A quality traceability management method for fresh food products

Abstract

The application discloses a quality traceability management method for fresh food, and belongs to the technical field of quality traceability management, and specifically comprises the following steps: receiving a traceability request and calling raw material processing state parameters, processing link gas environment parameters and logistics transportation link transportation state parameters, constructing a time axis continuous information main stem, scanning the transportation state parameters and intercepting the front and rear sequences of the gas environment parameters to generate a compensation data section when a collection breakpoint is identified, connecting the main stem, converting the packaging integrity parameters into gas permeation parameters, combining the illumination parameters to generate freshness decay trajectories, positioning the time point when the freshness index touches the preset threshold as the shelf life termination node on the trajectories, and outputting a quality traceability map, so that the transportation data breakpoint compensation and the shelf life termination node positioning which is jointly corrected by the retail packaging and the illumination factor are realized.

Description

Technical Field

[0001] This invention relates to the field of quality traceability management technology, and specifically to a quality traceability management method for fresh food. Background Technology

[0002] Fresh food products undergo numerous stages of frequent environmental changes, from raw material sorting, processing and packaging, logistics and transportation to shelf display, resulting in a continuous and dynamic decline in quality. As the supply chain continues to extend, quality-related data generated at each stage is scattered across different systems and participating entities. Consumers and regulators are increasingly demanding transparency in the quality information of the entire fresh food supply chain, making the establishment of traceability management methods covering the entire process from raw material handling to shelf display a key technological focus for the industry.

[0003] Existing quality traceability methods generally treat the status data of the logistics and transportation stages as a continuous sequence and directly integrate it into the traceability chain when constructing full-chain data records. When data collection breaks due to signal interruptions, equipment failures, or other reasons during logistics and transportation, existing methods typically discard the missing time period or fill in the gaps with simple linear interpolation. Fresh food continuously undergoes respiratory and metabolic activities within the gap period, and the concentration of gas components within its packaging changes non-linearly over time. The filler data generated by linear interpolation does not correspond to the actual physiological metabolic process of fresh food, resulting in a lack of physiological continuity between the gas concentration record for that period in the traceability chain and the data of the preceding and following stages. Furthermore, when determining the end-of-shelf-life position, most existing methods only mark the intersection of a single gas concentration threshold and the time axis, failing to incorporate differences in packaging sealing and changes in ambient light conditions at the retail stage into the process of determining the end-of-shelf-life position. Different levels of leakage in different packaging and different light intensities can alter the rate of change in gas composition within the packaging. Ignoring these two factors and directly extrapolating shelf life based on the initial gas concentration change trend leads to a discrepancy between the shelf life termination point marked in the traceability map and the quality change process of fresh food in the real retail environment. Summary of the Invention

[0004] The purpose of this invention is to provide a quality traceability management method for fresh food, and to solve the following technical problems:

[0005] Existing methods use linear interpolation to fill in data gaps in logistics and transportation. The filled data does not correspond to the physiological and metabolic processes of fresh food, and the shelf-life termination markers do not take into account the effects of packaging leakage and light exposure in the retail process, resulting in deviations in the traceability results.

[0006] The objective of this invention can be achieved through the following technical solutions: A method for quality traceability management of fresh food includes the following steps: S1. Receive a traceability request for a target fresh food product, the traceability request including a product identification code, the product identification code being associated with the production batch record of the fresh food product from raw material processing to shelf display; S2. Based on the product identification code, retrieve the status parameters of raw material processing, gas environment parameters of processing, and transportation status parameters of logistics and transportation from the management database. S3. Construct a dynamic traceability chain using the product identification code as the source point, and splice the status parameters, the gas environment parameters and the transportation status parameters in chronological order to generate a continuous information backbone on the time axis. S4. Scan the transportation status parameters. When the time interval between adjacent collection points is found to exceed the preset interval, extract the first and second segments of the gas environment parameters that enclose the time interval, generate a compensation data segment, and connect it to the information backbone. S5. Receive the packaging integrity parameters and ambient light parameters uploaded from the shelf display stage, and convert the packaging integrity parameters into gas permeation parameters. S6. Based on the gas environment parameters, gas permeation parameters and light parameters on the information backbone, generate a freshness decay trajectory; S7. Locate the time point on the freshness decay trajectory where the freshness index reaches the preset threshold, mark the time point as the shelf life termination node, and output the quality traceability map.

[0007] As a further aspect of the present invention: the specific process of retrieving the state parameters of the raw material processing in step S2 is as follows: In the raw material sorting process, multispectral response values ​​of raw materials in at least three different bands are collected. The physiological activity level of the corresponding raw material is determined based on the ratio of the response values ​​of two of the bands. The preset activity value corresponding to the physiological activity level is used as a status parameter. The status parameter is then associated with the raw material batch number and stored in the management database.

[0008] As a further aspect of the present invention: the specific process of splicing in chronological order in step S3 is as follows: Extract the collection timestamps of status parameters, gas environment parameters, and transportation status parameters. Retrieve the clock offset of each collection device relative to the standard time from the management database. Add the clock offset of the corresponding device to each timestamp to obtain the correction time point. Arrange all records in order of correction time points. Stack multiple records with the same correction time point according to the preset category order to form a continuous information backbone of the time axis.

