Portable agricultural product quality tracing and supervision method and system based on block chain

Abstract

The invention discloses a portable agricultural product quality tracing and supervision method and system based on a block chain, and belongs to the technical field of agricultural product quality supervision. The method comprises the following steps: carrying out accumulation abnormity evaluation on cereal products in a storage state according to obtained storage accumulation parameters, updating the storage state of the cereal products based on an obtained agricultural product accumulation evaluation result, and carrying out storage supervision adjustment on the cereal products according to the storage state; and according to the real-time transportation time and the obtained transportation state parameters, carrying out transportation abnormity evaluation on the cereal products in the transportation state, updating the transportation state of the cereal agricultural products based on an obtained agricultural product transportation evaluation result, and carrying out transportation supervision adjustment on the cereal products according to the transportation state. The effect of cereal product quality supervision in the storage link and the transportation link of cereal crops is remarkably improved, and collaborative optimization of the storage environment and the transportation link is also achieved.

Description

Technical Field

[0001] This invention relates to the field of agricultural product quality supervision technology, and in particular to a portable agricultural product quality traceability and supervision method and system based on blockchain. Background Technology

[0002] The existing methods for agricultural product quality traceability and supervision involve the following processes: Each product is generated with a unique QR code using technologies such as hash algorithms. This QR code's ID (Identifier) ​​is then bound to a "data address" on the blockchain. Data collected during production, processing, transportation, storage, and sales—through sensors, manual input, etc.—is linked to the corresponding product record on the blockchain via this ID. Consumers and regulatory agencies can scan the product's QR code using portable devices such as mobile phones to trace all data stored on the blockchain for that agricultural product, ensuring transparency and authenticity. When storing data using blockchain, the data is first broken down into multiple digital transactions. After node verification, these valid transactions are packaged according to a preset block size, forming a block containing several transaction data points. These blocks are then linked in the order of generation using timestamps and hash values ​​to form an immutable chain structure, ensuring data authenticity and traceability.

[0003] Because cereal products continue to respire during storage and transportation, consuming oxygen and releasing carbon dioxide, moisture, and heat, this physiological process leads to increased temperature and humidity inside the grain pile. If not properly monitored, this can cause localized condensation or abnormal heating, creating favorable conditions for mold growth. Simultaneously, the bottom layer of grain, subjected to prolonged pressure from the upper layers, is prone to mechanical damage, further increasing the risk of mold contamination. Mold contamination not only causes grain spoilage and quality decline but can also produce mycotoxins, threatening food safety. In storage, existing methods for quality control of cereal products primarily rely on real-time monitoring of environmental parameters using temperature and humidity sensor networks, combined with periodic sampling for testing physical indicators such as moisture content and breakage rate, as well as monitoring for mycotoxins. In transportation, GPS and IoT devices track routes and environmental changes, and portable near-infrared spectrometers are used for rapid on-site screening. However, these methods fail to fully consider the dynamic changes and interrelationships between the risk of mold contamination in the storage and transportation environment and the stacking method, resulting in insufficient early warning of mold growth in cereal products.

[0004] For example, the patent application with publication number CN119106962A discloses a blockchain-based agricultural product supply chain quality supervision system, which includes: a system management unit, a contract management unit, a quality management unit, a supervision and management unit, and a quality traceability unit; wherein: the system management unit is used by the construction unit to manage the blockchain system; the contract management unit is used to provide smart contract services, and by adding smart contracts to maintain and improve system functions, the scalability of the blockchain is guaranteed.

[0005] For example, patent application CN116934151A discloses a method for evaluating the quality and safety of agricultural products based on traceability and rapid testing data. This method includes: constructing an agricultural product quality and safety evaluation system based on traceability and rapid testing data; normalizing the values ​​of each evaluation indicator in the agricultural product quality and safety evaluation system and obtaining the first weight corresponding to each evaluation indicator using a chain-multiplication method; calculating the first quality and safety evaluation index of agricultural products based on the normalized evaluation indicator values ​​and their corresponding first weights; constructing a monitoring matrix based on the agricultural product quality and safety evaluation system; constructing a judgment matrix based on the safety thresholds corresponding to each evaluation indicator; and converting the monitoring matrix into a risk matrix using the judgment matrix.

