Method and system for detecting the processing environment of braised beef

Abstract

The present invention provides a method and system for detecting a processing environment of soy sauce beef, and relates to the technical field of food processing environment detection. The method comprises: setting a sequence number for each step of the soy sauce beef processing flow, detecting the temperature data, humidity data, air cleanliness data and microbial content data of the processing station of each step, and determining the processing temperature compliance score according to the temperature data, microbial content data and sequence number; determining the processing humidity compliance score according to the humidity data, microbial content data and sequence number; determining the processing cleanliness compliance score according to the air cleanliness data, microbial content data and sequence number; determining the processing environment compliance score, and generating a processing environment assessment report. According to the present invention, targeted environmental monitoring can be carried out for different requirements of each step for the environment, so as to judge the compliance of the processing environment of each step, so as to accurately assess the impact of the processing environment on the quality of soy sauce beef.

Description

Technical Field

[0001] The invention relates to the technical field of food processing environment detection, and in particular to a method and system for detecting the processing environment of soy sauce beef. Background Art

[0002] In the related art, CN103424526B discloses a beef freshness detection device and detection method. First, three carrier gases are selected to detect the volatile gases generated by freshly slaughtered beef. The concentration of the volatile gases is judged according to the fitting accuracy of the detection model of each carrier gas. When only one of the three carrier gases has an R value less than 0.9, the concentration of the volatile gas is the most appropriate, which can ensure the accuracy of the detection; and the beef freshness prediction model is selected. The sensor array detects the beef W to be detected; the maximum signal-to-noise ratio SNRW of the beef W is obtained; the computer calculates the storage day value t of the beef W using the beef freshness prediction model; and the computer makes a judgment on whether the beef sample is unqualified or qualified in freshness. The scheme has the characteristics of accurate, objective and fast detection; and provides reliable data support for the production of food using beef with qualified freshness.

[0003] CN118624841A relates to the technical field of beef tenderloin processing production line, specifically an automated detection device and processing method for beef tenderloin processing, including a main bracket, a detection alarm mechanism is mounted inside the top of the main bracket, and a transmission frame is connected to the middle of the detection alarm mechanism, the detection alarm mechanism includes an equipment cavity, and a metal detection module is arranged at the bottom of the equipment cavity. In this scheme, in order to maintain a high degree of monitoring of the beef tenderloin production line and timely control of quality, this metal detection device is respectively arranged in the unpacking and thawing, vacuum pickling and quick freezing packaging processes in the beef tenderloin production process, through the synchronous monitoring of the three nodes, to avoid the presence of metal foreign matter in the material package before the processing process, or the mixing of metal foreign matter during the processing process, and cooperate with the on-site detection terminal and the wireless transmission module to transmit the detection information to the mobile terminal of the manager, so that the rejection and subsequent processing of unqualified products can be carried out more quickly, and the production efficiency and quality can be improved.

[0004] Therefore, in the related art, although the freshness of beef can be detected and the processing quality of beef can be monitored during the processing process, the processing of braised beef requires multiple steps, and the environmental conditions required for each step are different. For example, the ambient temperatures required for the thawing step and the marinating step are different, and the related technology makes it difficult to monitor the environmental conditions required for each step, making it difficult to determine the impact of the environmental conditions of each step on the quality of the braised beef.

[0005] The information disclosed in the background technology section of this application is only intended to deepen the understanding of the general background technology of this application, and should not be regarded as an admission or any form of suggestion that the information constitutes the prior art already known to those skilled in the art. Summary of the invention

[0006] The invention provides a method and system for detecting the processing environment of soy sauce beef, which can solve the technical problem that the related technology is difficult to monitor the environmental conditions required for each step.

[0007] According to a first aspect of the present invention, a method for detecting a processing environment of soy sauce beef is provided, comprising:

[0008] According to the order of the braised beef processing process, set serial numbers for each step of the braised beef processing process;

[0009] At multiple times during the processing of each step of the same batch of raw beef, the temperature data, humidity data and air cleanliness data of the processing station of each step are detected respectively, and the microbial content data of multiple sampling points of each processing station are detected respectively at the start and end time of each step;

[0010] Determining a processing temperature compliance score based on the temperature data of the processing station in each step, the microbial content data and the sequence number of each step;

[0011] Determining a processing humidity compliance score based on the humidity data of the processing station of each step, the microbial content data and the sequence number of each step;

[0012] Determining a processing cleanliness compliance score based on the air cleanliness data of the processing stations in each step, the microbial content data and the sequence number of each step;

[0013] Determining a processing environment compliance score based on the processing temperature compliance score, the processing humidity compliance score, and the processing cleanliness compliance score;

[0014] Generate a processing environment assessment report based on the processing environment compliance score.

