A multi-source data-based organic fertilizer quality safety traceability management method

Abstract

This invention relates to the field of smart agricultural supply chain management technology, specifically to a method for traceability management of organic fertilizer quality and safety based on multi-source data. The method includes: collecting ambient air temperature, relative humidity, and vibration acceleration during transportation; using a thermal inertia compensation model to extrapolate the core temperature inside the product packaging based on ambient temperature and vibration data, comprehensively considering the heat conduction hysteresis effect and the thermal effect generated by mechanical vibration; using a dynamic biological activity decay model including a humidity coupling factor to calculate the instantaneous decay rate of microorganisms based on the core temperature and humidity; calculating the total remaining activity of the product by time integration of the instantaneous decay rate, and generating quality control instructions accordingly. In other words, the solution of this invention eliminates false alarms due to environmental thermal hysteresis, accurately assesses the comprehensive impact of temperature and humidity coupling on microbial activity, and achieves dynamic and precise control.

Description

Technical Field

[0001] This invention relates to the field of smart agricultural supply chain management technology. More specifically, this invention relates to a method for traceability management of organic fertilizer quality and safety based on multi-source data. Background Technology

[0002] For organic fertilizer products, especially liquid fertilizers containing active microorganisms, the core quality lies in the activity of these microorganisms. Maintaining suitable environmental conditions during product logistics, transportation, and storage is crucial for preserving microbial activity. Currently, the industry commonly uses IoT technology combined with temperature recorders for traceability and monitoring. The main approach involves deploying temperature sensors in transport vehicles or warehouses to collect ambient air temperature data. Management systems typically set fixed safety thresholds; once the monitored values ​​exceed these limits, the batch of products is deemed to have potential quality issues. This control model relies heavily on ambient temperature data as the sole basis for quality assessment, assuming that ambient temperature directly represents the product's condition.

[0003] However, in practical applications, liquid organic fertilizers typically have a large heat capacity, and changes in their internal core temperature exhibit a significant thermal lag in response to fluctuations in ambient temperature, resulting in a substantial physical difference between the ambient temperature and the product's actual temperature. When the ambient temperature experiences short-term, drastic fluctuations due to external factors, the internal temperature of the goods often changes relatively gradually. Furthermore, continuous mechanical vibration during transportation causes frictional heat to accumulate within thixotropic liquids, and this endogenous heat accumulation cannot be detected through external environmental monitoring. In addition, for products using non-fully sealed packaging such as breathable caps, high humidity significantly affects the packaging's permeability and microbial metabolic activity, creating complex temperature and humidity coupling stresses.

[0004] Existing monitoring technologies fail to effectively distinguish between transient environmental noise and actual heat accumulation, neglecting temperature response hysteresis caused by thermal inertia and the contribution of vibration to fluid temperature. This leads to frequent false alarms due to short-term spikes in ambient temperature or missed alarms due to the inability to detect internal heat accumulation. Furthermore, the lack of a quantitative assessment model for the synergistic effect of humidity and temperature prevents current solutions from accurately calculating the true degree of microbial activity decline. This monitoring approach, which focuses solely on a single ambient temperature indicator while neglecting multi-source data fusion analysis, results in a severe disconnect between the final quality assessment results and the actual fertilizer efficacy of the product, hindering precise and dynamic control of the biopharmaceutical supply chain. Summary of the Invention

[0005] The purpose of this invention is to propose a traceability management method for the quality and safety of organic fertilizer based on multi-source data, in order to solve the problem that the existing technology cannot accurately assess the true quality of the product due to thermal hysteresis error between environmental monitoring and the actual condition of the goods, as well as the neglect of the comprehensive influence of temperature and humidity coupling and vibration thermal effect on microbial activity; to this end, this invention provides a solution in one aspect.

[0006] This invention provides a method for traceability management of organic fertilizer quality and safety based on multi-source data, comprising: Multi-source environmental data is collected during the transportation of organic fertilizer. This data includes at least the ambient air temperature, relative humidity, and vibration acceleration at the current sampling time. Based on the ambient air temperature and vibration acceleration, a thermal inertia compensation model is used to estimate the core temperature of the organic fertilizer inside the packaging. This estimation of the core temperature takes into account both the heat conduction hysteresis effect and the thermal effect generated by mechanical vibration. Based on the core temperature and relative humidity, a preset dynamic biological activity decay rate model is used to calculate the instantaneous decay rate of microbial activity. This model includes a temperature exponential term and a humidity coupling factor term. The instantaneous decay rate is integrated over the transportation period to calculate the total remaining activity of the organic fertilizer at the current sampling time. Based on the comparison between the total remaining activity and a preset threshold, a corresponding quality control instruction is generated.