[0009] As a further aspect of the present invention: the specific process of generating the compensation data segment in step S4 is as follows: Extract the first segment of the sequence whose timestamp is earlier than the start time of the breakpoint interval and the second segment of the sequence whose timestamp is later than the end time of the breakpoint interval from the gas environment parameters. Extract the vibration intensity of a complete record whose timestamp is earlier than the start time of the breakpoint interval from the transport state parameters as the disturbance intensity. Extract the gas concentration value at the end of the first segment of the sequence and the gas concentration value at the start of the second segment of the sequence. Calculate the time change rate of the gas concentration value in the first segment of the sequence. By inputting the state parameters and disturbance intensity into the preset metabolic influence correspondence, the respiratory rate regulation factor and respiratory quotient regulation value are obtained. The time change rate is multiplied by the respiratory rate regulation factor to obtain the corrected change rate. Starting from the gas concentration value at the end of the previous sequence, the gas concentration value at each time point in the breakpoint interval is calculated along the corrected change rate under the constraint of the respiratory quotient regulation value until the calculated result is connected with the gas concentration value at the beginning of the next sequence. The calculated result is used as the compensation data segment.

[0010] As a further aspect of the present invention: the specific process of setting the preset interval in S4 is as follows: Retrieve the transportation status parameters of the logistics transportation links associated with the current traceability request within a preset historical time period from the management database, extract the time span values ​​of all identified interrupted collection segments, take the time span value at the middle position, and multiply the time span value at the middle position by the tolerance coefficient obtained based on the target fresh food category to obtain the preset interval.

[0011] As a further aspect of the present invention: in step S5, the specific process of converting the packaging integrity parameter into a gas permeation parameter is as follows: The packaging integrity parameters include the leak pore diameter and leak path length measurements obtained from the sealing test of the retail packaging, the gas permeability coefficient of the materials used in the retail packaging retrieved from the management database, the equivalent leak cross-sectional area calculated based on the leak pore diameter and leak path length measurements, and the gas permeability parameter obtained by multiplying the gas permeability coefficient by the equivalent leak cross-sectional area.

[0012] As a further aspect of the present invention: the specific process of generating the freshness decay trajectory in step S6 is as follows: The gas environment parameters after the packaging completion time are extracted from the information backbone. The gas concentration value and the headspace volume value of the packaging are obtained at each time point. The total amount of gas inside the packaging is calculated, and the partial pressure of the gas outside the packaging is obtained. The difference between the partial pressure of the gas outside the packaging and the partial pressure of the gas inside the packaging is multiplied by the gas permeation parameter to obtain the gas permeation amount per unit time. The light intensity value in the light parameter is multiplied by the preset photosensitivity coefficient of the target fresh food to obtain the photoinduced gas consumption per unit time. The total amount of gas inside the packaging and the gas concentration value are updated at each time step. The updated gas concentration value is input into the preset freshness conversion relationship to obtain the freshness index value of the corresponding time step. The freshness index values ​​of all time steps are connected in chronological order to form a curve to obtain the freshness decay trajectory.

[0013] As a further aspect of the present invention: the specific process of outputting the quality traceability map in step S7 is as follows: A horizontal timeline is drawn, on which are placed in chronological order: status parameter markers for raw material processing time points, gas parameter markers for time points when gas concentration in the processing stage falls below the preset warning line, time strip markers for the compensation data segment coverage area, and shelf-life termination node markers. The visual attributes of the status parameter markers correspond to the numerical values ​​of the status parameters. The gas parameter markers are connected to the gas environment parameter curve. The time strip markers cover the corresponding time span with a fill style that is different from other segments and are marked with data calculation indicators. The shelf-life termination node markers are marked with an end timestamp. Below the horizontal timeline, an instruction response area is set for each marker. After receiving a selection instruction, the instruction response area generates an information card, which lists the collection information and calculation explanation of the data associated with the corresponding marker.

[0014] The beneficial effects of this invention are: This invention constructs a continuous timeline information backbone with the product identification code as the source. When a data collection interruption occurs in the vibration recording during logistics and transportation, instead of using linear interpolation to fill the missing data, it extracts the gas environment parameter sequence before and after the interruption interval. Combined with the state parameters obtained in the raw material processing stage and the transportation vibration intensity, it retrieves the corresponding relationship of metabolic influence to obtain the respiratory rate regulation factor and respiratory quotient regulation value. Based on this, it extrapolates the gas concentration value within the interruption interval point by point along the corrected gas concentration change rate, so that the compensation data segment corresponds to the actual physiological metabolic process of fresh food during the interruption period, thus maintaining the physiological continuity of gas concentration records in the traceability chain. When determining the end-of-shelf-life node, the measured values ​​of the leakage aperture and leakage channel length of the retail packaging are converted into gas permeation parameters. The light intensity value of the surrounding environment is multiplied by a preset photosensitivity coefficient to obtain the photoinduced gas consumption. At each time step, the total gas volume and gas concentration values ​​inside the packaging are updated using the gas permeation and photoinduced gas consumption values. Then, based on the updated gas concentration values, freshness indicators are calculated and a freshness decay trajectory is generated. This allows the end-of-shelf-life nodes marked in the traceability map to comprehensively reflect the impact of differences in packaging sealing and changes in light conditions at the retail stage on the quality decay process of fresh food. Attached Figure Description

[0015] The invention will now be further described with reference to the accompanying drawings.