[0006] However, in the process of implementing the inventive technical solution in the embodiments of this application, it was found that the above-mentioned technology has at least the following technical problems:

[0007] In existing technologies, during the process of agricultural products leaving the warehouse, grain products are usually stored in piles. However, if the piles are too thick, heat and moisture cannot dissipate, which can easily lead to mold and mildew contamination, directly reducing the quality of agricultural products. Furthermore, early mold may only be inside the grains, and early mold contamination of agricultural products cannot be detected by rapid visual inspection, resulting in low accuracy of agricultural product quality supervision and affecting the credibility of agricultural product quality traceability. Summary of the Invention

[0008] This invention provides a blockchain-based portable method and system for tracing and monitoring the quality of agricultural products. It addresses the problems in existing technologies where excessively thick stacking of grain products prevents heat and moisture from dissipating, easily leading to mold and mildew contamination, directly reducing product quality. Furthermore, early mold may only be present inside the grain, making it difficult to detect through rapid visual inspection, resulting in low accuracy in quality monitoring and impacting the reliability of traceability. This invention significantly improves the effectiveness of quality monitoring for grain products in both storage and transportation stages.

[0009] This invention provides a portable agricultural product quality traceability and supervision method based on blockchain, comprising the following steps: assessing the stacking anomaly of grain products under storage conditions based on acquired storage stacking parameters, and updating the storage status of grain products based on the obtained agricultural product stacking assessment results; adjusting storage supervision of grain products according to storage status, including adjusting storage data monitoring to improve the consistency between monitoring frequency and storage status, and adjusting storage data to improve the timeliness of quality traceability of grain products under storage conditions via blockchain; assessing the transportation anomaly of grain products under transportation conditions based on acquired transportation status parameters, and updating the transportation status of grain products based on the obtained agricultural product transportation assessment results, where transportation status represents the status corresponding to the process of transporting grain products under storage conditions to the destination; and adjusting transportation supervision of grain products according to transportation status, including adjusting transportation data monitoring to improve the consistency between monitoring frequency and transportation status, and adjusting transportation data storage to improve the timeliness of quality traceability of grain products under transportation conditions via blockchain.

[0010] This invention also provides a portable agricultural product quality traceability and supervision system based on blockchain, including: a stacking anomaly assessment module, a storage supervision and adjustment module, a transportation anomaly assessment module, a transportation supervision and adjustment module, and an agricultural product quality database; wherein, the stacking anomaly assessment module is used to assess the stacking anomalies of grain products under storage conditions based on the acquired storage stacking parameters of each region, and update the storage status of grain products based on the obtained agricultural product stacking assessment results; the storage supervision and adjustment module is used to perform storage supervision and adjustment of grain products according to the storage status, including storage data monitoring and adjustment to improve the consistency between monitoring frequency and storage status, so as to... The system includes: a storage data adjustment module for improving the timeliness of quality traceability of grain products via blockchain during storage; a transportation anomaly assessment module for assessing transportation anomalies of grain products during transportation based on acquired transportation status parameters, and updating the transportation status of grain products based on the assessment results; and a transportation supervision and adjustment module for regulating the transportation of grain products according to their transportation status. This regulation includes adjusting transportation data monitoring to improve the consistency between monitoring frequency and transportation status, and adjusting transportation data storage to improve the timeliness of quality traceability of grain products via blockchain during transportation.

[0011] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0012] 1. In the storage of grain products, the stacking status of grain products under storage conditions is assessed, and the storage status is updated based on the assessment results. The storage status can intuitively show the quality and safety of grain products in the storage environment, thereby improving the level of quality monitoring and risk management of agricultural products. Then, storage supervision and adjustment of grain products based on the storage status can promptly detect and respond to abnormal situations, helping to reduce risks such as loss and mold. In the transportation stage, the transportation status of grain products is assessed, and the transportation status is updated based on the assessment results. The transportation status can intuitively show the suitability of grain products in the transportation environment, thereby improving the safety and efficiency of the transportation process. Transportation supervision and adjustment of grain products based on the transportation status can promptly detect possible abnormalities during transportation, avoid quality degradation caused by environmental problems, provide quality supervision and assurance for grain products in both storage and transportation stages, and ensure the efficiency of agricultural product quality traceability.

[0013] 2. This invention assesses the stacking status of grain products under storage conditions and updates the storage status based on the assessment results. This enables precise monitoring of the quality of grain crops in the storage environment, thereby timely detection of storage anomalies and risks. Dynamic monitoring and adjustment based on storage status helps optimize monitoring frequency and monitoring points according to storage status, ensuring the timeliness and effectiveness of crop quality supervision in the storage process. It effectively reduces the risk of crop spoilage caused by early mold contamination that cannot be detected by rapid visual inspection. This not only improves the storage quality of grain agricultural products but also enhances the accuracy and response speed of supervision, ensuring that agricultural products can be stored and managed under safe and stable conditions.