[0007] By constructing a physically driven thermal inertia compensation mechanism and a biochemically driven temperature and humidity coupling assessment mechanism, dynamic and precise control of organic fertilizer quality has been achieved. Through the fusion analysis of multi-source data, not only can environmental noise be filtered to restore the true core temperature, but the attenuation of microbial activity under complex working conditions can also be accurately assessed, realizing the transformation from "environmental monitoring" to "quality control" and significantly improving the transparency and safety of the organic fertilizer supply chain.

[0008] Preferably, the step of extrapolating the core temperature of the organic fertilizer packaging using a thermal inertia compensation model based on the ambient air temperature and vibration acceleration includes: calculating the core temperature of the cargo at the current sampling moment using the following expression: In the formula, The core temperature of the cargo at the current sampling time. The core temperature of the cargo calculated at the previous sampling time; The ambient air temperature measured at the current sampling time; The time interval between two samplings; The time constant is the thermal inertia. The mechanical-thermal conversion coefficient; This is the root mean square value of the vibration acceleration at the current sampling time.

[0009] By introducing the thermal inertia time constant and the mechanical-thermal conversion coefficient, this model can filter out high-frequency fluctuations in ambient temperature (such as short-term spikes caused by opening and closing doors) like a low-pass filter, and compensate for the minute internal heat generated by vibration, thereby accurately reconstructing the true temperature curve inside the packaging that cannot be directly measured, solving the problem of false alarms caused by thermal hysteresis.

[0010] Preferably, the method further includes an initialization step for the cargo core temperature extrapolation process: at the initial moment of the start of transportation, the cargo core temperature calculated at the previous sampling moment is set as the initial temperature value detected when the product leaves the warehouse, and this is used as the starting point for recursive calculation. Subsequently, every time the system receives a new data packet, it triggers the calculation of the thermal inertia compensation model once to realize the real-time dynamic update of the cargo core temperature.

[0011] Preferably, the step of calculating the instantaneous decay rate of microbial activity based on the core temperature of the cargo and the relative humidity of the environment using a preset dynamic biological activity decay rate model includes: calculating the instantaneous decay rate of microbial activity at the current sampling moment using the following expression: In the formula, This represents the instantaneous decay rate of microbial activity at the current sampling moment. Based on the natural decay rate; This is the optimal storage temperature constant for the bacterial strain; It is a temperature-sensitive characteristic value; The ambient relative humidity is the actual value measured at the current sampling time. Standard storage humidity constant; The maximum saturation humidity constant; is the damp-heat coupling coefficient.

[0012] By adding a humidity coupling term to the traditional biological decay equation, the system uses the humidity-heat coupling coefficient to assess the catalytic effect of high humidity environment on microbial metabolism in breathable packaging. This enables the system to accurately identify the hidden risks of "high temperature and high humidity" that cannot be detected by traditional monitoring methods, thus improving the sensitivity of risk identification.

[0013] Preferably, the method further includes the step of determining the moisture-heat coupling coefficient: determining the moisture-heat coupling coefficient based on the gas barrier properties of the organic fertilizer packaging material; when the packaging material is a high barrier material, selecting a coefficient value that characterizes no coupling effect; when the packaging material is a breathable material, selecting a coefficient value that characterizes the catalytic acceleration effect of environmental humidity on microbial metabolism, so as to reflect the change of high humidity environment on packaging permeability and its influence on microbial activity.

[0014] Preferably, the step of integrating the instantaneous decay rate over the transportation cycle to calculate the total remaining activity of the organic fertilizer at the current sampling time includes: calculating the predicted total remaining activity of the product at the current sampling time using the following expression: In the formula, This represents the total remaining activity of the product predicted at the current sampling time. This is the initial activity value of the product when it leaves the factory. Indexed by time step; For the first The instantaneous decay rate at each sampling moment.

