysis operation is maintained at a first temperature value and the time during enzymolysis operation is a first enzymolysis time, and can achieve the same effect, and details are not repeated here.

[0182] Further, the confirming the fitting database by using the target enzymolysis parameter group comprises:

[0183] Introducing the enzymolysis raw material liquid corresponding to the target enzymolysis parameter group into the pre-constructed vacuum concentration tank, performing vacuum concentration operation on the enzymolysis raw material liquid by using the vacuum concentration tank into which the enzymolysis raw material liquid is introduced, and obtaining the raw liquid concentration group time sequence by using the pre-constructed concentration detector set, the pre-set detection time interval, and the enzymolysis raw material liquid in the vacuum concentration operation, wherein the concentration detector set comprises a plurality of concentration detectors, the raw liquid concentration group time sequence comprises a plurality of raw liquid concentration groups, and the raw liquid concentration group comprises a plurality of raw liquid detection concentrations, wherein the raw liquid detection concentration corresponds to the concentration detector.

[0184] Performing the following operation on each raw liquid concentration group in the raw liquid concentration group time sequence:

[0185] Calculating the detection concentration value by using the raw liquid concentration group and the pre-constructed concentration evaluation relationship, and comparing the detection concentration value with the pre-set detection concentration threshold value.

[0186] If the detection concentration value is less than the detection concentration threshold value, the termination time corresponding to the detection concentration value is used to obtain the vacuum concentration time by using the start time and the termination time, and the fitting database is confirmed based on the vacuum concentration time.

[0187] It should be explained that the vacuum concentration tank is a device for performing vacuum concentration operation, and a falling film concentration device can be used as the vacuum concentration tank, and other technologies can also achieve the same effect, which will not be described here. The purpose of performing vacuum concentration operation on the enzyme hydrolysis raw material liquid is to improve the concentration of the produced fish soup. The vacuum concentration operation refers to placing the frozen enzyme hydrolysis raw material liquid in a vacuum concentration tank with a water absorbing agent, and continuously vacuuming to concentrate the enzyme hydrolysis raw material liquid. The vacuum concentration operation is a prior art, which will not be described here.

[0188] It can be understood that the concentration detector refers to an instrument for detecting the enzyme hydrolysis raw material liquid during vacuum concentration operation. Alternatively, a fish soup concentration tester BRIX detector can be used as the concentration detector, and other technologies can also achieve the same effect, which will not be described here.

[0189] For example, the detection time interval is 5s, then part of the sample is extracted from the enzyme hydrolysis raw material liquid being vacuum concentrated every 5 seconds, and the concentration of the part of the sample is detected by using multiple concentration detectors in the concentration detector, to obtain a raw liquid concentration group. According to the order of the time corresponding to the obtained raw liquid concentration group from early to late, the multiple raw liquid concentration groups are sorted to obtain a raw liquid concentration group time sequence.

[0190] Further, when the detection concentration value is less than the detection concentration threshold value, it indicates that the enzyme hydrolysis raw material liquid subjected to vacuum concentration operation meets the concentration requirement and is stable. The vacuum concentration time refers to the absolute difference between the start time and the end time.

[0191] It should be understood that the concentration evaluation relationship is as follows:

[0192]

[0193] Wherein, Y represents the detection concentration value, x k represents the kth raw liquid detection concentration in the multiple raw liquid detection concentrations, d represents the total of d raw liquid detection concentrations, ω k represents the preset kth coefficient, and σ represents the variance of the multiple raw liquid detection concentrations.

[0194] It can be understood that the fitting database confirmed based on the vacuum concentration time comprises:

[0195] Associating the fish identification species, protease, and vacuum concentration time corresponding to the target enzyme hydrolysis parameter group with the target enzyme hydrolysis parameter group to obtain a production parameter group.

[0196] Summarizing the production parameter group to obtain a production parameter group set, and constructing a fitting database based on the production parameter group set.

