Food safety monitoring management method

Abstract

The invention discloses a food safety monitoring management method, which comprises the following steps: after food processing is completed, continuously collecting environmental parameters of a food storage environment; correcting the original shelf life of the food based on the continuously collected environmental parameters to obtain the latest real shelf life; and performing classification management on the food according to the corrected real shelf life. According to the food safety monitoring management method provided by the invention, the real shelf life of the food under the actual storage condition can be reflected more accurately, so that the food management efficiency and safety are improved, and the food waste is reduced.

Description

Technical Field

[0001] This invention belongs to the field of food management technology, and specifically relates to a food safety monitoring and management method. Background Technology

[0002] The shelf life of food refers to the maximum time a food product maintains its quality and safety under normal storage conditions. Traditional shelf-life labeling is usually based on accelerated destructive testing (ASLT) results under laboratory conditions, but this method ignores the impact of changes in the actual storage environment on the food's shelf life. During actual storage and transportation, changes in environmental parameters can significantly affect the rate of food spoilage. Therefore, a method is needed that can dynamically adjust the food's shelf life based on its storage environment to more accurately predict its true shelf life. Summary of the Invention

[0003] This invention provides a food safety monitoring and management method to solve the aforementioned technical problems, specifically adopting the following technical solution: A food safety monitoring and management method includes the following steps: After food processing is completed, environmental parameters of the food storage environment are continuously collected; The original shelf life of food is corrected based on continuously collected environmental parameters to obtain the latest true shelf life; Food products are categorized and managed based on their corrected, actual shelf-life dates.

[0004] Furthermore, the specific method for correcting the original shelf life of food based on continuously collected environmental parameters to obtain the latest true shelf life is as follows: Determine the storage conditions for food; The collected environmental parameters are compared with the storage condition parameters. When the collected environmental parameters exceed the threshold corresponding to the storage condition parameters, the impact of the excess on the shelf life is statistically analyzed, thereby correcting the original shelf life to obtain the latest true shelf life.

[0005] Furthermore, the method also includes handling scenarios without detection data, specifically the following steps: Record the time points when food enters or leaves the storage environment that can be monitored; For undetected blank time periods, cumulative statistics are performed using preset environmental parameters; The preset environmental parameters for the blank time period are combined with the actual measured environmental parameters to ensure data integrity.

[0006] Furthermore, for any undetected blank time periods, real weather data for those blank time periods is obtained, and preset environmental parameters are calculated based on the real weather data.

[0007] Furthermore, the original shelf life of the food is dynamically corrected using a preset shelf life correction model to obtain the latest true shelf life. The shelf life correction model uses the following formula for dynamic correction: Among them, t real To determine the corrected actual shelf life, t original E represents the original shelf life of food. i (t′) represents the actual measured value of the i-th environmental parameter at time t′, E i,thresh Let E be the threshold for the i-th environmental parameter. i When (t′) exceeds this threshold, it begins to affect the shelf life, E i,scale is the normalization factor for the i-th environmental parameter, used to unify parameters of different units and orders of magnitude to the same dimension, n is the total number of environmental parameters, and t is the total storage time of food.

[0008] Furthermore, the shelf-life correction model incorporates environmental parameter influence factors to adjust the degree of influence of different environmental parameters on shelf life. The formula is adjusted as follows: Where α i The influence factor of the i-th environmental parameter is determined based on the specific food type and the influence of environmental parameters on the food spoilage rate.

[0009] Furthermore, depending on the type of product, different calculation periods are used to correct the original shelf life of the food to obtain the latest true shelf life.

[0010] Furthermore, the calculation period is determined based on the actual shelf life, and the calculation period is calculated using the following formula: The value of a ranges from 0.001 to 0.01.

[0011] Furthermore, the shelf life decline rate is calculated based on the actual shelf life calculated from the number of consecutive predetermined cycles, and an early warning operation is performed when the decline rate exceeds a preset value.

[0012] Furthermore, the environmental parameters include temperature, humidity, and oxygen concentration.

[0013] The advantage of this invention is that the food safety monitoring and management method provided can more accurately reflect the true shelf life of food under actual storage conditions, thereby improving the efficiency and safety of food management and reducing food waste.

[0014] The advantage of this invention lies in the food safety monitoring and management method it provides. By monitoring and analyzing various environmental parameters in real time and dynamically adjusting the original shelf life of food, it can more accurately reflect the true shelf life of food. By promptly handling food that is nearing or has exceeded its shelf life, food safety problems can be effectively avoided. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of a food safety monitoring and management method according to the present invention. Detailed Implementation

[0017] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0018] like Figure 1 The image shows a food safety monitoring method according to this application, comprising the following steps: S1: After food processing is completed, continuously collect environmental parameters of the food storage environment.