[0015] By performing integral calculations throughout the entire lifecycle, discrete and abstract sensor data is transformed into an intuitive and measurable total amount of remaining activity. This not only provides scientific data support for hierarchical control in the logistics process but also provides end users with a visualized quality trust certificate, enhancing the market credibility of the product.

[0016] Preferably, the step of generating a corresponding quality control instruction based on the comparison result of the total remaining activity of the product with a preset threshold includes: if the total remaining activity of the product is greater than the safety threshold, a normal warehousing instruction is generated, and the product is determined to be a superior product; if the total remaining activity of the product is less than or equal to the safety threshold but greater than the minimum threshold, a warning instruction is generated, prompting the product to be sold at a reduced price or restricted to use in non-core farmland; if the total remaining activity of the product is less than or equal to the minimum threshold, an interception instruction is generated, the product is determined to be invalid and prohibited from entering the market.

[0017] Preferably, after collecting multi-source environmental data of organic fertilizer during transportation, the method further includes a data cleaning step: processing the collected ambient air temperature sequence and ambient relative humidity sequence using a sliding window mid-range filtering algorithm to identify and remove non-physical jump noise caused by sensor electromagnetic interference. The width of the sliding window is adaptively adjusted according to the sampling frequency to retain the true environmental change trend.

[0018] Preferably, the collection of multi-source environmental data of organic fertilizer during transportation includes: deploying smart sensor tags at the sealing point of the smallest packaging unit of organic fertilizer or at the geometric center of the pallet, and using the smart sensor tags to collect the ambient air temperature, ambient relative humidity and vibration acceleration in real time at preset time intervals to ensure that the collected data can represent the microenvironmental state of the goods.

[0019] Preferably, the thermal inertia time constant is determined by the following steps: placing an organic fertilizer product of a specific specification in a constant temperature difference environment, recording the time required for its center temperature change to reach 63.2% of the total temperature difference, and using this time as the thermal inertia time constant.

[0020] The beneficial effects of this invention are as follows: By constructing a dual evaluation mechanism that couples physical thermal inertia compensation with biochemical attenuation, this invention achieves a fundamental shift from single environmental monitoring to intrinsic product quality control. It not only effectively eliminates misjudgments caused by environmental thermal noise and restores the true heating curve of goods, but also accurately quantifies the comprehensive impact of multi-source environmental stress on microbial activity, providing a dynamic, accurate and scientific quality and safety assurance system for the cold chain logistics of highly active biological agents. Attached Figure Description

[0021] Figure 1 This illustration schematically shows a flowchart of the steps in the organic fertilizer quality and safety traceability management method based on multi-source data in this embodiment; Figure 2 This illustration schematically shows the stress characteristics of the transportation environment and the distribution of quality risks in this embodiment. Figure 3 The diagram illustrates a comparative analysis of the accuracy of the activity prediction models in this embodiment. Detailed Implementation

[0022] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0023] like Figure 1 As shown in this embodiment, an organic fertilizer quality and safety traceability management method based on multi-source data includes the following steps: Step S1: Collect multi-source environmental data of organic fertilizer during transportation. The multi-source environmental data includes at least the ambient air temperature, ambient relative humidity and vibration acceleration at the current sampling time.

[0024] Specifically, to ensure that the collected data accurately represents the microenvironment of the goods, low-power smart sensor tags with temperature, humidity, and vibration monitoring capabilities need to be deployed at specific locations within the smallest packaging unit of organic fertilizer, such as the inner side of the liquid fertilizer container lid or the geometric center of the pallet stack. Strong adhesive or screws are used to ensure a rigid connection between the sensor tags and the goods, guaranteeing the accuracy of vibration data transmission. The system sets the sampling time interval. For example, set it to 300 seconds.

[0025] The sensor tag collects sequence data in real time at a preset frequency, specifically including the following data: : Ambient air temperature at the current sampling time, in degrees Celsius; The ambient relative humidity at the current sampling time is expressed as a percentage. The root mean square value of vibration acceleration at the current sampling time, in units of... .