[0197] Further, the fish identification species corresponding to the target enzymolysis parameter group, the protease, and the vacuum concentration time are associated with the target enzymolysis parameter group, so that all parameters for producing fish solubles by using a certain protease and a certain fish can be obtained. In general, the remaining parameters required in the production of fish solubles can be the same as the parameters set when obtaining the production parameter group. For example, the vacuum degree and temperature in the vacuum concentration operation.

[0198] S3, retrieving the fermentation enzyme species set and the raw material fish species set in the fitting database, and sending the fermentation enzyme species set and the raw material fish species set to the initiator of the automatic production instruction, receiving the target fermentation enzyme species and the target raw material fish species selected by the user in the fermentation enzyme species set and the raw material fish species set by using the parameter input unit.

[0199] It should be explained that the fermentation enzyme species set and the raw material fish species set are respectively the collection of fish identification species and the collection of proteases in the fitting database. The target fermentation enzyme species and the target raw material fish species are respectively the protease and the fish identification species selected by the user in the fermentation enzyme species set and the raw material fish species set.

[0200] For example, there are 5 proteases in the protease species set, but one protease in the protease species set cannot meet the requirement of obtaining the fitting database, so that only 4 proteases can be retrieved in the fitting database, and the fermentation enzyme species set is composed of the 4 proteases.

[0201] S4, retrieving the target production parameter group in the fitting database by using the target fermentation enzyme species and the target raw material fish species.

[0202] Further, the target production parameter group includes the vacuum concentration time and the target enzymolysis parameter group.

[0203] S5, confirming the automatic production instruction received from the automatic production unit, and realizing the automatic production of fish solubles based on the automatic production instruction and the target production parameter group.

[0204] It can be understood that the technology for realizing the automatic production of fish solubles by using the target production parameter group is prior art, which will not be described here.

[0205] For example, the parameters of each device used for producing fish solubles are set according to the target production parameter group and the automatic production instruction, and the automatic production of fish solubles is realized by using the devices after setting the parameters.

[0206] Compared with the problems described in the background art, the application identifies the data fitting instruction from the data fitting unit, and identifies the fitting database based on the data fitting instruction. It can be seen that the application screens different types of fish when identifying the fitting database, and then uses the same type of fish to fit the parameters required for fish solubility in production, which can improve the accuracy of obtaining the fitting database. When using the same type of fish, the fish is broken to a predetermined proportion, i.e. a first set of broken raw materials is obtained. It can be seen that the embodiment of the application considers that the volume of the fish may affect the accuracy of identifying the parameters required for fish solubility in production, and then the first set of broken raw materials can improve the accuracy of obtaining the parameters for fish solubility production. Then, in a combined form, a plurality of first temperature values, a plurality of first pH values, a plurality of first protease concentration values and a plurality of first enzymolysis time values are used to obtain a plurality of first experimental parameter groups. It can be seen that the application considers that the protease suitable for different types of fish and the optimal temperature, optimal pH, optimal concentration value of the protease are different. Therefore, by obtaining a plurality of first experimental parameter groups, more accurate parameters can be obtained. The application calculates a comprehensive evaluation value based on the target acid-soluble protein content and the pre-constructed comprehensive evaluation relationship, and identifies the target enzymolysis parameter group based on the comprehensive evaluation value set. The target enzymolysis parameter group is the first experimental parameter group corresponding to the maximum comprehensive evaluation value in the comprehensive evaluation value set. It can be seen that the application uses the target acid-soluble protein content for evaluating the quality of fish solubility and the required energy consumption to identify the target enzymolysis parameter group in the comprehensive evaluation value set, so that when the target enzymolysis parameter group is used to prepare fish solubility, not only the quality requirements for preparing fish solubility can be met, but also the energy consumption required for preparing fish solubility can be reduced. The start time and the end time are used to obtain the vacuum concentration time. It can be seen that the embodiment of the application also considers the time required for the vacuum concentration stage, and thus improves the automation degree of fish solubility production. The fermentation enzyme type set and the raw material fish type set are retrieved in the fitting database, and the fermentation enzyme type set and the raw material fish type set are sent to the initiator of the automatic production instruction. The target fermentation enzyme type and the target raw material fish type selected by the user in the fermentation enzyme type set and the raw material fish type set are received by the parameter input unit. The target production parameter group is retrieved in the fitting database by using the target fermentation enzyme type and the target raw material fish type. By selecting parameters by the user, the parameters required for producing fish solubility under different conditions are obtained, and thus the accuracy of setting parameters for fish solubility production is improved. Therefore, the automatic production method, device, electronic equipment and computer readable storage medium for fish solubility preparation provided by the application mainly aim to solve the problems of inaccurate parameter setting for fish solubility production and energy consumption waste in producing fish solubility.