[0015] According to a second aspect of the present invention, a system for detecting a processing environment for soy sauce beef is provided, comprising:

[0016] The serial number module is used to set serial numbers for each step of the braised beef processing process according to the order of the braised beef processing process;

[0017] The acquisition module is used to detect the temperature data, humidity data and air cleanliness data of the processing station of each step at multiple times during the processing of each step of the same batch of raw beef, and to detect the microbial content data of multiple sampling points of each processing station at the start and end time of each step;

[0018] A processing temperature compliance scoring module, for determining a processing temperature compliance score according to the temperature data of the processing station of each step, the microbial content data and the sequence number of each step;

[0019] A processing humidity compliance scoring module, for determining a processing humidity compliance score according to humidity data of processing stations in each step, the microbial content data and the sequence number of each step;

[0020] A processing cleanliness compliance scoring module, for determining a processing cleanliness compliance score according to the air cleanliness data of the processing station of each step, the microbial content data and the sequence number of each step;

[0021] A processing environment compliance scoring module, used to determine a processing environment compliance score according to the processing temperature compliance score, the processing humidity compliance score and the processing cleanliness compliance score;

[0022] The reporting module is used to generate a processing environment assessment report based on the processing environment compliance score.

[0023] Technical effect: According to the present invention, the temperature data, microbial content data, humidity data and air cleanliness data of the processing station of each step can be detected for each step in the processing flow of braised beef, so that targeted environmental monitoring can be carried out according to the different requirements of each step for the environment, so as to judge the compliance of the processing environment of each step, and then generate a processing environment assessment report to accurately evaluate the impact of the processing environment on the quality of braised beef. When determining the first relationship function, the first unknown coefficient can be set based on the law of the impact of the deviation of the temperature data of the processing station and the standard temperature data on the microbial activity, so as to fit the gap between the relative change rate of the microbial content data after changing the temperature data and the relative change rate of the microbial content data under the standard temperature data, and the relationship between the change in temperature data, so as to obtain a first relationship function that can accurately describe the impact of temperature on the relative change rate of the microbial content data. When solving the processing temperature compliance score, the first relationship function can be used to solve the predicted value of the microbial content data at the end of the processing process when the temperature of the processing station is the standard temperature data, and then determine the influence of temperature data on microbial activity, obtain the indirect influence of temperature data on the quality of braised beef, and obtain the direct influence of temperature data on the quality of braised beef through the similarity between the average temperature data and the standard temperature data in the processing process, so as to obtain the total influence of temperature data on the quality of braised beef in each step. Further, based on the rule that the earlier the step, the easier it is for the influence of temperature in the step on the quality of braised beef to accumulate to the subsequent steps, thereby causing a greater impact on the quality of the finished braised beef, the weight of the total influence of temperature data on the quality of braised beef in each step can be set, and then the weighted average is used to obtain the processing temperature compliance score, which can accurately and objectively represent the cumulative influence of temperature data in each step on the quality of the finished braised beef.

[0024] It should be understood that the above general description and the following detailed description are exemplary and explanatory only and do not limit the present invention. Other features and aspects of the present invention will become more apparent from the following detailed description of exemplary embodiments with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other embodiments can be obtained based on these drawings without creative work.

[0026] Figure 1 The flowchart of the method for detecting the processing environment of braised beef in soy sauce according to an embodiment of the present invention is exemplarily shown;

[0027] Figure 2 A block diagram of a detection system for processing environment of braised beef in soy sauce according to an embodiment of the present invention is exemplarily shown. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] The technical solution of the present invention is described in detail with specific embodiments below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0030] Figure 1 The flowchart of the method for detecting the processing environment of braised beef in soy sauce according to an embodiment of the present invention is exemplarily shown, and the method comprises:

[0031] Step S101, according to the sequence of the braised beef processing flow, set sequence numbers for each step of the braised beef processing flow;

[0032] Step S102, at multiple times during the processing of each step of the same batch of raw beef, respectively detect the temperature data, humidity data and air cleanliness data of the processing station of each step, and respectively detect the microbial content data of multiple sampling points of each processing station at the start time and the end time of each step;

[0033] Step S103, determining a processing temperature compliance score according to the temperature data of the processing station of each step, the microbial content data and the sequence number of each step;

[0034] Step S104, determining a processing humidity compliance score according to the humidity data of the processing stations of each step, the microbial content data and the sequence number of each step;

[0035] Step S105, determining a processing cleanliness compliance score according to the air cleanliness data of the processing station in each step, the microbial content data and the sequence number of each step;

[0036] Step S106, determining a processing environment compliance score according to the processing temperature compliance score, the processing humidity compliance score and the processing cleanliness compliance score;

[0037] Step S107, generating a processing environment assessment report according to the processing environment compliance score.

[0038] According to the method for detecting the processing environment of the braised beef in an embodiment of the present invention, the temperature data, microbial content data, humidity data and air cleanliness data of the processing station of each step can be detected respectively for multiple steps in the braised beef processing flow, so as to carry out targeted environmental monitoring according to the different requirements of each step for the environment, so as to judge the compliance of the processing environment of each step, and then generate a processing environment assessment report to accurately evaluate the impact of the processing environment on the quality of the braised beef.