[0026] After data acquisition, the system automatically performs a data cleaning step to improve data quality. This step uses a sliding window median filtering algorithm to process the acquired ambient air temperature and relative humidity sequences. Specifically, a sliding window of length N is established, and the data points within the window are sorted by value. The value at the middle of the sorted sequence is taken as the filtered output value for the current moment. This processing method can effectively deal with impulse noise interference. For example, when the sensor outputs an abnormally high temperature value at a certain moment due to external electromagnetic interference, such as a sudden jump from 25°C to 80°C and then rapidly dropping back to 25°C in the next moment, the median filtering algorithm can identify and remove this isolated maximum value, thus preserving the true and smooth trend of environmental changes.

[0027] By filtering and adaptively preprocessing the dataset as described above, environmental noise and non-physical interference can be effectively eliminated, ensuring that the basic data input into the model has high accuracy and representativeness, thus laying a reliable foundation for subsequent core temperature extrapolation.

[0028] Step S2: Based on the ambient air temperature and vibration acceleration, the core temperature of the goods inside the organic fertilizer packaging is estimated using a thermal inertia compensation model. The estimation of the core temperature of the goods takes into account the heat conduction hysteresis effect and the thermal effect generated by mechanical vibration.

[0029] The core logic of this step lies in objectively distinguishing the physical difference between the environmental monitoring temperature and the actual product temperature. To obtain the true heat source that causes the decline in microbial activity, a physical model incorporating thermal hysteresis compensation and mechanothermal correction was constructed to simulate the dynamic process of heat conduction from the packaging surface to the geometric center. This model is based on a discretized form of Newton's law of cooling and introduces a mechanothermal effect correction term, designed to compensate for the trace heat accumulation caused by molecular friction within the fluid during the bumpy long-distance transportation of thixotropic liquid organic fertilizer.

[0030] Specifically, the core temperature of the cargo at the current sampling time is calculated as follows: ; in, The core temperature of the cargo at the current sampling time. The core temperature of the goods, calculated at the previous sampling time, is used as the initial temperature value detected by the pin thermometer when the product leaves the warehouse at the beginning of transportation. This initial temperature value is then set as the core temperature. The initial value is used as the starting point for recursive calculations; The ambient air temperature measured at the current sampling time; The time interval between two samples is in seconds.

[0031] The thermal inertia time constant is a parameter used to characterize the degree of hysteresis in the response of a product with a specific packaging size to changes in ambient temperature. A higher value indicates a more gradual change in internal temperature. This constant is derived from a standard laboratory measurement method. Specifically, a product of a specific size, such as a 5-liter container, is placed in an environment with a constant temperature difference. A high-precision temperature probe is used to monitor the temperature change at its geometric center, and the time required for the center temperature change to reach 63.2% of the total temperature difference is recorded. This time is defined as... In actual operation of the model, The value of needs to be much greater than Constraints are imposed to ensure the stability of the discretization calculation.

[0032] The mechanical-thermal conversion coefficient is expressed in units of 1000 ppm. This parameter characterizes the efficiency of converting unit vibration intensity into internal fluid temperature rise. This coefficient is obtained through fitting a vibration table simulation of transport tests; specifically, the fluid temperature rise rate is measured under different vibration intensity inputs in a controlled experiment, and determined through linear regression analysis. The specific value.

[0033] The root mean square value of vibration acceleration at the current sampling moment is used to quantify the degree of vehicle bumps and mechanical energy input at the current moment.

[0034] For example, setting the system sampling time interval The thermal inertia time constant, measured for a specific package size, is 300 seconds. The mechanical-thermal conversion coefficient obtained from the experimental fitting was 3000 seconds. The value is 0.01. Assume the core temperature of the cargo calculated at the previous sampling time is... The temperature was 25.0℃. At the current sampling time, the ambient air temperature was affected by the temporary opening of the transport vehicle's cargo door. The temperature suddenly rose to 35.0℃, and at the same time, the root mean square value of the vibration acceleration generated during vehicle operation... The measured value was 2.0. .

[0035] Based on the aforementioned formula, the core temperature of the cargo at the current sampling time is... The simulation calculations are then performed. First, the incremental heat conduction driven by the ambient temperature difference is calculated. For the first part, the result calculated is 1.0℃; secondly, the incremental part of the endogenous thermal effect generated by mechanical vibration is calculated, i.e. The result of this part is 0.02℃; finally, the core temperature of the previous moment is added to the above two increments to obtain the core temperature of the cargo at the current sampling moment as 26.02℃.