[0019] S2: The original shelf life of food is corrected based on continuously collected environmental parameters to obtain the latest true shelf life.

[0020] S3: Classify and manage food according to the corrected true shelf life. The food safety monitoring method of this application, by real-time monitoring and analysis of environmental parameters and dynamically adjusting the original shelf life of food, can more accurately reflect the true shelf life of food. Using the true shelf life to determine the current state of food and promptly handling food approaching or exceeding its shelf life can effectively avoid food safety problems. The steps described above are detailed below.

[0021] For step S1: After food processing is completed, continuously collect environmental parameters of the food storage environment.

[0022] After food processing is completed, real-time collection of environmental parameters during food storage and transportation is fundamental to dynamically adjusting shelf life. In the embodiments of this application, environmental parameters include temperature, humidity, and oxygen concentration.

[0023] Specifically, a sensor network is installed in storage areas and transportation facilities to collect data. Preferably, a wireless sensor network is used for data collection, and the sensors include temperature sensors, humidity sensors, and oxygen concentration sensors, with a data collection frequency of once every 1-10 minutes. These sensors can be installed at various stages of food storage and transportation, including warehouses, transport vehicles, and retail stores.

[0024] To ensure data accuracy and reliability, sensor networks should possess the following characteristics: High precision: The sensor should have high precision and be able to accurately measure changes in environmental parameters.

[0025] Wireless transmission: Using wireless sensor networks can reduce the complexity of wiring and improve the flexibility and scalability of the system.

[0026] Distributed deployment: Sensors should be distributed throughout all stages of food storage and transportation to ensure comprehensive coverage.

[0027] For step S2: The original shelf life of the food is corrected based on the continuously collected environmental parameters to obtain the latest true shelf life.

[0028] In the embodiments of this application, the specific method for correcting the original shelf life of food based on continuously collected environmental parameters to obtain the latest true shelf life is as follows: The storage condition parameters for food are determined, and the collected environmental parameters are compared with the storage condition parameters. When the collected environmental parameters exceed the threshold corresponding to the storage condition parameters, the impact of the excess on the shelf life is statistically analyzed, thereby correcting the original shelf life to obtain the latest true shelf life.

[0029] It's understandable that every food product has its specific storage conditions, corresponding to a set of storage parameters. For example, the temperature should not exceed 20°C, humidity should not exceed 70%, and oxygen concentration should not exceed 21%. Under these conditions, food products can theoretically reach their preset original shelf life, at which point the actual shelf life is equal to the original shelf life. However, when one or more environmental parameters exceed their corresponding thresholds, the food's expiration will be accelerated over time, resulting in a shorter actual shelf life than the original shelf life. The greater the parameter exceeds the threshold and the longer it exceeds it, the shorter the actual shelf life will be. Therefore, by statistically analyzing the impact of these exceeded parameters on the shelf life, we can correct the original shelf life to obtain the latest actual shelf life.

[0030] In the embodiments of this application, the original shelf life of the food is dynamically corrected using a preset shelf life correction model to obtain the latest true shelf life. The shelf life correction model uses the following formula for dynamic correction: Among them, t real To determine the corrected actual shelf life, t original E represents the original shelf life of food. i (t′) represents the actual measured value of the i-th environmental parameter at time t′, E i,thresh Let E be the threshold for the i-th environmental parameter. i When (t′) exceeds this threshold, it begins to affect the shelf life, E i,scale is the normalization factor for the i-th environmental parameter, used to unify parameters of different units and orders of magnitude to the same dimension, n is the total number of environmental parameters, and t is the total storage time of food.

[0031] It is understandable that each environmental parameter E i There is a threshold E for each. i,thresh When the actual measured value E i When (t′) does not exceed this threshold, it has no effect on the shelf life. When E i (t′) exceeds E i,thresh At that time, the excess part of E i (t′) −E i,thresh It begins to affect the shelf life. The cumulative effect exceeding the threshold is calculated through integration. A normalization factor E is introduced into the formula. i,scale This is used to unify environmental parameters of different units and orders of magnitude to the same dimension, avoiding the unreasonable dominance of parameters with large values ​​on the correction effect. Normalization factor E i,scale The impact of different environmental parameters on shelf life is determined based on their typical range to ensure comparability. Finally, the cumulative effect is converted into an adjustment factor for shelf life. A larger cumulative effect results in a smaller exponential function value, thus shortening the shelf life.