[0039] According to one embodiment of the present invention, in step S101, the processing of soy sauce beef may include multiple steps such as thawing, pickling, braising, cooling and packaging of raw beef, and each step has different requirements for the environment. For example, the thawing step requires an ambient temperature of 12°C-18°C to avoid excessive high temperature, prevent microbial growth and reduce the quality of beef, while the pickling step requires an ambient temperature of 6°C-8°C to avoid temperature increase leading to microbial growth. For another example, the thawing step requires an ambient humidity of 60% relative humidity to prevent the water on the surface of the beef from evaporating too quickly, and the pickling step requires an ambient humidity of 90% relative humidity to prevent the surface of the beef from drying out. Therefore, the requirements for the processing environment of each step are different, and a sequence number can be set for each step to effectively manage the environment of the processing station of each step.

[0040] According to one embodiment of the present invention, in step S102, the processing time of each step is different. The temperature data, humidity data and air cleanliness data of the processing station can be detected at multiple times during the processing of each step, and the microbial content data of multiple sampling points of each processing station can be detected at the start and end of each step, so as to monitor the environment of each processing process and evaluate the impact of environmental factors on the quality of braised beef in each processing process.

[0041] According to one embodiment of the present invention, in step S103, the influence of the processing temperature of each processing station on the quality of the braised beef can be determined based on the temperature data of the processing stations in each step and the microbial content data. Among them, the temperature may cause abnormal changes in the microbial content. Therefore, in addition to detecting the deviation between the actual temperature and the temperature required for the step, it is also possible to monitor whether there is an abnormal change in the microbial content.

[0042] According to one embodiment of the present invention, a processing temperature compliance score is determined based on the temperature data of the processing station of each step, the microbial content data and the serial number of each step, including: determining the standard environmental information of each step, wherein the standard environmental information includes standard temperature data, standard humidity data and standard air cleanliness data; determining the standard processing time of each step; setting the humidity data of the test environment to the standard humidity data, and setting the air cleanliness data of the test environment to the standard air cleanliness data; in the test environment, setting a variety of temperature data, and respectively detecting the test microbial content data at the beginning and end of the standard processing time; determining a first relationship function between microbial content and temperature based on the test microbial content data and the set multiple temperature data; determining the processing time of each step; determining the processing temperature compliance score based on the first relationship function of each step, the processing time of each step, the temperature data of the processing station of each step, the microbial content data and the serial number of each step.

[0043] According to one embodiment of the present invention, it is possible to determine whether an abnormal change occurs in the microbial content. In this process, it is possible to first determine how the microbial content changes under normal conditions, that is, how it will change when the temperature meets the requirements of each step, and then combine the measured microbial content data to determine the difference between the change in the measured microbial content and the change in the microbial content under normal conditions, thereby determining the abnormal change in the microbial content.

[0044] According to one embodiment of the present invention, based on the above method, the change law of microbial content data under different temperature conditions can be tested. During the test process, the standard environment information of each step can be determined first, and a test environment can be set in which only the temperature changes, and the humidity and air cleanliness are maintained at the standard, that is, the humidity is maintained at the standard humidity data, the air cleanliness is maintained at the standard air cleanliness data, and only the temperature data of the test environment is changed, so as to test how the microbial content data detected in the test environment changes within the standard processing time, and the relationship between the microbial content data and the temperature data, that is, to determine the impact of temperature on the change of microbial content data.

[0045] According to one embodiment of the present invention, a temperature data can be set. After the temperature data is set, the duration of the maintenance is the standard processing time, and at the beginning and end of the standard processing time, the microbial content data is detected respectively, that is, the test microbial content data, so as to determine the change rate of the test microbial content data under the influence of the temperature, and the above temperature data can include standard temperature data. Further, after obtaining the change rate of the microbial content data under the influence of multiple temperatures, the relationship between the two can be determined, that is, the first relationship function.

[0046] According to one embodiment of the present invention, a first relationship function between microbial content and temperature is determined based on test microbial content data and multiple set temperature data, including: setting the temperature data of the test environment as standard temperature data, and respectively detecting the initial test microbial content data at the beginning and end of the standard processing time; adjusting the temperature data of the test environment based on the test temperature data, and respectively detecting the test microbial content data at the beginning and end of the standard processing time; determining the first relationship function based on the standard temperature data, the multiple set temperature data, the initial test microbial content data, the test microbial content data and the standard processing time.