[0207] Example 2:

[0208] As Figure 2As shown is a structural schematic diagram of an electronic device for implementing the automatic production method for fish solubility preparation according to an embodiment of the present application.

[0209] The electronic device 1 can include a processor 10, a memory 11, a bus 12 and a communication interface 13, and can further include a computer program stored in the memory 11 and executable on the processor 10, such as an automatic production program for fish solubility preparation.

[0210] The memory 11 includes at least one type of readable storage medium, such as a flash memory, a mobile hard disk, a multimedia card, a card-type memory (e.g., an SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a mobile hard disk of the electronic device 1. In other embodiments, the memory 11 can also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Further, the memory 11 can include both an internal storage unit and an external storage device of the electronic device 1. The memory 11 can be used not only to store application software and various data installed in the electronic device 1, such as the code of the automatic production program for fish solubility preparation, but also to temporarily store data that has been output or will be output.

[0211] The processor 10 can be composed of an integrated circuit in some embodiments, such as a single packaged integrated circuit or a plurality of packaged integrated circuits with the same or different functions, including one or more combinations of a central processing unit (CPU), a microprocessor, a digital processing chip, a graphics processor and various control chips, etc. The processor 10 is the control unit of the electronic device, which connects various components of the entire electronic device through various interfaces and lines, executes or runs programs or modules stored in the memory 11 (such as the automatic production program for fish solubility preparation, etc.), and calls data stored in the memory 11 to perform various functions and process data of the electronic device 1.

[0212] The bus can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable connection and communication between the memory 11, the at least one processor 10, etc.

[0213] Figure 2 Only the electronic device with components is shown, and those skilled in the art can understand that, Figure 2 The structure shown does not constitute a limitation on the electronic device 1, and can include fewer or more components than shown, or combine certain components, or different component arrangements.

[0214] For example, although not shown, the electronic device 1 can also include a power supply (such as a battery) to power each component. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, so that the power management device can implement functions such as charge management, discharge management, and power consumption management. The power supply can also include one or more direct current or alternating current power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, etc. The electronic device 1 can also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which are not described here.

[0215] Further, the electronic device 1 can also include a network interface, which can optionally include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), and is typically used to establish a communication connection between the electronic device 1 and other electronic devices.

[0216] Optionally, the electronic device 1 can also include a user interface, which can be a display (Display), an input unit (such as a keyboard (Keyboard)), and optionally a standard wired interface, a wireless interface. Optionally, in some embodiments, the display can be an LED display, a liquid crystal display, a touch liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch, etc. The display can also be appropriately referred to as a display screen or a display unit, and is used to display information processed in the electronic device 1 and to display a visualized user interface.

[0217] It should be understood that the embodiments are only for illustration and are not limited in the scope of the patent application by this structure.