[0036] The calculation results show that although the ambient air temperature experienced a dramatic 10°C jump in a short period, the model-predicted core cargo temperature only increased by approximately 1.02°C due to the thermal inertia of liquids. This result is highly consistent with actual physical laws, demonstrating that through the thermal inertia compensation model and the initial recursive calculation mechanism, the system can effectively filter out high-frequency fluctuation noise in the ambient temperature data, like a low-pass filter, and restore a smooth and realistic cargo heating curve. This avoids system misjudgments caused by short-term dramatic environmental fluctuations due to operations such as opening and closing doors.

[0037] Step S3: Based on the core temperature of the cargo and the relative humidity of the environment, calculate the instantaneous decay rate of microbial activity using a preset dynamic biological activity decay rate model. The dynamic biological activity decay rate model includes a temperature exponential term and a humidity coupling factor term.

[0038] The decline in microbial activity follows biochemical kinetics. This step introduces a humidity coupling factor term into the traditional decline equation. The theoretical basis for this improvement is that for non-absolutely airtight packaging widely used in agriculture, such as plastic drums with breathable screw caps, high humidity in the external environment significantly alters the local oxygen permeability of the packaging material or causes hygroscopic expansion of the micropores on the material surface. This change in physical properties allows external moisture to interact with the internal microenvironment, resulting in a synergistic effect under high-temperature conditions, accelerating the ineffective metabolic consumption of aerobic microorganisms or leading to the death of anaerobic microorganisms.

[0039] Specifically, the system uses a preset dynamic bioactivity decay rate model to calculate the instantaneous decay rate of microbial activity at the current sampling moment. The calculation method is as follows: ; in, It represents the instantaneous decay rate of microbial activity at the current sampling moment, and its physical unit is CFU / (g·h), which is the amount of colonies that decay per gram of sample per hour. The basic natural decay rate is obtained through long-term sample retention tests under standard temperature and humidity conditions. Its physical unit is CFU / (g·h), which reflects the inherent decay characteristics of the strain under ideal conditions. The core temperature of the cargo at the current sampling moment is calculated based on the thermal inertia model in the previous steps. This is the optimal storage temperature constant for the bacterial strain, for example, set to 20℃; The temperature-sensitive characteristic value is expressed in degrees Celsius. This parameter characterizes the sensitivity of the bacterial species to heat stress, i.e., the gradient characteristic of the decay rate as temperature changes. The ambient relative humidity (%) was measured at the current sampling time. This is the standard storage humidity constant, for example, set to 60%; This is the maximum saturation humidity constant. To normalize the humidity difference term, this value is fixed at 100.

[0040] The humidity-heat coupling coefficient is a dimensionless physical quantity. Its determination depends on the gas barrier properties of the organic fertilizer packaging material. When the packaging material is a high-barrier aluminum foil composite bag, external humidity is difficult to penetrate. A value of 0 is used to ignore the effect of humidity; when the packaging material is a plastic bucket with a certain degree of air permeability, a positive value is selected as the value to reflect the change in packaging air permeability and the catalytic acceleration effect on microbial activity caused by a high humidity environment. The coefficient value.

[0041] For example, suppose that the baseline natural decay rate of a specific bacterial species has been determined through long-term experiments. for CFU / (g·h), the optimal storage temperature constant for this strain Set to 20℃, temperature-sensitive characteristic value Set to 10℃.

[0042] At the current sampling moment, the core temperature of the cargo is deduced based on previous steps. The temperature was 26.02℃. At the same time, the sensor collected the ambient relative humidity. A humidity level as high as 90% indicates that the goods are under typical high-temperature and high-humidity conditions. The system sets a standard storage humidity constant. The coefficient is 60%, and the moisture-heat coupling coefficient is selected based on the characteristics of the packaging material. It is 1.0.

[0043] The above parameters are substituted into the dynamic bioactivity decay rate model for calculation. First, the temperature exponent is calculated, i.e. For this part, the result is calculated to be 1.826; next, the humidity coupling factor term is calculated, i.e. In the first part, the value of the humidity coupling factor term was obtained as 1.3; finally, the basic decay rate, temperature index term, and humidity coupling factor term were multiplied together to calculate the instantaneous decay rate of microbial activity at the current moment. It is approximately 2373.8 CFU / (g·h).