[0047] According to one embodiment of the present invention, the temperature data of the test environment can be set as the standard temperature data, and the standard processing time can be maintained, and the reference microbial content data can be detected at the start and end of the standard processing time. Subsequently, the temperature data of the test environment can be adjusted, and the standard processing time can be maintained, and the test microbial content data can be obtained at the start and end of the standard processing time. Further, the temperature data can be adjusted multiple times, and multiple test microbial content data can be obtained. Then, the first relationship function can be obtained by combining the change rate of the reference microbial content data between the start and end of the standard processing time, and the change rate of the test microbial content data between the start and end of the standard processing time.

[0048] According to one embodiment of the present invention, determining the first relationship function according to the standard temperature data, the set multiple temperature data, the reference microbial content data, the test microbial content data and the standard processing time includes: determining the undetermined coefficient equation of the first relationship function according to formula (1),

[0049] (1)

[0050] in, is the test microbial content data at the end of the standard processing time measured during the jth test of the i-th step, is the test microbial content data at the beginning of the standard processing time measured during the jth test of the i-th step, is the standard processing time of the ith step, is the reference microbial content data at the end of the standard processing time of the i-th step, is the reference microbial content data at the beginning of the standard processing time of the i-th step, is the temperature data of the jth test in the i-th step, is the standard temperature data of the ith step, and is the first undetermined coefficient of the undetermined coefficient equation of the ith step; according to the temperature data during multiple tests and the test microbial content data, the first undetermined coefficient is solved to obtain the solution value of the first undetermined coefficient; according to the solution value of the first undetermined coefficient, the first relationship function is determined.

[0051] According to one embodiment of the present invention, It is the relative change of the reference microbial content data of the processing station when all environmental requirements are met within the standard processing time (that is, the temperature data of the processing station is the standard temperature data, the humidity data of the processing station is the standard humidity data, and the air cleanliness data of the processing station is the standard air cleanliness data). Therefore, That is, the relative change rate of the reference microbial content data of the processing station within the standard processing time when all environmental requirements are met. Then, the relative change rate of the test microbial content data of the processing station when the temperature data of the processing station is the set temperature data and other environmental requirements are met. The gap between the two relative change rates is related to the gap between the temperature data of the processing station, that is, the greater the deviation between the temperature data of the processing station and the standard temperature data, the greater the impact on the microbial activity, and the greater the gap in the above relative change rate. Therefore, by setting the first undetermined coefficient, the relationship between the gap between the relative change rate and the gap between the temperature data can be fitted to obtain the undetermined coefficient equation of the first relationship function. And the above first undetermined coefficient can be solved by the test microbial content data measured after multiple changes in the temperature data, and the deviation between the temperature data and the standard temperature data, to obtain the solution value of the first undetermined coefficient. Then, the solution value of the first undetermined coefficient can be substituted into the undetermined coefficient equation of the first relationship function, and the first relationship function can be obtained.

[0052] In this way, the first unknown coefficient can be set based on the law of how the deviation of the temperature data of the processing station and the standard temperature data affects the microbial activity, so as to fit the gap between the relative change rate of the microbial content data after the temperature data is changed and the relative change rate of the microbial content data under the standard temperature data, and the relationship between the change in temperature data, so as to obtain a first relationship function that can accurately describe the influence of temperature on the relative change rate of the microbial content data.

[0053] According to one embodiment of the present invention, there may be a certain deviation between the actual processing time of each step and the standard processing time, therefore, the processing time of each step, that is, the actual processing time, can be obtained. According to the first relationship function of each step, the processing time of each step, the temperature data of the processing station of each step, the microbial content data and the sequence number of each step, the processing temperature compliance score is determined, including: determining the processing temperature compliance score according to formula (2): ,

[0054] (2)

[0055] in, is the temperature data at the kth moment in the processing of the i-th step, m is the number of moments in the processing of the i-th step, N is the number of steps, is the microbial content data detected at the end of the i-th step, is the microbial content data detected at the beginning of the i-th step, is the processing time of the ith step, for The solution value of for The solution value of , k≤m, i≤N, and k, m, i and N are all positive integers.

[0056] According to one embodiment of the present invention, is the relative change in microbial content data between the end and start of the processing process, is the relative rate of change of microbial content data between the end and start of the processing process, which can be assumed to be is the relative change rate of the microbial content data between the end and start of the processing process under ideal conditions (i.e., the temperature of the processing station is the standard temperature data, and other environmental data are the same as the environmental data during the processing), where: is the predicted value of the microbial content data at the end of the processing process when the temperature of the processing station is the standard temperature data. Therefore, based on the first relationship function, it can be obtained:

[0057] ;

[0058] After finishing, we can get:

[0059] .

[0060] Therefore, when the temperature of the processing station is the standard temperature data, the deviation between the predicted value of the microbial content data at the end of the processing process and the actual microbial content data detected at the end of the i-th step is the effect of temperature on the microbial content.