[0016] Figure 1 This is a flowchart illustrating the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Please see Figure 1 As shown, this invention is a method for quality traceability management of fresh food, comprising the following steps: S1. Receive a traceability request for a target fresh food product, the traceability request including a product identification code, the product identification code being associated with the production batch record of the fresh food product from raw material processing to shelf display; S2. Based on the product identification code, retrieve the status parameters of raw material processing, gas environment parameters of processing, and transportation status parameters of logistics and transportation from the management database. S3. Construct a dynamic traceability chain using the product identification code as the source point, and splice the status parameters, the gas environment parameters and the transportation status parameters in chronological order to generate a continuous information backbone on the time axis. S4. Scan the transportation status parameters. When the time interval between adjacent collection points is found to exceed the preset interval, extract the first and second segments of the gas environment parameters that enclose the time interval, generate a compensation data segment, and connect it to the information backbone. S5. Receive the packaging integrity parameters and ambient light parameters uploaded from the shelf display stage, and convert the packaging integrity parameters into gas permeation parameters. S6. Based on the gas environment parameters, gas permeation parameters and light parameters on the information backbone, generate a freshness decay trajectory; S7. Locate the time point on the freshness decay trajectory where the freshness index reaches the preset threshold, mark the time point as the shelf life termination node, and output the quality traceability map.

[0019] In a preferred embodiment of the present invention, the specific process of retrieving the state parameters of the raw material processing in step S2 is as follows: The system collects multispectral response values ​​of raw materials in at least three different wavelength bands. Based on the ratio of response values ​​from two of these bands, the physiological activity level of each individual raw material is determined. A preset activity value corresponding to this physiological activity level is used as a status parameter, which is then stored in a management database after being associated with the raw material batch number. Specifically, a multispectral imaging device is installed above the sorting conveyor belt. This device integrates an area array image sensor and has a switchable filter wheel in front of it. The filter wheel sequentially embeds narrowband filters with a center wavelength of 670 nm, 780 nm, and 980 nm. When a raw material passes over the conveyor belt, a photoelectric switch is triggered. Within one acquisition cycle, the imaging device sequentially switches between the three filters to acquire grayscale reflectance images of the same raw material in the three wavelength bands. The grayscale value stored in the pixel region corresponding to the raw material in each grayscale image is the response value for the corresponding wavelength band. For each individual raw material, the average gray value of the region of interest (ROI) in the 670 nm band image is used as the first response value, the average gray value of the same ROI in the 780 nm band image is used as the second response value, and the average gray value of the same ROI in the 980 nm band image is used as the third response value. The ROI is determined by automatically identifying the outline of the individual raw material using an edge detection operator and then selecting the inscribed rectangle with the largest area within the outline.

[0020] The difference between the second response value and the first response value is calculated, and then the sum of the second and first response values ​​is calculated. The difference is divided by the sum to obtain the first ratio. Simultaneously, the difference between the second and third response values ​​is calculated, and then the sum of the second and third response values ​​is calculated. The difference is divided by the sum to obtain the second ratio. The first ratio reflects the difference in reflectance between the raw material and the visible light red-edge band and red band, and this difference corresponds to chlorophyll content and cell structural integrity. The second ratio reflects the difference in reflectance between the near-infrared band and the short-wave infrared band, and this difference corresponds to the moisture content and cell turgor pressure state within the raw material tissue.

[0021] A variety-activity zone comparison table is pre-stored in the management database. This table is constructed as follows: under laboratory conditions, multispectral data and destructive testing quality index values ​​are simultaneously collected from multiple samples of the same variety at different time points after harvest. The quality index values ​​are a weighted comprehensive score of chlorophyll content, soluble solids content, and ascorbic acid content. The first ratio of each sample is plotted on a two-dimensional plane as the x-axis value and the second ratio as the y-axis value. Simultaneously, the comprehensive score is stratified into high, medium, and low intervals, forming several closed zones on the two-dimensional plane through cluster boundaries. Each zone corresponds to a physiological activity level and is assigned an activity coefficient value, which is an integer between 1.0 and 10.0, where 1.0 represents the lowest physiological activity and 10.0 represents the highest. This mapping relationship constitutes the variety-activity zone comparison table.

[0022] For each raw material to be sorted, the calculated first and second ratios are located in a lookup table to determine its corresponding partition. The activity coefficient value corresponding to that partition is extracted as the preset activity value for the physiological activity level of that raw material. This preset activity value is used as a status parameter, and a one-to-one association record is established between it and the current raw material batch number, and written to the status parameter storage table in the management database. The raw material batch number is composed of the sorting date, variety code, and serial number.