[0014] 3. This invention assesses the transportation status of cereal products during the transportation process and updates the transportation status based on the assessment results. This enables precise monitoring of the quality of cereal crops in the transportation environment, thereby timely detection of transportation anomalies and risks. Dynamic supervision and adjustment based on the transportation status helps optimize the monitoring frequency and monitoring points according to the transportation status, ensuring the timeliness and effectiveness of crop quality supervision during the transportation process. This not only improves the safety and efficiency of the transportation process but also enhances the accuracy and response speed of supervision, ensuring that agricultural products can be delivered to their destination in a timely and safe manner, reducing losses and maintaining high quality. Attached Figure Description

[0015] Figure 1 A flowchart illustrating a blockchain-based portable agricultural product quality traceability and supervision method provided in this application embodiment.

[0016] Figure 2 A mind map for warehouse supervision and regulation provided in the embodiments of this application.

[0017] Figure 3 A mind map for transportation regulation and control provided in the embodiments of this application.

[0018] Figure 4 A schematic diagram of the structure of a blockchain-based portable agricultural product quality traceability and supervision system provided in this application embodiment. Detailed Implementation

[0019] This application provides a blockchain-based portable agricultural product quality traceability and supervision method and system. It addresses the problem in existing technologies where excessively thick stacking of grain products prevents heat and moisture dissipation, easily leading to mold and mildew contamination, directly reducing product quality. Furthermore, early mold may only be present inside the grain, making it difficult to detect through rapid visual inspection, resulting in low accuracy in agricultural product quality supervision and impacting the reliability of agricultural product quality traceability. The method first assesses the stacking anomalies of grain products under storage conditions based on acquired storage stacking parameters, and updates the storage status of grain products based on the stacking assessment results. Then, based on the storage... The system regulates the storage of grain products by adjusting monitoring frequency to improve consistency between monitoring frequency and storage status, and optimizing data storage to enhance the timeliness of quality traceability using blockchain technology. Based on acquired transportation status parameters, it assesses transportation anomalies in grain products and updates their transportation status accordingly. Then, it regulates transportation based on the transportation status, including adjusting monitoring frequency to ensure consistency with transportation status and optimizing transportation data storage to enhance the timeliness of quality traceability using blockchain. This significantly improves the effectiveness of quality supervision of grain products in both storage and transportation stages.

[0020] The technical solution in this application aims to address the problem that excessively thick stacking of grain-based agricultural products can prevent heat and moisture from dissipating, easily leading to mold and mildew contamination, directly reducing the quality of agricultural products. Furthermore, early mold may only be present inside the grain, making it difficult to detect early mold contamination through rapid visual inspection, resulting in low accuracy in agricultural product quality supervision and affecting the reliability of agricultural product quality traceability. The overall approach is as follows:

[0021] By monitoring the storage and transportation status parameters in real time, dynamically updating the storage and transportation status, and intelligently adjusting regulatory strategies and adopting differentiated data storage mechanisms based on the status, the system effectively improves the timeliness of quality traceability using blockchain while ensuring the accuracy of agricultural product quality supervision. This significantly enhances the effectiveness of quality supervision of grain products in the storage and transportation stages.

[0022] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0023] like Figure 1 The diagram shows a flowchart of a blockchain-based portable agricultural product quality traceability and supervision method provided in this application embodiment. The method includes the following steps: assessing the abnormal stacking of grain products under storage conditions based on acquired storage stacking parameters; updating the storage status of grain products based on the obtained agricultural product stacking assessment results; the storage status includes normal storage, abnormal storage, and dangerous storage; and supervisory personnel gain viewing access through designated portable devices. The method also includes adjusting the storage supervision of grain products according to their storage status, including adjusting storage data monitoring to improve the consistency between monitoring frequency and storage status, and adjusting storage data to improve the quality traceability of grain products under storage conditions via blockchain. The system ensures the timeliness of traceability; it assesses transportation anomalies for grain products based on acquired transportation status parameters, and updates the transportation status of grain products based on the assessment results. The transportation status represents the state of grain products in storage and transport to the destination, including normal, abnormal, and dangerous transportation. Supervisory personnel can view the status through designated portable devices. The system also adjusts transportation supervision based on the transportation status, including adjusting transportation data monitoring to improve the consistency between monitoring frequency and transportation status, and adjusting transportation data storage to improve the timeliness of quality traceability of grain products through blockchain during transportation.