[0061] According to one embodiment of the present invention,

[0062]

[0063] To represent the effect of temperature on microbial content, the higher the ratio, the smaller the measured microbial content data is relative to the predicted value of the microbial content, the average temperature data in the i-th step of the processing is less conducive to microbial reproduction relative to the standard temperature data, and is conducive to the processing quality of the braised beef; conversely, the lower the ratio, the more the average temperature data in the i-th step of the processing is relative to the standard temperature data, is more conducive to microbial reproduction, and is not conducive to the processing quality of the braised beef.

[0064] According to one embodiment of the present invention,

[0065] ,in, represents the average deviation between the average temperature data and the standard temperature data during the processing of the i-th step, so, It can represent the similarity between the average temperature data and the standard temperature data in the processing of the i-th step. The higher the similarity, the more conducive it is to the processing quality of the braised beef.

[0066] According to an embodiment of the present invention, both of the above two items can represent the impact of the environment on the processing quality of braised beef, wherein: It can show the direct impact of temperature data on the processing quality of braised beef. It indicates the influence of temperature data on microbial activity, which causes the microbial content to change relative to the ideal state, thus affecting the quality of the braised beef. Therefore, this item can represent the indirect influence of temperature data on the quality of braised beef. The product of the two can be used as the total influence of temperature data on the quality of braised beef.

[0067] According to one embodiment of the present invention, It can be used as the weight of the total impact of temperature data on the quality of braised beef. Since the smaller the step number, the earlier the step is, and the earlier it is affected by temperature, the impact of temperature on the quality of braised beef in this step is more likely to accumulate to subsequent steps, thereby causing a greater impact on the quality of the finished braised beef. Based on this, a higher weight can be given to the total impact of temperature data on the quality of braised beef in steps with smaller step numbers. Therefore, this item can be used as the weight of the total impact of temperature data on the quality of braised beef.

[0068] According to one embodiment of the present invention, the above-mentioned weights can be used to perform a weighted average on the total impact of the temperature data in each step on the quality of the braised beef, and a processing temperature compliance score can be obtained, which can be used to represent the cumulative impact of the temperature data in each step on the quality of the finished braised beef. The higher the processing temperature compliance score, the smaller the impact of the temperature data in each step on the quality of the finished braised beef, and the higher the quality of the finished braised beef.

[0069] In this way, the predicted value of the microbial content data at the end of the processing process can be solved by the first relationship function when the temperature of the processing station is the standard temperature data, and then the influence of the temperature data on the microbial activity can be determined, and the indirect influence of the temperature data on the quality of the braised beef can be obtained. The direct influence of the temperature data on the quality of the braised beef can be obtained by the similarity between the average temperature data and the standard temperature data in the processing process, so as to obtain the total influence of the temperature data on the quality of the braised beef in each step. Furthermore, based on the rule that the earlier the step, the easier it is for the influence of the temperature in the step on the quality of the braised beef to accumulate to the subsequent steps, thereby causing a greater impact on the quality of the finished braised beef, the weight of the total influence of the temperature data in each step on the quality of the braised beef can be set, and then the weighted average is used to obtain the processing temperature compliance score, which can accurately and objectively represent the cumulative influence of the temperature data in each step on the quality of the finished braised beef.

[0070] According to one embodiment of the present invention, in step S104, the processing humidity compliance score is solved in a similar manner to the processing temperature compliance score. Specifically, the processing humidity compliance score is determined according to the humidity data of the processing station of each step, the microbial content data and the serial number of each step, including: setting the temperature data of the test environment to the standard temperature data, and setting the air cleanliness data of the test environment to the standard air cleanliness data; in the test environment, setting a variety of humidity data, and respectively detecting the test microbial content data at the beginning and end of the standard processing time; determining the second relationship function between microbial content and humidity according to the test microbial content data and the set multiple humidity data; determining the processing time of each step; determining the processing humidity compliance score according to the second relationship function of each step, the processing time of each step, the humidity data of the processing station of each step, the microbial content data and the serial number of each step.

[0071] According to one embodiment of the present invention, when testing the effect of humidity on microbial activity and determining the second relationship function, the humidity data of the test environment can be set to standard humidity data, the standard processing time can be maintained, and the reference microbial content data can be detected at the start and end of the standard processing time. Subsequently, the humidity data of the test environment can be adjusted, the standard processing time can be maintained, and the test microbial content data can be obtained at the start and end of the standard processing time. Further, the humidity data can be adjusted multiple times and multiple test microbial content data can be obtained. Then, the change rate of the reference microbial content data between the start and end of the standard processing time and the change rate of the test microbial content data between the start and end of the standard processing time can be combined to obtain the second relationship function. The solution method of the second relationship function is similar to formula (1). The undetermined coefficients in formula (1) can be reset, and the difference between the temperature data and the standard temperature data at the jth test of the i-th step can be replaced by the difference between the humidity data and the standard humidity data at the jth test of the i-th step, and the new undetermined coefficients can be solved by the microbial content data measured after multiple humidity changes, so as to obtain the second relationship function. Furthermore, similar to formula (2), the predicted value of the microbial content data at the end of the processing process when the humidity of the processing station is the standard humidity data can be solved based on the second relationship function, and the ratio of the predicted value of the microbial content data at the end of the processing process to the measured value of the microbial content data can be solved as the indirect effect of humidity data on the quality of the marinated beef. The direct effect of humidity data on the quality of the marinated beef can also be solved in a similar way to the direct effect of temperature data on the quality of the marinated beef. The direct effect and the indirect effect can then be multiplied to obtain the total effect of humidity data on the quality of the marinated beef. Based on the rule that the smaller the sequence number of a step, the easier it is for the effect of humidity on the quality of the marinated beef in that step to accumulate to the subsequent steps, thereby causing a greater impact on the quality of the finished marinated beef, the following is set. The weight of the total impact of humidity data on the quality of braised beef is used as the weight, and the weighted average is used to obtain the cumulative impact of humidity data in each step on the quality of the finished braised beef product as the processing humidity compliance score.