[0023] In another preferred embodiment of the present invention, the specific process of splicing in chronological order in step S3 is as follows: The system extracts the acquisition timestamps for status parameters, gas environment parameters, and transportation status parameters. It retrieves the clock offsets of each acquisition device relative to the standard time from the management database and adds the corresponding device's clock offset to each timestamp to obtain the corrected time point. The status parameter acquisition timestamps are automatically added by the real-time clock module inside the raw material sorting equipment when generating each status parameter record. The clock source for this real-time clock module is a quartz crystal oscillator on the equipment's motherboard. The gas environment parameter acquisition timestamps are automatically added by the environmental acquisition terminal in the processing workshop when generating each gas environment parameter record. The clock source for this acquisition terminal is the clock counter built into the terminal's main control chip. The transportation status parameter acquisition timestamps are automatically added by the satellite positioning and timing module of the logistics transportation vehicle terminal when generating each transportation status parameter record.

[0024] The management database stores clock offset records for each data acquisition device. The clock offset records are obtained as follows: every 24 hours, each data acquisition device sends a clock synchronization request to the management database. Upon receiving the request, the management database returns a standard timestamp, which it obtains from a standard time server. After receiving the returned standard timestamp, each data acquisition device calculates the difference between its current timestamp and the standard timestamp. This difference is used as the clock offset, and it is written to the clock offset record table along with the data acquisition device number and the recorded timestamp. A positive clock offset indicates that the device's clock is ahead of the standard time, and a negative clock offset indicates that the device's clock is behind the standard time.

[0025] Add the acquisition timestamp of each status parameter record to the clock offset most recently reported by the raw material sorting equipment to obtain the corrected time point for the status parameter record. Add the acquisition timestamp of each gas environment parameter record to the clock offset most recently reported by the processing workshop environment acquisition terminal to obtain the corrected time point for the gas environment parameter record. Add the acquisition timestamp of each transportation status parameter record to the clock offset most recently reported by the logistics transportation vehicle terminal to obtain the corrected time point for the transportation status parameter record.

[0026] All records are arranged chronologically according to their calibration time points. Multiple records with the same calibration time point are stacked according to a preset category order. The preset category order is: gas environment parameter records at the bottom layer, state parameter records in the middle layer, and transportation state parameter records at the top layer. The stacking operation does not overwrite any records; instead, it adds a layer number field to each record. Layer number 1 corresponds to the bottom layer, layer number 2 to the middle layer, and layer number 3 to the top layer. Multiple records with the same calibration time point and category are further sorted according to the microsecond precision of the original acquisition timestamp and then assigned incrementally increasing layer sub-numbers. The record sequence formed after the above calibration and stacking operations constitutes the continuous information backbone of the timeline. Each calibration time point in the information backbone corresponds to one or more ordered record sets at different layers, and the time interval between adjacent calibration time points corresponds to the actual time interval between the acquisition of state parameters, gas environment parameters, and transportation state parameters in actual physical time.

[0027] In another preferred embodiment of the present invention, the specific process of generating the compensation data segment in step S4 is as follows: This process extracts the preceding sequence from gas environmental parameters whose timestamps are earlier than the start time of the breakpoint interval and the following sequence whose timestamps are later than the end time of the breakpoint interval. The breakpoint interval refers to the time period between two adjacent records of transport status parameters in the information backbone where the difference in their acquisition timestamps exceeds a preset interval. The start time of the breakpoint interval is the acquisition timestamp of the preceding record, and the end time is the acquisition timestamp of the following record. When extracting the preceding sequence, the starting time of the breakpoint interval is used as the cutoff boundary, and gas environmental parameter records are searched backwards to extract a continuous record with a complete time span and no internal gaps. The length of the preceding sequence is taken from all gas environmental parameter records within the 120 acquisition cycles before the breakpoint. If the number of records within the 120 acquisition cycles before the breakpoint is less than 60, the search range is expanded forward until 60 records are found. When extracting the latter part of the sequence, the gas environment parameter records are retrieved backward from the end time point of the breakpoint interval as the starting boundary. All gas environment parameter records within 120 collection cycles after the breakpoint are extracted, and at least 60 records are required. If the time is insufficient, the search range is expanded.

[0028] The vibration intensity is extracted from a complete record segment whose timestamp is earlier than the start time of the breakpoint interval from the transportation state parameters. The vibration intensity is calculated as follows: Take the most recent continuous vibration acceleration record segment before the start time of the breakpoint interval. This segment must cover at least 300 vibration sampling points. Extract the triaxial vibration acceleration value from each sampling point in this segment. Sum the squares of the triaxial vibration acceleration values ​​at each sampling point and take the square root to obtain the composite acceleration value for that sampling point. Then, take the root mean square (RMS) value of the composite acceleration values ​​from all sampling points. This RMS value is the disturbance intensity. The composite acceleration value reflects the comprehensive mechanical impact level exerted by the transport vehicle on the packaged fresh food during operation, while the RMS value characterizes the average level of vibration energy within the recorded segment.