[0218] The automation production program for fish solubles preparation stored in the memory 11 in the electronic device 1 is a combination of multiple instructions, which, when running in the processor 10, can realize:

[0219] receiving the automation production instruction, and confirming an automation production system based on the automation production instruction, wherein the automation production system comprises a data fitting unit, a parameter input unit and an automatic production unit;

[0220] confirming that a data fitting instruction from the data fitting unit is received, and confirming a fitting database based on the data fitting instruction;

[0221] retrieving a set of fermentation enzyme species and a set of raw material fish species in the fitting database, and sending the set of fermentation enzyme species and the set of raw material fish species to an initiating end of the automation production instruction, and receiving a target fermentation enzyme species and a target raw material fish species selected by a user from the set of fermentation enzyme species and the set of raw material fish species by using the parameter input unit;

[0222] retrieving a target production parameter group in the fitting database by using the target fermentation enzyme species and the target raw material fish species;

[0223] confirming that an automation production instruction from the automatic production unit is received, and realizing the automation production of the fish solubles based on the automation production instruction and the target production parameter group.

[0224] Specifically, the processor 10 can refer to the specific implementation method of the above instructions Figures 1 to 2 The description of related steps in the corresponding embodiments will not be repeated here.

[0225] Further, the modules / units integrated in the electronic device 1 can be stored in a computer readable storage medium if they are realized in the form of software function units and sold or used as independent products. The computer readable storage medium can be volatile or non-volatile. For example, the computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory).

[0226] The application also provides a computer readable storage medium, which stores a computer program, and the computer program can realize the following when being executed by a processor of an electronic device:

[0227] receiving the automation production instruction, and confirming an automation production system based on the automation production instruction, wherein the automation production system comprises a data fitting unit, a parameter input unit and an automatic production unit;

[0228] Confirming receiving data fitting instruction from the data fitting unit, confirming fitting database based on the data fitting instruction;

[0229] Retrieving the set of fermentation enzyme species and the set of raw material fish species in the fitting database, and sending the set of fermentation enzyme species and the set of raw material fish species to the initiator of the automatic production instruction, receiving the target fermentation enzyme species and the target raw material fish species selected by the user in the set of fermentation enzyme species and the set of raw material fish species by using the parameter input unit;

[0230] Retrieving the target production parameter group in the fitting database by using the target fermentation enzyme species and the target raw material fish species;

[0231] Confirming receiving automatic production instruction from the automatic production unit, and realizing the automatic production of fish solubles based on the automatic production instruction and the target production parameter group.

[0232] The modules described as separate components can or can not be physically separate, and the components displayed as modules can or can not be physical units, i.e. they can be located in one place or distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment.

[0233] In addition, the functional modules in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of hardware plus software functional modules.

[0234] It is obvious to those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and can be implemented in other specific forms without departing from the spirit or essential characteristics of the present application.