[0044] In a comparative analysis, if the traditional monitoring method, which only considers the temperature dimension and ignores the humidity coupling effect, is used, the calculated result is only 1826 CFU / (g·h). The comparison shows that even though the core temperature of the cargo (26.02℃) does not significantly exceed the optimal temperature range, the actual decay rate increases by approximately 30% compared to the traditional method due to the catalytic effect of the high humidity environment on the metabolism of microorganisms within the breathable packaging.

[0045] Thus, by constructing a model that includes humidity coupling factors, the system can accurately quantify and assess the accelerated decay effect of high temperature and high humidity environments on microbial activity, thereby enabling the traceability data to more objectively reflect the real biochemical change process and effectively avoid quality assessment bias and hidden underreporting risks caused by ignoring the humidity dimension.

[0046] Step S4: Integrate the instantaneous decay rate over the transportation cycle to calculate the total remaining activity of the organic fertilizer at the current sampling time, and generate a corresponding quality control instruction based on the comparison result of the total remaining activity of the product with a preset threshold.

[0047] Specifically, based on the instantaneous decay rate obtained in step S3, this step performs time-domain integral accumulation calculations on the entire transportation process to calculate the total amount of remaining activity upon arrival at the destination, thus realizing a leap from simple temperature physical monitoring to bioactivity quality control.

[0048] Specifically, the system calculates the predicted total remaining activity of the product at the current sampling time using the following formula: ; In the formula, This represents the total remaining activity of the product predicted at the current sampling time. This is the initial activity value of the product when it leaves the factory. This is a time step index, representing the sequence from the start of transportation to the current sampling time; For the first The instantaneous decay rate at each sampling moment. The value 3600 is a time unit conversion factor used to convert sampling intervals in seconds. Convert to hours to ensure consistency with instantaneous decay rate The dimensions are kept consistent, thus ensuring the correctness of the physical meaning of the integral operation.

[0049] The cloud-based management system employs a recursive calculation mechanism. Each time a sensor data packet containing new environmental data is received, the above formula is calculated once. The system then determines the remaining product activity based on the calculated total amount at the current moment. It compares the data with preset thresholds in real time and executes hierarchical control strategies accordingly.

[0050] When the calculated total residual activity of the product is significantly greater than the preset safety threshold, the system determines that the batch of products is of superior quality, indicating that it has not suffered substantial quality damage during transportation, and generates a normal warehousing instruction, allowing the product to enter the standard sales channels.

[0051] When the calculated total remaining activity of the product is less than or equal to the preset safety threshold, but still greater than the preset minimum threshold, the system determines that the batch of products is in a critical quality state, generates an early warning instruction, and prompts the manager to take downgrade measures, such as suggesting that the product be sold at a lower price nearby or restricting the use of the batch of fertilizer to non-core farmland, so as to ensure safe use while reducing economic losses.

[0052] When the calculated total remaining activity of the product is less than or equal to the minimum threshold, the system determines that the batch of products has expired and no longer has the expected agronomic value. It directly generates an interception command to prevent the batch of products from entering the market and triggers the scrapping or recall process.

[0053] For example, suppose a batch of liquid organic fertilizer products has an initial activity value determined by testing at the time of manufacture. It is 1,000,000 CFU / g, where CFU / g is the colony-forming unit per gram.

[0054] After a long-distance transport, the cloud system integrates and accumulates the instantaneous decay rate throughout the entire transport cycle. Although, as shown in the previous steps, the instantaneous decay rate can reach 2373.8 CFU / (g·h) under extreme conditions of high temperature and humidity, the decay rate decreases accordingly at night or during periods of stable road conditions. By precisely accumulating the decay amount at each sampling moment, the system calculates the total cumulative activity decay of the batch of products at the current moment, i.e., the summation term in the formula is 50000 CFU / g.

[0055] Based on the formula for calculating the total remaining activity, the system subtracts the cumulative decay of 50,000 from the initial activity value of 1,000,000 to obtain the total remaining activity of the product at the current sampling time. It is 950,000 CFU / g.