[0072] According to one embodiment of the present invention, in step S105, the processing cleanliness compliance score is solved in a similar manner to the processing temperature compliance score. Specifically, the processing cleanliness compliance score is determined according to the air cleanliness data of the processing station of each step, the microbial content data and the serial number of each step, including: setting the temperature data of the test environment to the standard temperature data, and setting the humidity data of the test environment to the standard humidity data; in the test environment, setting a variety of air cleanliness data, and respectively detecting the test microbial content data at the beginning and end of the standard processing time; determining the third relationship function between the microbial content and the air cleanliness data according to the test microbial content data and the set multiple air cleanliness data; determining the processing time of each step; determining the processing cleanliness compliance score according to the third relationship function of each step, the processing time of each step, the air cleanliness data of the processing station of each step, the microbial content data and the serial number of each step.

[0073] According to one embodiment of the present invention, when testing the effect of air cleanliness on microbial activity and determining the third relationship function, the air cleanliness data of the test environment can be set to the standard air cleanliness data, and the standard processing time can be maintained, and the reference microbial content data can be detected at the start and end of the standard processing time. Subsequently, the air cleanliness data of the test environment can be adjusted, and the standard processing time can be maintained, and the test microbial content data can be obtained at the start and end of the standard processing time. Further, the air cleanliness data can be adjusted multiple times, and multiple test microbial content data can be obtained. The third relationship function can then be obtained by combining the change rate of the reference microbial content data between the start and end of the standard processing time, and the change rate of the test microbial content data between the start and end of the standard processing time. The solution method of the third relationship function is similar to that of formula (1). The undetermined coefficients in formula (1) can be reset, and the difference between the temperature data and the standard temperature data at the jth test of the i-th step can be replaced by the difference between the air cleanliness data and the standard air cleanliness data at the jth test of the i-th step, and the new undetermined coefficients can be solved by the microbial content data measured after multiple changes in air cleanliness, so as to obtain the third relationship function. Further, similar to formula (2), the predicted value of the microbial content data at the end of the processing process when the air cleanliness of the processing station is the standard air cleanliness data can be solved based on the third relationship function, and the ratio of the predicted value to the measured value of the microbial content data at the end of the processing process can be solved as the indirect effect of the air cleanliness data on the quality of the braised beef. The direct effect of the air cleanliness data on the processing quality of the braised beef can also be solved in a similar way to the direct effect of the temperature data on the processing quality of the braised beef, and then the direct effect and the indirect effect can be multiplied to obtain the total effect of the air cleanliness data on the quality of the braised beef. Based on the rule that the smaller the step number, the more likely the impact of air cleanliness on the quality of braised beef in this step will be accumulated to the subsequent steps, thus causing a greater impact on the quality of the finished braised beef, set The weight of the total impact of air cleanliness data on the quality of braised beef is used as the weight, and the weighted average is used to obtain the cumulative impact of air cleanliness data in each step on the quality of the finished braised beef product as the processing cleanliness compliance score.

[0074] According to one embodiment of the present invention, in step S106, the processing temperature compliance score, the processing humidity compliance score and the processing cleanliness compliance score may be weightedly summed to obtain a processing environment compliance score. The higher the processing environment compliance score, the closer the three environmental data of temperature, humidity and air cleanliness are to the standard data, and the smaller the impact on the quality of the braised beef, that is, the higher the quality of the braised beef.

[0075] According to one embodiment of the present invention, in step S107, a processing environment assessment report can be generated based on the processing environment compliance score. The report may include a processing temperature compliance score, a processing humidity compliance score, and a processing cleanliness compliance score, which are respectively used to describe the impact of the three environmental data on the processing quality of the sauce beef. It may also include a processing environment compliance score, which is used to describe the total impact of the three environmental data on the processing quality of the sauce beef. The strictness of the processing environment and the quality of the sauce beef can be represented by the processing environment compliance score, and a text report can be generated accordingly. For example, when the processing environment compliance score is high, a text report can be generated to describe the characteristics of the processing environment of the sauce beef being strictly controlled, very close to the standard environment, and the high quality of the sauce beef.