[0235] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. An automated production method for preparing fish slurry, characterized in that, The method includes: Receive automated production instructions, and confirm an automated production system based on the automated production instructions. The automated production system includes a data fitting unit, a parameter input unit, and an automated production unit. Confirm receipt of data fitting instructions from the data fitting unit, identify one or more target raw material fish sets based on the data fitting instructions, and identify a fitting database based on the one or more target raw material fish sets; The step of identifying a fitting database based on the one or more target raw material fish sets includes: For each of one or more target raw material fish sets, perform the following operation: The target raw material fish set is crushed to obtain an initial crushed raw material set. The initial crushed raw material set is then screened using a pre-constructed raw material screening machine to obtain a first screened raw material set and a second screened raw material set. Weigh the first set of raw materials and the second set of raw materials to obtain the mass of the first screening and the mass of the second screening, respectively. A quality threshold is calculated using a preset ratio value and a second screening quality, wherein the quality threshold is the product of the second screening quality and the ratio value, and the quality threshold is compared with the first screening quality. If the first screening quality is greater than the quality threshold, then the first screening raw material set is taken as the target raw material fish set, and the step of performing the crushing operation on the target raw material fish set is returned until the first screening quality is less than or equal to the quality threshold. If the first screening quality is less than or equal to the quality threshold, then the first screening raw material set and the second screening raw material set are combined to obtain the first crushed raw material set; Using a preset mass threshold, the first set of crushed raw materials is divided into multiple sets of second crushed raw materials, wherein the mass of the second set of crushed raw materials is the mass threshold. For each of the multiple secondary crushing raw material sets, the following operations are performed: The second set of crushed raw materials is introduced into a pre-constructed storage tank, and water with a preset volume threshold is introduced into the storage tank to obtain an initial hydrolysate. The initial hydrolysate is then introduced into a pre-constructed cooking tank, and the initial hydrolysate is cooked using the cooking tank to obtain the target hydrolysate. The target hydrolysate is pressed to obtain initial fish juice, and the initial fish juice is defatted to obtain fish slurry raw material liquid; By summarizing the fish lysate raw materials, multiple fish lysate raw materials are obtained, and a fitting database is identified based on these multiple fish lysate raw materials. The step of identifying a fitting database based on the plurality of fish slurry raw materials includes: Multiple fish lysate raw material groups are obtained using a preset grouping threshold and multiple fish lysate raw material liquids, wherein each fish lysate raw material liquid group includes multiple fish lysate raw material liquids, and the number of multiple fish lysate raw material liquids corresponds to the grouping threshold. Obtain a set of protease species for enzymatic hydrolysis, wherein the set of protease species includes multiple protease species; For each of the multiple proteases, the following procedure was performed: A set of parameter ranges is obtained based on the protease, wherein the set of parameter ranges includes: temperature range, pH range, protease concentration range, and enzymatic hydrolysis time range; Using a preset first temperature division value, multiple first temperature values ​​are extracted within the temperature range, and multiple first acid-base values, multiple first protease concentration values, and multiple first enzymatic hydrolysis times are obtained based on the acid-base range, protease concentration range, and enzymatic hydrolysis time range, respectively. In combination, multiple first experimental parameter sets are obtained using multiple first temperature values, multiple first pH values, multiple first protease concentration values, and multiple first enzymatic hydrolysis times. The first experimental parameter sets include first temperature values, first pH values, first protease concentration values, and first enzymatic hydrolysis times. Multiple first target experimental groups are obtained by using the multiple first experimental parameter groups and multiple fish sol raw material groups, wherein the first target experimental group includes the first experimental parameter group and the fish sol raw material group, and the first experimental parameter group and the fish sol raw material group correspond one-to-one. The fitting database was identified based on the multiple first target experimental groups; The set of fermentation enzymes and the set of raw fish species are retrieved from the fitting database. The set of fermentation enzymes and the set of raw fish species are sent to the initiator of the automated production instruction. The parameter input unit receives the target fermentation enzymes and target raw fish species selected by the user in the set of fermentation enzymes and the set of raw fish species. The target production parameter set was retrieved from the fitting database using the target fermentation enzyme type and the target raw material fish type. The automated production instruction from the automated production unit is received. Based on the automated production instruction and the target production parameter set, the automated production of fish slurry is realized.

2. The automated production method for preparing fish slurry as described in claim 1, characterized in that, The process of identifying one or more target raw material fish sets based on the data fitting instructions includes: Obtain an initial raw material fish set for producing fish slurry, wherein the initial raw material fish set includes multiple initial raw material fish; obtain a fish identification model set based on the data fitting instruction, wherein the fish identification model set includes multiple fish identification models. Perform the following operations on the initial raw material fish in the initial raw material fish set in sequence: The initial raw material fish and the fish identification model set are used to obtain an identification species set, wherein the identification species set includes multiple fish identification species, and the fish identification species correspond one-to-one with the fish identification model; Based on the fish species identified, the number of fish species in the identification species set is counted to obtain the identification species quantity set, wherein the identification species quantity set includes one or more identification species quantities; For each of the one or more identification categories, perform the following operation: The number of identified species is labeled using the corresponding number of fish species to obtain the labeled species. The identification categories are summarized to obtain an identification category set. The identification categories in the identification category set are then sorted in descending order of the number of identification categories to obtain an identification sequence. Extract the first and second identifier categories from the identifier recognition sequence, calculate the absolute difference between the number of identification categories corresponding to the first identifier category and the number of identification categories corresponding to the second identifier category, and obtain the evaluation difference. Compare the evaluation difference with a preset evaluation threshold; If the evaluation difference is greater than or equal to the evaluation threshold, then the species of the initial raw material fish is confirmed to be the fish species corresponding to the first identification species. If the evaluation difference is less than the evaluation threshold, the initial raw material fish is discarded. Based on the fish species identified, the initial raw material fish are summarized to obtain one or more target raw material fish sets.