[0032] For example, a certain food product has a shelf life of 5 days at 37°C, but its shelf life is shortened to 2 days at 47°C. By setting a temperature threshold of 37°C, it can be ensured that the shelf life is not affected below 37°C, while the shelf life begins to shorten above 37°C.

[0033] As a preferred implementation method, the shelf-life correction model further incorporates environmental parameter influence factors to adjust the degree of influence of different environmental parameters on shelf life. The formula is adjusted as follows: Where α i The influence factor of the i-th environmental parameter is determined based on the specific food type and the influence of environmental parameters on the food spoilage rate.

[0034] In this invention, the influence factor α iThis is used to quantify the impact of each environmental parameter on the food spoilage rate. Specifically, α i This represents the relative impact of the i-th environmental parameter (such as temperature, humidity, oxygen concentration, etc.) on the shelf life of food. By introducing influencing factors, the impact of different environmental parameters on food spoilage can be quantified and standardized, thereby more accurately correcting the shelf life of food.

[0035] Understandably, different foods have varying sensitivities to temperature, humidity, and oxygen concentration. For example, some foods are highly sensitive to temperature changes but relatively insensitive to humidity changes, while others may be more sensitive to humidity fluctuations. Each environmental parameter affects food spoilage through different mechanisms. For instance, temperature primarily affects chemical reaction rates and microbial growth rates; humidity affects the water activity of food and microbial growth; and oxygen concentration affects the oxidation reaction rate. Through experimental data and historical experience, the specific degree of influence of each environmental parameter on the spoilage rate of a particular food can be determined.

[0036] By introducing the influence factor α i This can more accurately reflect the impact of different environmental parameters on food spoilage, thereby improving the accuracy of shelf-life prediction. The influencing factors can be adjusted according to specific circumstances, such as optimization based on new experimental data or feedback from practical applications.

[0037] To determine the impact factor α of each environmental parameter on a specific food i The following experimental methods can be used: Accelerated Degradation Testing (ASLT): Accelerated degradation testing is conducted under different environmental conditions (such as different temperatures, humidity, and oxygen concentrations) to record the spoilage time of food.

[0038] Long-term stability test: Conduct a long-term stability test under actual storage conditions and record the quality changes of the food at different time points.

[0039] Microbiological and chemical analysis: Investigating the effects of environmental parameters on microbial growth and chemical reactions in food through microbiological and chemical analysis.

[0040] Experimental data can be used to analyze the impact of each environmental parameter on the food spoilage rate. The specific steps are as follows: Data collection: Collect food spoilage data under different environmental conditions, including spoilage time and quality indicators.

[0041] Data fitting: Using regression analysis or other statistical methods to fit the relationship between environmental parameters and food spoilage rate.

[0042] Determine the influencing factors: Based on the fitting results, determine the influencing factor α for each environmental parameter.i .

[0043] Here is a specific example illustrating how to set different influencing factors for different foods: Suppose we have three types of food: fresh meat, refrigerated juice, and canned food. Through experimental data and analysis, we obtain the following influencing factors: Fresh meat: Temperature influence factor α 温度 =0.8, humidity influence factor α 湿度 =0.2, oxygen concentration influence factor α 氧气 =0.1.

[0044] Refrigerated juice: Temperature influence factor α 温度 =0.5, humidity influence factor α 湿度 =0.3, oxygen concentration influence factor α 氧气 =0.2.

[0045] Canned foods: Temperature influence factor α 温度 =0.3, humidity influence factor α 湿度 =0.1, oxygen concentration influence factor α 氧气 =0.1.

[0046] These influencing factors reflect the sensitivity of different foods to environmental parameters. For example, fresh meat is very sensitive to temperature changes, so its temperature influencing factor is high; while canned food is relatively less sensitive to temperature changes, so its temperature influencing factor is low.

[0047] In practical applications, the influence factor α i It can be dynamically adjusted based on new experimental data or feedback from practical applications. For example: Regular updates: Conduct regular experimental verifications and update the impact factor based on new data.

[0048] Feedback mechanism: Adjust the influencing factors based on feedback from actual applications to improve the accuracy of shelf life prediction.

[0049] By setting the impact factor α i This method can more accurately reflect the impact of different environmental parameters on food spoilage, thereby improving the accuracy of shelf-life prediction. Specific influencing factors can be set according to food type and experimental data, and dynamically adjusted based on actual conditions. This approach not only improves the efficiency and safety of food management but also reduces food waste, and has broad application prospects.