[0029] Extract the gas concentration values ​​at the end of the preceding sequence, which are the oxygen and carbon dioxide concentration values ​​from the last record of the preceding sequence. Extract the gas concentration values ​​at the beginning of the following sequence, which are the oxygen and carbon dioxide concentration values ​​from the first record of the following sequence. To calculate the rate of change of gas concentration values ​​over time in the preceding sequence, subtract the oxygen concentration value from the oxygen concentration value of the last record of the preceding sequence to obtain the total decrease in oxygen concentration. Divide this total decrease in oxygen concentration by the time span between the first and last records of the preceding sequence to obtain the rate of decrease in oxygen concentration per unit time. Similarly, subtract the carbon dioxide concentration value from the carbon dioxide concentration value of the first record of the preceding sequence to obtain the total increase in carbon dioxide concentration. Divide this total increase in carbon dioxide concentration by the time span between the first and last records of the preceding sequence to obtain the rate of increase in carbon dioxide concentration per unit time.

[0030] The respiratory rate regulation factor and respiratory quotient regulation value are obtained by inputting the state parameters and disturbance intensity into the preset metabolic influence correspondence. The state parameters are the activity coefficient values ​​obtained in step S2, corresponding to the physiological activity level of the raw material associated with the current traceability request. The activity coefficient values ​​are integers between 1.0 and 10.0. The preset metabolic influence correspondence is a multidimensional data retrieval table. The first dimension of the retrieval table is the activity coefficient value, and the second dimension is the disturbance intensity range. Each table entry stores a pair of values, namely the respiratory rate regulation factor and the respiratory quotient regulation value. The retrieval table is constructed as follows: under laboratory conditions, simulated transport breakpoint experiments are conducted on the same type of fresh food under different activity coefficient values ​​and different vibration intensity combinations. During the simulated breakpoint, the changes in oxygen and carbon dioxide concentrations inside the packaging are continuously monitored. The ratio of the measured change rate to the baseline change rate under no-vibration conditions is recorded as the respiratory rate regulation factor, and the ratio of the measured carbon dioxide generation to the oxygen consumption is recorded as the respiratory quotient regulation value. During retrieval, the current activity coefficient value is used as the first-dimensional index value, and the vibration intensity range into which the current disturbance intensity falls is used as the second-dimensional index value. The respiratory rate regulation factor and respiratory quotient regulation value stored in the corresponding table entry are then extracted.

[0031] The corrected rate of decrease in oxygen concentration per unit time is obtained by multiplying the rate of increase in carbon dioxide concentration per unit time by the respiratory rate adjustment factor. The corrected rate of increase is obtained by multiplying the rate of increase in carbon dioxide concentration per unit time by the respiratory rate adjustment factor. The oxygen and carbon dioxide concentration values ​​at the end of the previous sequence are used as the starting point for calculation. The total time span of the breakpoint interval is the difference between the end time and the start time. The total time span is divided into several time steps, each time step being 1 minute. Starting from the first time step, the oxygen concentration value at the current time step is equal to the oxygen concentration value at the previous time step minus the corrected rate of decrease multiplied by the time step. The carbon dioxide concentration value at the current time step is equal to the carbon dioxide concentration value at the previous time step plus the corrected rate of increase multiplied by the time step. Simultaneously, the ratio of the increase in carbon dioxide concentration to the decrease in oxygen concentration at the current time step equals the respiratory quotient adjustment value. When calculating to the last time step, the calculated oxygen and carbon dioxide concentration values ​​are compared with the oxygen and carbon dioxide concentration values ​​at the beginning of the next sequence. If the absolute value of the difference is less than 0.1 percentage points, then all the oxygen and carbon dioxide concentration values ​​generated during the calculation process are used as the compensation data segment. If the difference exceeds 0.1 percentage points, the respiratory quotient adjustment value is increased by 0.01 and the calculation process is repeated until the difference meets the requirements. Each gas concentration record in the compensation data segment is assigned a calculation timestamp of the corresponding time step and connected to the position corresponding to the interruption point interval of the information backbone.

[0032] In another preferred embodiment of the present invention, the specific process of setting the preset interval in S4 is as follows: The system retrieves transportation status parameters of the logistics transportation links associated with the current traceability request within a preset historical period from the management database. The preset historical period is 90 calendar days prior to the time the current traceability request was initiated. It iterates through the retrieved transportation status parameter records, detecting the time span values ​​of all identified data collection interruptions. The method for identifying data collection interruptions is as follows: scan each transportation status parameter record one by one, calculate the difference in collection timestamps between each record and the next record. When this difference exceeds three times the standard vibration collection cycle of the transportation vehicle, the time interval between these two records is marked as a data collection interruption, and the time span value of this interruption is the difference in collection timestamps between the two records. All identified data collection interruption time span values ​​are sorted by numerical value, and the time span value at the middle position after sorting is taken. If the number of identified data collection interruptions is odd, the middle position is the N+1 / 2 value after sorting, where N is the total number. If the number is even, the middle position is the arithmetic mean of the N / 2 and N / 2+1 values ​​after sorting.