[0076] According to the method for detecting the processing environment of braised beef in an embodiment of the present invention, the temperature data, microbial content data, humidity data and air cleanliness data of the processing station of each step can be detected for each step in the braised beef processing flow, so that targeted environmental monitoring can be carried out for the different requirements of each step for the environment, so as to judge the compliance of the processing environment of each step, and then generate a processing environment assessment report to accurately assess the impact of the processing environment on the quality of braised beef. When determining the first relationship function, the first coefficient to be determined can be set based on the law of the influence of the deviation of the temperature data of the processing station and the standard temperature data on the microbial activity, so as to fit the gap between the relative change rate of the microbial content data after changing the temperature data and the relative change rate of the microbial content data under the standard temperature data, and the relationship between the change amount of the temperature data, so as to obtain a first relationship function that can accurately describe the influence of temperature on the relative change rate of the microbial content data. When solving the processing temperature compliance score, the first relationship function can be used to solve the predicted value of the microbial content data at the end of the processing process when the temperature of the processing station is the standard temperature data, and then determine the influence of temperature data on microbial activity, obtain the indirect influence of temperature data on the quality of braised beef, and obtain the direct influence of temperature data on the quality of braised beef through the similarity between the average temperature data and the standard temperature data in the processing process, so as to obtain the total influence of temperature data on the quality of braised beef in each step. Further, based on the rule that the earlier the step, the easier it is for the influence of temperature in the step on the quality of braised beef to accumulate to the subsequent steps, thereby causing a greater impact on the quality of the finished braised beef, the weight of the total influence of temperature data on the quality of braised beef in each step can be set, and then the weighted average is used to obtain the processing temperature compliance score, which can accurately and objectively represent the cumulative influence of temperature data in each step on the quality of the finished braised beef.

[0077] Figure 2A block diagram of a detection system for processing environment of soy sauce beef according to an embodiment of the present invention is exemplarily shown, and the system comprises:

[0078] The serial number module is used to set serial numbers for each step of the braised beef processing process according to the order of the braised beef processing process;

[0079] The acquisition module is used to detect the temperature data, humidity data and air cleanliness data of the processing station of each step at multiple times during the processing of each step of the same batch of raw beef, and to detect the microbial content data of multiple sampling points of each processing station at the start and end time of each step;

[0080] A processing temperature compliance scoring module, for determining a processing temperature compliance score according to the temperature data of the processing station of each step, the microbial content data and the sequence number of each step;

[0081] A processing humidity compliance scoring module, for determining a processing humidity compliance score according to humidity data of processing stations in each step, the microbial content data and the sequence number of each step;

[0082] A processing cleanliness compliance scoring module, for determining a processing cleanliness compliance score according to the air cleanliness data of the processing station of each step, the microbial content data and the sequence number of each step;

[0083] A processing environment compliance scoring module, used to determine a processing environment compliance score according to the processing temperature compliance score, the processing humidity compliance score and the processing cleanliness compliance score;

[0084] The reporting module is used to generate a processing environment assessment report based on the processing environment compliance score.

[0085] It should be understood by those skilled in the art that the embodiments of the present invention described above and shown in the accompanying drawings are only examples and do not limit the present invention. The purpose of the present invention has been fully and effectively achieved. The functional and structural principles of the present invention have been demonstrated and explained in the embodiments, and the embodiments of the present invention may be deformed or modified in any way without departing from the principles.