[0056] The system then proceeds to the decision-making stage, assuming a preset quality control safety threshold of 900,000 CFU / g. The system compares the calculated value of 950,000 with the safety threshold of 900,000, and the result shows that the remaining total activity is greater than the safety threshold. Based on this, the system determines that the batch of products is of superior quality, automatically generates a mark indicating that it meets quality standards, and sends a normal warehousing instruction to the warehouse management terminal.

[0057] Through the above-mentioned integral calculation and hierarchical control process, this invention successfully transforms discrete and abstract sensor data streams into intuitive activity indicators and executable control instructions. This not only significantly improves the scientific nature and accuracy of supply chain management, but also provides end users with visualized quality trust credentials, effectively solving the industry problem in traditional logistics where temperature data alone cannot confirm the biological quality of goods.

[0058] The following is in conjunction with the appendix Figure 2 and attached Figure 3 The beneficial effects of the present invention will be further explained.

[0059] Figure 2 The diagram illustrates the distribution of environmental stress characteristics and quality risks during transportation. The horizontal axis represents the thermal hysteresis characteristic index, and the vertical axis represents cumulative vibration energy. A quality and safety control domain is defined by a dashed circle. The dots within the dashed circle represent normal batches, indicating that although they experienced environmental fluctuations, calculations by the model confirm that no substantial damage occurred. The diamond-shaped dots in the upper right corner outside the dashed circle represent high-risk batches, corresponding to abnormal situations involving continuous and severe shaking and excessive heat accumulation. The diagram demonstrates that the algorithm logic in step S2 possesses strong classification capabilities, effectively distinguishing between products with hidden internal damage and normal products.

[0060] Figure 3 The figure demonstrates a comparison of the accuracy of bioactivity prediction models. The horizontal axis represents the laboratory-measured true bioactivity values, and the vertical axis represents the system's predicted values. The crosses scattered above the diagonal in the figure represent existing technologies, particularly in areas with low true values, where existing technologies still predict high values, indicating a false negative defect. In contrast, the dots of the present invention are closely aligned around the diagonal, showing minimal prediction error in both high and low bioactivity regions. The figure shows that by employing the coupling attenuation and integration model in steps S3 and S4, the actual changes in bioactivity can be accurately reproduced, effectively addressing the pain point of underreporting caused by the disconnect between environmental monitoring and physical quality in the industry.

[0061] In the description of this specification, "multiple" means at least two, such as two, three or more, etc., unless otherwise expressly and specifically defined.

[0062] While various embodiments of the invention have been shown and described in this specification, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Many modifications, alterations, and alternatives will occur to those skilled in the art without departing from the spirit and essence of the invention.

Claims

1. A method for traceability management of organic fertilizer quality and safety based on multi-source data, characterized in that, include: Collect multi-source environmental data of organic fertilizer during transportation, including at least the ambient air temperature, relative humidity and vibration acceleration at the current sampling time. Based on the ambient air temperature and vibration acceleration, the core temperature of the goods inside the organic fertilizer packaging is estimated using a thermal inertia compensation model. The estimation of the core temperature of the goods takes into account both the heat conduction hysteresis effect and the thermal effect generated by mechanical vibration. Based on the core temperature of the cargo and the relative humidity of the environment, the instantaneous decay rate of microbial activity is calculated using a preset dynamic biological activity decay rate model, which includes a temperature exponential term and a humidity coupling factor term. The instantaneous decay rate is integrated over time during the transportation cycle to calculate the total remaining activity of the organic fertilizer at the current sampling time. Based on the comparison between the total remaining activity of the product and a preset threshold, a corresponding quality control instruction is generated.

2. The organic fertilizer quality and safety traceability management method based on multi-source data according to claim 1, characterized in that, The process of extrapolating the core temperature of the organic fertilizer packaging using a thermal inertia compensation model based on the ambient air temperature and vibration acceleration includes: The core temperature of the cargo at the current sampling moment is calculated using the following expression: ； In the formula, The core temperature of the cargo at the current sampling time. The core temperature of the cargo calculated at the previous sampling time; The ambient air temperature measured at the current sampling time; The time interval between two samplings; The time constant is the thermal inertia. The mechanical-thermal conversion coefficient; This is the root mean square value of the vibration acceleration at the current sampling time.