[0050] When food is transferred through various storage environments with monitored environmental parameters, some intermediate processes lack environmental parameter monitoring capabilities, making it impossible to test the food during these processes. Furthermore, when these processes are lengthy, the missing steps become crucial for statistical analysis and cannot be ignored. Therefore, in the embodiments of this application, the method also includes handling scenarios where no detection data is available, specifically through the following steps: Record time points: Record the time points when food enters or leaves the detectable storage environment. This step ensures a clear record of the storage time of food in different environments, providing basic data for subsequent shelf-life correction.

[0051] Preset environmental parameters: For undetected blank time periods, preset environmental parameters are used for cumulative statistics. The preset environmental parameters can be set in advance according to specific circumstances, or reasonably estimated based on historical data or standard conditions.

[0052] Understandably, preset environmental parameters can be pre-set according to specific circumstances. As an alternative approach, for undetected blank time periods, real weather data for those periods can be obtained, and the preset environmental parameters can be calculated based on this data. This method utilizes external data sources (such as meteorological data) to supplement missing environmental parameters, further improving data accuracy and reliability. It's understandable that real weather data primarily reflects outdoor weather conditions, but even in intermediate stages, food is generally not placed directly outdoors; therefore, the obtained weather data cannot be directly used as preset environmental parameters. However, outdoor weather conditions are related to the indoor environment. Based on real outdoor weather data for this time period, the corresponding indoor environment can be calculated or predicted, thus serving as the preset environmental parameters.

[0053] Combined calculation: The preset environmental parameters of the blank time period are combined with the actual detected environmental parameters to ensure data integrity.

[0054] In the embodiments of this application, the original shelf life of the food is corrected using different calculation periods according to the type of product to obtain the latest true shelf life.

[0055] Different types of food have different sensitivities to environmental parameters, so it is necessary to select an appropriate calculation period to dynamically correct the shelf life based on the specific characteristics and storage requirements of the food.

[0056] The specific selection principles are as follows: Short-shelf-life foods (such as fresh and perishable foods): These foods typically have a short original shelf life and are highly sensitive to changes in environmental parameters. Therefore, it is recommended to use a shorter calculation cycle, such as performing shelf-life correction every hour. This allows for timely reflection of the impact of changes in environmental parameters on the food's shelf life, ensuring that the food is sold or used in its optimal condition.

[0057] Medium-shelf-life foods (such as processed foods and refrigerated foods): These foods have an original shelf life between that of short-shelf-life and long-shelf-life foods, and are somewhat sensitive to changes in environmental parameters. It is recommended to use a medium-length calculation cycle, such as performing shelf-life correction every two days. This cycle balances the frequency of correction with the feasibility of practical operation.

[0058] Long-shelf-life foods (such as canned foods and dried goods): These foods have a longer original shelf life and are relatively less sensitive to changes in environmental parameters. Therefore, a longer calculation cycle can be used, such as weekly shelf-life correction. This cycle can reduce the frequency of correction while ensuring that the weekly management of the food's shelf life remains within a reasonable range.

[0059] It is evident that a longer calculation period is used for foods with a longer shelf life, and a shorter period is used for foods with a shorter shelf life. However, in this application, the shelf life is varied. To more accurately select the calculation period, this application determines the calculation period based on the actual shelf life, and the calculation period is calculated using the following formula: The value of 'a' ranges from 0.001 to 0.01. This range accommodates different types of food, varying environmental parameters, and practical operational feasibility, ensuring that the calculation period T reasonably reflects the dynamic changes in food shelf life and improves the efficiency and safety of food management. When determining the specific value, a comprehensive consideration should be given to the type of food, storage environment, and actual operating conditions to determine the most suitable value for 'a'.

[0060] Correcting the original shelf life of food by using different calculation cycles according to the type of product is a scientific and practical method. By rationally selecting the calculation cycle and dynamically adjusting it based on changes in actual environmental parameters and the state of the food, the accuracy and timeliness of food shelf life management can be ensured, improving the efficiency and safety of food management and reducing food waste.

[0061] In practical applications, the selection and adjustment of the calculation cycle can be achieved through automated systems. For example, an IoT-based intelligent management system can be developed. This system can monitor the parameters of the food storage environment in real time and automatically adjust the calculation cycle according to preset rules. The system can dynamically determine the calculation cycle for each food based on its type, original shelf life, and real-time monitored changes in environmental parameters, and automatically perform shelf life correction.

[0062] For step S3: Classify and manage food products according to the corrected actual shelf life.