[0033] The preset interval is obtained by multiplying the time span value at the middle position by the tolerance coefficient obtained from the search based on the target fresh food category. The management database pre-stores category-tolerance comparison records. These records are constructed as follows: for each category of fresh food, the time elapsed from packaging completion to the freshness index dropping to the shelf-life threshold under standard temperature conditions in a laboratory environment is measured. This time is used as the baseline shelf-life for that category. Categories with a baseline shelf-life of 0 to 72 hours are assigned a tolerance coefficient of 0.3; those with 73 to 168 hours, 0.5; those with 169 to 336 hours, 0.7; and those exceeding 336 hours, 1.0. During the search, the category code of the target fresh food is matched with the category code in the category-tolerance comparison records, and the tolerance coefficient is extracted from the matching records. The time span value at the middle position is multiplied by this tolerance coefficient, and the product is used as the preset interval. When the time span at the midpoint is 45 minutes, the target product category is leafy vegetables, and its shelf life baseline is in the range of 0 to 72 hours, with a corresponding tolerance coefficient of 0.3, then the preset interval is 45 multiplied by 0.3, which is 13.5 minutes. In step S4, when scanning the transportation status parameters, if the time interval between two adjacent collection time points exceeds this 13.5 minutes, then that interval is determined to be a breakpoint interval.

[0034] In another preferred embodiment of the present invention, the specific process of converting the packaging integrity parameter into a gas permeation parameter in step S5 is as follows: Packaging integrity parameters include the leak pore diameter and leak path length measurements obtained from a seal test of retail packaging. The seal test is performed by a vacuum decay method packaging tester located at the retail end, before the shelf display stage begins. During testing, the retail packaging is placed in a sealed test chamber, and a vacuum is created to reduce the pressure inside the chamber to a preset vacuum level. The time it takes for the pressure inside the chamber to recover from the preset vacuum level to a preset recovery value is recorded. The leak pore diameter measurement is derived from this time and the calibrated headspace volume of the packaging. The leak pore diameter measurement represents the equivalent circular diameter of micropores or cracks present on the packaging. The leak path length measurement is the length of the leakage path along the thickness direction of the packaging material, taken as the measured thickness of the packaging film material. After the tester completes the test, the leak pore diameter measurement and the leak path length measurement are packaged into a single packaging integrity parameter record and uploaded to the management database.

[0035] The gas permeability coefficients of the materials used in retail packaging are retrieved from the management database. The management database stores a packaging material attribute table. Each record in the attribute table includes a material code, material name, standard oxygen permeability coefficient, and standard carbon dioxide permeability coefficient. The standard oxygen permeability coefficient is the volume of oxygen that permeates through a unit area per unit thickness of material per unit time under environmental conditions of 23 degrees Celsius and 0% relative humidity, measured in milliliters per micrometer per square meter per day per standard atmosphere. The standard carbon dioxide permeability coefficient is the amount of carbon dioxide that permeates under the same conditions. During retrieval, the corresponding material code is searched based on the packaging batch number associated with the product identification code in the traceability request, and the standard oxygen permeability coefficient and standard carbon dioxide permeability coefficient corresponding to that material code are extracted.

[0036] The equivalent leakage cross-sectional area is calculated based on the measured values ​​of the leak orifice diameter and the leak channel length. The square of the leak orifice diameter is multiplied by pi and then divided by 4 to obtain the cross-sectional area of ​​a single leak orifice. This single-orifice cross-sectional area is then divided by the measured leak channel length to obtain the equivalent leakage cross-sectional area. The equivalent leakage cross-sectional area characterizes the effective flow cross-section of gas molecules per unit length through the leak channel driven by a pressure difference. The oxygen permeability parameter is obtained by multiplying the standard oxygen permeability coefficient by the equivalent leakage cross-sectional area, and the carbon dioxide permeability parameter is obtained by multiplying the standard carbon dioxide permeability coefficient by the equivalent leakage cross-sectional area. The oxygen and carbon dioxide permeability parameters together constitute the gas permeability parameters.

[0037] In another preferred embodiment of the present invention, the specific process of generating the freshness decay trajectory in step S6 is as follows: Extract gaseous environmental parameters from the information backbone after the packaging completion time. The packaging completion time is determined by the process completion flag added to the gaseous environmental parameter record of the processing stage. Obtain the gas concentration value and packaging headspace volume value at each time point. The gas concentration values ​​include oxygen concentration and carbon dioxide concentration values, expressed as volume percentages. The packaging headspace volume is the difference between the total internal cavity volume of the packaging recorded at the time of packaging completion and the actual volume of the fresh food, in milliliters. When calculating the total amount of gas inside the packaging, multiply the oxygen concentration value by the packaging headspace volume value to obtain the oxygen volume inside the packaging, and multiply the carbon dioxide concentration value by the packaging headspace volume value to obtain the carbon dioxide volume inside the packaging.

[0038] Obtain the partial pressure of gases in the external environment of the packaging. The partial pressure of oxygen in the external environment is calculated by multiplying the standard atmospheric pressure by the volume percentage of oxygen in the air (0.209). The partial pressure of carbon dioxide in the external environment is calculated by multiplying the standard atmospheric pressure by the volume percentage of carbon dioxide in the air (0.0004). The oxygen permeation rate per unit time is calculated by multiplying the pressure difference between the oxygen partial pressure in the external environment and the oxygen partial pressure inside the packaging by the oxygen permeation parameter, expressed in milliliters per minute. The carbon dioxide permeation rate per unit time is calculated by multiplying the pressure difference between the carbon dioxide partial pressure inside the packaging and the carbon dioxide partial pressure in the external environment by the carbon dioxide permeation parameter, expressed in milliliters per minute.