3. The organic fertilizer quality and safety traceability management method based on multi-source data according to claim 2, characterized in that, The method also includes an initialization step for extrapolating the core temperature of the cargo: At the initial moment of transportation, the core temperature of the goods calculated at the previous sampling moment is set as the initial temperature value detected when the product leaves the warehouse, and this is used as the starting point for recursive calculation. Subsequently, every time the system receives a new data packet, it triggers the calculation of the thermal inertia compensation model to realize the real-time dynamic update of the core temperature of the goods.

4. The organic fertilizer quality and safety traceability management method based on multi-source data according to claim 2, characterized in that, The step of calculating the instantaneous decay rate of microbial activity based on the core temperature of the cargo and the relative humidity of the environment using a preset dynamic biological activity decay rate model includes: The instantaneous decay rate of microbial activity at the current sampling moment is calculated using the following expression: ； In the formula, This represents the instantaneous decay rate of microbial activity at the current sampling moment. Based on the natural decay rate; This is the optimal storage temperature constant for the bacterial strain; It is a temperature-sensitive characteristic value; The ambient relative humidity is the actual value measured at the current sampling time. Standard storage humidity constant; The maximum saturation humidity constant; is the damp-heat coupling coefficient.

5. The organic fertilizer quality and safety traceability management method based on multi-source data according to claim 4, characterized in that, The method also includes the step of determining the hygrothermal coupling coefficient: The moisture-heat coupling coefficient is determined based on the gas barrier properties of the organic fertilizer packaging material. When the packaging material is a high-barrier material, a coefficient value representing no coupling effect is selected. When the packaging material is a breathable material, a coefficient value representing the catalytic acceleration effect of environmental humidity on microbial metabolism is selected to reflect the changes in packaging permeability and the impact on microbial activity caused by a high-humidity environment.

6. The organic fertilizer quality and safety traceability management method based on multi-source data according to claim 2, characterized in that, The step of integrating the instantaneous decay rate over the transportation cycle to calculate the total remaining activity of the organic fertilizer at the current sampling time includes: The total remaining product activity predicted at the current sampling time is calculated using the following expression: ； In the formula, This represents the total remaining activity of the product predicted at the current sampling time. This is the initial activity value of the product when it leaves the factory. Indexed by time step; For the first The instantaneous decay rate at each sampling moment.

7. The organic fertilizer quality and safety traceability management method based on multi-source data according to claim 6, characterized in that, The step of generating corresponding quality control instructions based on the comparison result of the total remaining active ingredients of the product with a preset threshold includes: If the total remaining activity of the product is greater than the safety threshold, a normal warehousing instruction is generated, and the product is determined to be a superior product. If the total remaining activity of the product is less than or equal to the safety threshold and greater than the minimum threshold, an early warning instruction is generated, prompting the product to be sold at a reduced price or restricted to use in non-core farmland. If the total remaining activity of the product is less than or equal to the minimum threshold, an interception command is generated to determine that the product is invalid and prohibit it from entering the market.

8. The organic fertilizer quality and safety traceability management method based on multi-source data according to claim 1, characterized in that, After collecting multi-source environmental data during the transportation of organic fertilizer, the method further includes a data cleaning step: The collected ambient air temperature and relative humidity sequences are processed using a sliding window mid-range filtering algorithm to identify and remove non-physical jump noise caused by sensor electromagnetic interference. The width of the sliding window is adaptively adjusted according to the sampling frequency to preserve the true trend of environmental changes.

9. The method for traceability management of organic fertilizer quality and safety based on multi-source data according to claim 1, characterized in that, The collection of multi-source environmental data during the transportation of organic fertilizer includes: Smart sensor tags are deployed at the seal of the smallest packaging unit of organic fertilizer or at the geometric center of the pallet. The smart sensor tags are used to collect ambient air temperature, relative humidity and vibration acceleration in real time at preset time intervals to ensure that the collected data can represent the microenvironmental state of the goods.

10. The method for traceability management of organic fertilizer quality and safety based on multi-source data according to claim 2, characterized in that, The thermal inertia time constant is determined through the following steps: A specific specification of organic fertilizer product is placed in a constant temperature difference environment, and the time required for its center temperature change to reach 63.2% of the total temperature difference is recorded. This time is used as the thermal inertia time constant.

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