3. The automated production method for preparing fish slurry as described in claim 2, characterized in that, The step of identifying the fitting database based on the plurality of first target experimental groups includes: For each of the multiple first-target experimental groups, the following operations were performed: An initial pH set is obtained based on the fish sol raw material liquid group corresponding to the first target experimental group. The initial pH set includes multiple initial pH values, and each initial pH value corresponds one-to-one with the fish sol raw material liquid. The initial pH value variance is obtained using the initial pH value set, wherein the initial pH value variance is the variance of multiple initial pH values ​​in the initial pH value set. Compare the initial pH variance with a preset pH variance threshold. If the initial pH variance is greater than the pH variance threshold, then perform the following operation on each initial pH value in the initial pH set: A screening set of pH values ​​is obtained using the initial pH set and initial pH values, wherein the screening set of pH values ​​is the complement of the initial pH values ​​in the initial pH set; Based on the initial pH value and the selected pH set, the pH value is calculated and evaluated using the following formula: Among them, P i p represents the evaluated pH value corresponding to the i-th initial pH value in the initial pH set. i q represents the i-th initial pH value in the initial pH set. j This indicates the j-th initial pH value in the pH set to be selected, and n indicates that there are n initial pH values ​​in the pH set to be selected. The assessed pH values ​​are summarized to obtain an assessed pH value set. A pH value to be removed is extracted from this set, where the removed pH value is the largest assessed pH value in the set. The initial pH value corresponding to the removed pH value is then removed from the initial pH set to obtain an updated pH set. Using this updated pH set as the initial pH set, the process returns to the step of obtaining the initial pH variance using the initial pH set, until the initial pH variance is less than or equal to the pH variance threshold. Record the number of pH values ​​that are removed, obtain the removal count, and compare the removal count with the preset removal threshold. If the number of rejections is greater than the rejection threshold, then the third target experimental group is obtained using the first experimental parameter group corresponding to the first target experimental group, and the third target experimental group is used as the first target experimental group. Then, the step of obtaining the initial pH set based on the fish slurry raw material liquid group corresponding to the first target experimental group is returned. If the number of eliminations is less than or equal to the elimination threshold, the first target experimental group is confirmed as the second target experimental group. The second target experimental groups are then aggregated to obtain multiple second target experimental groups. Based on the multiple second target experimental groups, the fitting database is confirmed.

4. The automated production method for preparing fish slurry as described in claim 3, characterized in that, The fitted database identified based on the multiple second-target experimental groups includes: For each of the multiple second-target experimental groups, the following operation was performed: For each of the multiple fish lysate raw materials corresponding to the second target experimental group, the following operations were performed: Using the first pH value and fish lysate raw material corresponding to the second target experimental group, an adjusted fish lysate raw material was obtained. Based on the first temperature value, first protease concentration value and first enzymatic hydrolysis time corresponding to the second target experimental group, an enzymatic hydrolysis operation was performed on the adjusted fish lysate raw material to obtain an enzymatic hydrolysate. The acid-soluble protein content is obtained by using a pre-constructed method for detecting acid-soluble protein content and the enzymatic hydrolysis raw material solution. The acid-soluble protein content is then summarized to obtain an acid-soluble protein content set. The mean value of acid-soluble protein content is obtained from the acid-soluble protein content set, where the mean value of acid-soluble protein content is the average value of multiple acid-soluble protein contents in the acid-soluble protein content set. The average acid-soluble protein content is summarized to obtain a set of average acid-soluble protein content. The average acid-soluble protein content in the set is sorted in descending order to obtain an acid-soluble protein content sequence. Based on the acid-soluble protein content sequence and the preset acid-soluble protein threshold, a target acid-soluble protein sequence is obtained, wherein the target acid-soluble protein sequence includes multiple target acid-soluble protein contents, and the target acid-soluble protein contents are greater than or equal to the acid-soluble protein threshold. The target acid-soluble protein sequence is used to confirm the fitting database.