[0039] The photoinduced gas consumption per unit time is obtained by multiplying the light intensity value in the illumination parameters by the preset photosensitivity coefficient of the target fresh food. The illumination parameters are the average illuminance value of the retail environment during daily business hours, collected and uploaded by a light sensor every 10 minutes. The preset photosensitivity coefficient is the volume of oxygen consumed by photo-oxidation reaction per unit time under laboratory conditions for this type of fresh food under unit illuminance, expressed in milliliters per minute per lux. The product of the light intensity value and the photosensitivity coefficient is the photoinduced oxygen consumption per unit time.

[0040] The total gas volume and concentration within the packaging are updated at each time step, with a time step of 10 minutes. The oxygen volume within the packaging at the current time step equals the oxygen volume at the previous time step plus the oxygen infiltration rate per unit time multiplied by the time step, minus the photoinduced oxygen consumption per unit time multiplied by the time step. The carbon dioxide volume within the packaging at the current time step equals the carbon dioxide volume at the previous time step minus the carbon dioxide leaching rate per unit time multiplied by the time step. The updated oxygen and carbon dioxide volumes are divided by the headspace volume of the packaging to obtain the oxygen and carbon dioxide concentration values ​​at the current time step. The updated oxygen and carbon dioxide concentration values ​​are input into a preset freshness conversion table to obtain the freshness index value for the corresponding time step. The freshness conversion table is an assignment table; for every 0.5 percentage point decrease in oxygen concentration and every 0.3 percentage point increase in carbon dioxide concentration, the freshness index value decreases by 1 unit. The freshness index values ​​for all time steps are connected sequentially to form a continuous curve, which represents the freshness decay trajectory.

[0041] In another preferred embodiment of the present invention, the specific process of outputting the quality traceability map in step S7 is as follows: Draw a horizontal timeline, starting with the earliest timestamp among the raw material processing times and ending with the shelf-life termination date. Place the status parameter markers for each raw material processing time point on the horizontal timeline in chronological order. These status parameter markers are circular symbols, with the fill color depth corresponding to the value of the status parameter. The status parameter values ​​range from 1.0 to 10.0, with larger values ​​receiving darker fill colors. Add the raw material batch number next to each circular symbol.

[0042] Gas parameter markers are placed at the point in the processing stage when the gas concentration falls below a preset warning line. The preset warning line is an oxygen concentration below 18.0% by volume. The gas parameter markers use triangular symbols, with dashed lines connecting the bottom of the triangle to the gas environment parameter curve for the 60-minute period before and after that point. The gas environment parameter curve is plotted as a line graph showing the time-varying changes in oxygen and carbon dioxide concentrations, with time on the horizontal axis and concentration value on the vertical axis.

[0043] The coverage area of ​​the compensation data segment is represented by time stripes. The starting boundary of the time stripe is aligned with the timestamp of the first record in the compensation data segment, and the ending boundary is aligned with the timestamp of the last record in the compensation data segment. The time stripes are filled with diagonal stripes, with the stripes running from the lower left to the upper right. The fill color is a semi-transparent light gray, and the words "Estimated Data" are marked inside the stripes.

[0044] The end-of-shelf-life marker is a diamond symbol filled in red. An end-of-shelf-life timestamp is attached next to the diamond symbol in the format of year, month, day, hour, and minute.

[0045] Below the horizontal time axis, a command response area is set for each marker. Each command response area is a rectangular hotspot, 2 cm wide and 1 cm high, directly below the corresponding marker. Upon receiving a selection command, the command response area generates an information card above the horizontal time axis. The information card lists the acquisition device number, acquisition time point, and calculation source description for the data associated with the corresponding marker. The acquisition device number is a unique identifier for the data generating device, the acquisition time point is the timestamp of the data record, and the calculation source description displays "calculated based on the correspondence between the rate of change of upstream gas concentration and metabolic effects" for markers corresponding to the compensation data segment.

[0046] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A quality traceability management method for fresh food products, characterized by, Includes the following steps: S1. Receive a traceability request for a target fresh food product, the traceability request including a product identification code, the product identification code being associated with the production batch record of the fresh food product from raw material processing to shelf display; S2. Based on the product identification code, retrieve the status parameters of raw material processing, gas environment parameters of processing, and transportation status parameters of logistics and transportation from the management database. S3. Construct a dynamic traceability chain using the product identification code as the source point, and splice the status parameters, the gas environment parameters and the transportation status parameters in chronological order to generate a continuous information backbone on the time axis. S4. Scan the transportation status parameters. When the time interval between adjacent collection points is found to exceed the preset interval, extract the first and second segments of the gas environment parameters that enclose the time interval, generate a compensation data segment, and connect it to the information backbone. S5. Receive the packaging integrity parameters and ambient light parameters uploaded from the shelf display stage, and convert the packaging integrity parameters into gas permeation parameters. S6. Based on the gas environment parameters, gas permeation parameters and light parameters on the information backbone, generate a freshness decay trajectory; S7. Locate the time point on the freshness decay trajectory where the freshness index reaches the preset threshold, mark the time point as the shelf life termination node, and output the quality traceability map.