[0086] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting the processing environment of soy sauce beef, characterized in that: include: According to the order of the braised beef processing process, set serial numbers for each step of the braised beef processing process; At multiple times during the processing of each step of the same batch of raw beef, the temperature data, humidity data and air cleanliness data of the processing station of each step are detected respectively, and the microbial content data of multiple sampling points of each processing station are detected respectively at the start and end time of each step; Determining a processing temperature compliance score based on the temperature data of the processing station in each step, the microbial content data and the sequence number of each step; Determining a processing humidity compliance score based on the humidity data of the processing station of each step, the microbial content data and the sequence number of each step; Determining a processing cleanliness compliance score based on the air cleanliness data of the processing stations in each step, the microbial content data and the sequence number of each step; Determining a processing environment compliance score based on the processing temperature compliance score, the processing humidity compliance score, and the processing cleanliness compliance score; Generate a processing environment assessment report based on the processing environment compliance score; According to the temperature data of the processing station of each step, the microbial content data and the sequence number of each step, the processing temperature compliance score is determined, including: Determine standard environment information for each step, wherein the standard environment information includes standard temperature data, standard humidity data, and standard air cleanliness data; Determine the standard processing time for each step; The humidity data of the test environment is set as the standard humidity data, and the air cleanliness data of the test environment is set as the standard air cleanliness data; In the test environment, set a variety of temperature data, and detect the test microbial content data at the beginning and end of the standard processing time; Determine a first relationship function between microbial content and temperature according to the tested microbial content data and the set multiple temperature data; Determine the processing time for each step; Determining the processing temperature compliance score according to the first relationship function of each step, the processing time of each step, the temperature data of the processing station of each step, the microbial content data and the sequence number of each step; According to the tested microbial content data and the set multiple temperature data, a first relationship function between the microbial content and the temperature is determined, including: The temperature data of the test environment is set as the standard temperature data, and the reference microbial content data at the beginning and end of the standard processing time are respectively detected; Based on the test temperature data, adjust the temperature data of the test environment, and detect the test microbial content data at the beginning and end of the standard processing time respectively; Determining the first relationship function according to the standard temperature data, the set multiple temperature data, the reference microbial content data, the test microbial content data and the standard processing time; Determining the first relationship function according to the standard temperature data, the set multiple temperature data, the reference microbial content data, the test microbial content data and the standard processing time includes: According to the formula Determine the undetermined coefficient equation of the first relationship function, where: is the test microbial content data at the end of the standard processing time measured during the jth test of the i-th step, is the test microbial content data at the beginning of the standard processing time measured during the jth test of the i-th step, is the standard processing time of the ith step, is the reference microbial content data at the end of the standard processing time of the i-th step, is the reference microbial content data at the beginning of the standard processing time of the i-th step, is the temperature data of the jth test in the i-th step, is the standard temperature data of the ith step, and is the first undetermined coefficient of the undetermined coefficient equation of the i-th step; Solving the first undetermined coefficient according to the temperature data and the test microbial content data during multiple tests to obtain a solution value of the first undetermined coefficient; Determining the first relationship function according to the solved value of the first undetermined coefficient; Determining the processing temperature compliance score according to the first relationship function of each step, the processing time of each step, the temperature data of the processing station of each step, the microbial content data and the sequence number of each step, including: According to the formula Determining Processing Temperature Compliance Score ,in, is the temperature data at the kth moment in the processing of the i-th step, m is the number of moments in the processing of the i-th step, N is the number of steps, is the microbial content data detected at the end of the i-th step, is the microbial content data detected at the beginning of the i-th step, is the processing time of the ith step, for The solution value of for The solution value of , k≤m, i≤N, and k, m, i and N are all positive integers; According to the humidity data of the processing stations of each step, the microbial content data and the sequence number of each step, the processing humidity compliance score is determined, including: The temperature data of the test environment is set as the standard temperature data, and the air cleanliness data of the test environment is set as the standard air cleanliness data; In the test environment, set a variety of humidity data, and detect the test microbial content data at the beginning and end of the standard processing time; Determine a second relationship function between microbial content and humidity according to the tested microbial content data and the set multiple humidity data; Determine the processing time for each step; Determining the processing humidity compliance score according to the second relationship function of each step, the processing time of each step, the humidity data of the processing station of each step, the microbial content data and the sequence number of each step; The processing cleanliness compliance score is determined based on the air cleanliness data of the processing stations in each step, the microbial content data and the sequence number of each step, including: The temperature data of the test environment is set to the standard temperature data, and the humidity data of the test environment is set to the standard humidity data; In the test environment, set a variety of air cleanliness data, and test the test microbial content data at the beginning and end of the standard processing time; Determine a third relationship function between the microbial content and the air cleanliness data according to the tested microbial content data and the set multiple air cleanliness data; Determine the processing time for each step; The processing cleanliness compliance score is determined based on the third relationship function of each step, the processing time of each step, the air cleanliness data of the processing station of each step, the microbial content data and the sequence number of each step.

2. A detection system for processing environment of soy sauce beef for executing the method according to claim 1, characterized in that: include: The serial number module is used to set serial numbers for each step of the braised beef processing process according to the order of the braised beef processing process; The acquisition module is used to detect the temperature data, humidity data and air cleanliness data of the processing station of each step at multiple times during the processing of each step of the same batch of raw beef, and to detect the microbial content data of multiple sampling points of each processing station at the start and end time of each step; A processing temperature compliance scoring module, for determining a processing temperature compliance score according to the temperature data of the processing station of each step, the microbial content data and the sequence number of each step; A processing humidity compliance scoring module, for determining a processing humidity compliance score according to humidity data of processing stations in each step, the microbial content data and the sequence number of each step; A processing cleanliness compliance scoring module, for determining a processing cleanliness compliance score according to the air cleanliness data of the processing station of each step, the microbial content data and the sequence number of each step; A processing environment compliance scoring module, used to determine a processing environment compliance score according to the processing temperature compliance score, the processing humidity compliance score and the processing cleanliness compliance score; The reporting module is used to generate a processing environment assessment report based on the processing environment compliance score.

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