[0063] By dynamically adjusting shelf-life dates, the true condition of food under actual storage conditions can be more accurately reflected. Specifically, the time interval between the calculated true shelf-life and the current time is a key indicator for judging the food's condition. Based on the time interval between the true shelf-life and the current time, combined with the specific type of food, the current condition of the food can be determined. Different control measures are then implemented for different condition categories. This classification management method ensures that food is sold or used in its best condition, while promptly handling food that is nearing or past its expiration date to avoid food safety issues.

[0064] Specifically, an automated early warning system can be established to monitor the food's condition in real time based on the corrected shelf life. The system can issue different levels of warnings according to the food's condition category.

[0065] In the embodiments of this application, the shelf life decline rate is calculated based on the actual shelf life calculated from a predetermined number of consecutive cycles, and an early warning operation is performed when the decline rate exceeds a preset value.

[0066] This application provides a formula for calculating the descent rate, as follows: Among them, t real,k This represents the actual shelf life calculated in the k-th iteration. m is the predetermined number of iterations, and m > 2. R is the shelf life reduction rate. When the calculated shelf life reduction rate R is greater than the preset reduction rate threshold R... threshold When this occurs, an alert is triggered. The alert action can be sending an alarm to notify administrators.

[0067] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the above embodiments do not limit the present invention in any way, and all technical solutions obtained by equivalent substitution or equivalent transformation fall within the protection scope of the present invention.

Claims

1. A food safety monitoring and management method, characterized in that, Includes the following steps: After food processing is completed, environmental parameters of the food storage environment are continuously collected; The original shelf life of food is corrected based on continuously collected environmental parameters to obtain the latest true shelf life; Food products are categorized and managed based on their corrected, actual shelf-life dates.

2. The food safety monitoring and management method according to claim 1, characterized in that, The specific method for correcting the original shelf life of food based on continuously collected environmental parameters to obtain the latest true shelf life is as follows: Determine the storage conditions for food; The collected environmental parameters are compared with the storage condition parameters. When the collected environmental parameters exceed the threshold corresponding to the storage condition parameters, the impact of the excess on the shelf life is statistically analyzed, thereby correcting the original shelf life to obtain the latest true shelf life.

3. The food safety monitoring and management method according to claim 2, characterized in that, The method also includes handling scenarios with no detection data, the specific steps of which are as follows: Record the time points when food enters or leaves the storage environment that can be monitored; For undetected blank time periods, cumulative statistics are performed using preset environmental parameters; The preset environmental parameters for the blank time period are combined with the actual measured environmental parameters to ensure data integrity.

4. The food safety monitoring and management method according to claim 3, characterized in that, For any undetected blank time periods, obtain the actual weather data for those blank time periods and calculate the preset environmental parameters based on the actual weather data.

5. The food safety monitoring and management method according to claim 2, characterized in that, The original shelf life of food is dynamically corrected using a preset shelf life correction model to obtain the latest true shelf life. The shelf life correction model uses the following formula for dynamic correction: Among them, t real To determine the corrected actual shelf life, t original E represents the original shelf life of food. i (t′) represents the actual measured value of the i-th environmental parameter at time t′, E i,thresh Let E be the threshold for the i-th environmental parameter. i When (t′) exceeds this threshold, it begins to affect the shelf life, E i,scale is the normalization factor for the i-th environmental parameter, used to unify parameters of different units and orders of magnitude to the same dimension, n is the total number of environmental parameters, and t is the total storage time of food.

6. The food safety monitoring and management method according to claim 5, characterized in that, The shelf-life correction model further incorporates environmental parameter influence factors to adjust the degree of influence of different environmental parameters on shelf life. The formula is adjusted as follows: Where α i The influence factor of the i-th environmental parameter is determined based on the specific food type and the influence of environmental parameters on the food spoilage rate.

7. The food safety monitoring and management method according to claim 6, characterized in that, Depending on the type of product, different calculation periods are used to correct the original shelf life of the food to obtain the latest true shelf life.

8. The food safety monitoring and management method according to claim 7, characterized in that, The calculation period is determined based on the actual shelf life and is calculated using the following formula: The value of a ranges from 0.001 to 0.

01.

9. The food safety monitoring and management method according to claim 1, characterized in that, The shelf life decline rate is calculated based on the actual shelf life calculated from the number of consecutive predetermined cycles. When the decline rate exceeds the preset value, an early warning operation is performed.

10. The food safety monitoring and management method according to claim 1, characterized in that, The environmental parameters include temperature, humidity, and oxygen concentration.

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