2. The quality traceability management method for fresh food products according to claim 1, characterized in that, In step S2, the specific process of retrieving the state parameters of the raw material processing is as follows: In the raw material sorting process, multispectral response values ​​of raw materials in at least three different bands are collected. The physiological activity level of the corresponding raw material is determined based on the ratio of the response values ​​of two of the bands. The preset activity value corresponding to the physiological activity level is used as a status parameter. The status parameter is then associated with the raw material batch number and stored in the management database.

3. The quality traceability management method for fresh food products according to claim 1, characterized by, In S3, the specific process of splicing in chronological order is as follows: Extract the collection timestamps of status parameters, gas environment parameters, and transportation status parameters. Retrieve the clock offset of each collection device relative to the standard time from the management database. Add the clock offset of the corresponding device to each timestamp to obtain the correction time point. Arrange all records in order of correction time points. Stack multiple records with the same correction time point according to the preset category order to form a continuous information backbone of the time axis.

4. The quality traceability management method for fresh food products according to claim 1, characterized by, In step S4, the specific process of generating the compensation data segment is as follows: Extract the first segment of the sequence whose timestamp is earlier than the start time of the breakpoint interval and the second segment of the sequence whose timestamp is later than the end time of the breakpoint interval from the gas environment parameters. Extract the vibration intensity of a complete record whose timestamp is earlier than the start time of the breakpoint interval from the transport state parameters as the disturbance intensity. Extract the gas concentration value at the end of the first segment of the sequence and the gas concentration value at the start of the second segment of the sequence. Calculate the time change rate of the gas concentration value in the first segment of the sequence. By inputting the state parameters and disturbance intensity into the preset metabolic influence correspondence, the respiratory rate regulation factor and respiratory quotient regulation value are obtained. The time change rate is multiplied by the respiratory rate regulation factor to obtain the corrected change rate. Starting from the gas concentration value at the end of the previous sequence, the gas concentration value at each time point in the breakpoint interval is calculated along the corrected change rate under the constraint of the respiratory quotient regulation value until the calculated result is connected with the gas concentration value at the beginning of the next sequence. The calculated result is used as the compensation data segment.

5. The quality traceability management method for fresh food products according to claim 4, characterized in that, In S4, the specific process of setting the interval is as follows: Retrieve the transportation status parameters of the logistics transportation links associated with the current traceability request within a preset historical time period from the management database, extract the time span values ​​of all identified interrupted collection segments, take the time span value at the middle position, and multiply the time span value at the middle position by the tolerance coefficient obtained based on the target fresh food category to obtain the preset interval.

6. The quality traceability management method for fresh food products according to claim 1, characterized by, In step S5, the specific process of converting the packaging integrity parameter into the gas permeation parameter is as follows: The packaging integrity parameters include the leak pore diameter and leak path length measurements obtained from the sealing test of the retail packaging, the gas permeability coefficient of the materials used in the retail packaging retrieved from the management database, the equivalent leak cross-sectional area calculated based on the leak pore diameter and leak path length measurements, and the gas permeability parameter obtained by multiplying the gas permeability coefficient by the equivalent leak cross-sectional area.

7. The quality traceability management method for fresh food products according to claim 1, characterized by, In step S6, the specific process of generating the freshness decay trajectory is as follows: Extract gas environment parameters after the packaging completion time from the information backbone, obtain the gas concentration value and packaging headspace volume value at each time point, calculate the total amount of gas inside the packaging, obtain the partial pressure of the gas outside the packaging, and multiply the difference between the partial pressure of the gas outside the packaging and the partial pressure of the gas inside the packaging by the gas permeation parameter to obtain the gas permeation amount per unit time. The light intensity value in the light parameters is multiplied by the preset photosensitivity coefficient of the target fresh food to obtain the photoinduced gas consumption per unit time. The total amount of gas and gas concentration value in the packaging are updated in each time step. The updated gas concentration value is input into the preset freshness conversion relationship to obtain the freshness index value of the corresponding time step. The freshness index values ​​of all time steps are connected in chronological order to form a curve to obtain the freshness decay trajectory.

8. The quality traceability management method for fresh food products according to claim 1, characterized by, In step S7, the specific process of outputting the quality traceability map is as follows: A horizontal timeline is drawn, on which are placed in chronological order: status parameter markers for raw material processing time points, gas parameter markers for time points when gas concentration in the processing stage falls below the preset warning line, time strip markers for the compensation data segment coverage area, and shelf-life termination node markers. The visual attributes of the status parameter markers correspond to the numerical values ​​of the status parameters. The gas parameter markers are connected to the gas environment parameter curve. The time strip markers cover the corresponding time span with a fill style that is different from other segments and are marked with data calculation indicators. The shelf-life termination node markers are marked with an end timestamp. Below the horizontal timeline, an instruction response area is set for each marker. After receiving a selection instruction, the instruction response area generates an information card, which lists the collection information and calculation explanation of the data associated with the corresponding marker.

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