5. The automated production method for preparing fish slurry as described in claim 4, characterized in that, The process of identifying the fitting database using the target acid-soluble protein sequence includes: For each target acid-soluble protein content in the target acid-soluble protein sequence, the following operation is performed: The comprehensive evaluation value is calculated based on the content of the target acid-soluble protein and the pre-constructed comprehensive evaluation formula, wherein the comprehensive evaluation formula is as follows: Where Z represents the comprehensive evaluation value, m represents the target acid-soluble protein content, α, τ, and β are all preset coefficients, and e ph This represents the unit energy consumption during pH adjustment, where c1 represents the pH value corresponding to the first pH level, v0 represents the volume of the fish lysate raw material, c2 represents the initial pH value corresponding to the fish lysate raw material, and e(t,r) represents the energy consumption required to maintain the temperature at the first temperature value and the time during the enzymatic hydrolysis operation at the first hydrolysis time, where t represents the first hydrolysis time, r represents the first temperature value, and e... o This indicates the energy required to prepare the protease at the concentration of the first protease. The comprehensive evaluation values ​​are summarized to obtain a comprehensive evaluation value set. Based on the comprehensive evaluation value set, the target enzymatic hydrolysis parameter set is identified. The target enzymatic hydrolysis parameter set is the first experimental parameter set corresponding to the largest comprehensive evaluation value in the comprehensive evaluation value set. The fitting database was identified using the target enzymatic hydrolysis parameter set.

6. The automated production method for preparing fish slurry as described in claim 5, characterized in that, The process of identifying the fitting database using the target enzymatic hydrolysis parameter set includes: The enzymatic hydrolysis raw material corresponding to the target enzymatic hydrolysis parameter group is introduced into a pre-constructed vacuum concentration tank. The enzymatic hydrolysis raw material is vacuum concentrated using the vacuum concentration tank. The time when the vacuum concentration operation begins is taken as the starting time. The stock solution concentration group time sequence is obtained using a pre-constructed concentration detector set, a preset detection time interval, and the enzymatic hydrolysis raw material during the vacuum concentration operation. The concentration detector set includes multiple concentration detectors, the stock solution concentration group time sequence includes multiple stock solution concentration groups, and the stock solution concentration group includes multiple stock solution detection concentrations. The stock solution detection concentration corresponds one-to-one with the concentration detector. For each stock solution concentration group in the time series, perform the following operation: The detection concentration value is calculated using the stock solution concentration group and the pre-constructed concentration evaluation formula, and the detection concentration value is compared with the preset detection concentration threshold. If the detected concentration value is less than the detected concentration threshold, the time corresponding to the detected concentration value is taken as the termination time. The vacuum concentration time is obtained using the start time and the termination time, and the fitting database is confirmed based on the vacuum concentration time.

7. The automated production method for preparing fish slurry as described in claim 6, characterized in that, The concentration assessment relationship is shown below: Where Y represents the detected concentration value, x k ω represents the k-th concentration of the stock solution among multiple stock solution detection concentrations, d represents the total d stock solution detection concentrations, and ω represents the k-th concentration among multiple stock solution detection concentrations. k σ represents the preset k-th coefficient, and σ represents the variance of the concentrations of multiple original solutions.

8. The automated production method for preparing fish slurry as described in claim 7, characterized in that, The process of identifying the fitting database based on the vacuum concentration time includes: By associating the fish species, protease, and vacuum concentration time corresponding to the target enzymatic hydrolysis parameter set with the target enzymatic hydrolysis parameter set, a production parameter set is obtained; The production parameter groups are summarized to obtain a production parameter set, and a fitting database is constructed based on the production parameter set.

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