[0024] In addition, the agricultural product quality database is used to store relevant data for blockchain-based portable agricultural product quality traceability and supervision methods, including critical stacking thickness, critical stacking time, critical dew point temperature, abnormal storage stacking threshold, and average abnormal storage stacking deviation threshold. The data in the agricultural product quality database can be directly queried through public databases such as crop species resource database and agricultural product quality evaluation center database, or it can be obtained through cooperation with agricultural universities, agricultural product market associations, agricultural product processing enterprises and other institutions.

[0025] In this embodiment, the present invention effectively improves the accuracy and safety of quality supervision of cereal agricultural products by dynamically evaluating and adjusting the status of storage and transportation. In the storage stage, the storage status in the portable device is first updated according to storage status parameters, and the quality supervision of agricultural products is dynamically adjusted according to different storage statuses to ensure that the impact of the storage environment on the quality of agricultural products is minimized. Simultaneously, by storing storage data in a differentiated manner, the security and economy of blockchain storage are effectively balanced. In the transportation stage, the transportation status in the portable device is updated in real time, and quality supervision is adjusted according to the transportation status to ensure the timeliness and effectiveness of crop quality supervision. Transportation data is also stored differently according to the status to ensure the security and economy of blockchain. The present invention implements targeted adjustment supervision strategies based on the status information of storage and transportation stages. It dynamically increases the monitoring frequency and supervision indicators according to the actual status, ensuring the timeliness and effectiveness of cereal agricultural product supervision. It also intelligently selects data storage strategies based on status information, optimizing the timeliness of blockchain quality traceability. This achieves accurate supervision and efficient traceability of cereal products from storage to transportation, ensuring the quality and safety of agricultural products and the accuracy of quality supervision.

[0026] Furthermore, the steps for assessing the stacking anomalies of grain products under storage conditions based on the acquired storage stacking parameters include: obtaining reference data for storage stacking parameters from a pre-set agricultural product quality database, specifically including: critical stacking thickness, critical stacking time, and critical dew point temperature; performing a ratio approximation calculation on the storage stacking parameters and the reference data, which is a ratio calculation; and then weighting and coupling the ratio approximation calculation results using the influence ratio of the storage stacking parameters to obtain an average storage risk quantification index. The average storage risk quantification index represents the quantified data of the average influence of storage stacking parameters in various regions on the stacking state of grain products under storage conditions; the storage stacking parameters include stacking thickness, stacking time, and dew point temperature, and the influence ratio of the storage stacking parameters includes the influence ratio of stacking thickness, stacking time, and dew point temperature.

[0027] The average warehouse risk quantification index is obtained as follows:

[0028]

[0029] In the formula, PA represents the average storage risk quantification index, ρ1 represents the proportion of influence from stacking thickness, ρ2 represents the proportion of influence from stacking time, and ρ3 represents the proportion of influence from dew point temperature. Where i is the region number, i = 1, 2, 3, ..., N, and N is the total number of regions.

[0030] TH represents the stacking thickness, which indicates the vertical height of grain in the storage space. It can be directly measured using equipment such as depth gauges and laser rangefinders. TH0 represents the critical stacking thickness.

[0031] TI represents stacking time, which can be obtained directly from the warehouse management system. TI0 represents critical stacking time.

[0032] SD represents the dew point temperature, which is the critical temperature at which water vapor begins to condense into liquid water under the current air humidity. It reflects the combined effect of temperature and humidity in the storage space. It can be calculated by averaging the temperature and humidity data monitored by temperature and humidity sensors in various areas of the storage space and then using the Magnus empirical formula. SD0 represents the critical dew point temperature.

[0033] In the agricultural product quality database, ρ1, ρ2, and ρ3 represent the influence ratios of stacking thickness, stacking time, and dew point temperature, respectively. These influence ratios quantitatively characterize the contribution of these storage state parameters to the warehousing risk quantification index. Specifically, stacking thickness, stacking time, and dew point temperature are each configured with independent mapping tables, containing one-to-one or many-to-one correspondences. These tables record each possible storage state parameter value and its corresponding influence ratio. In practical applications, the real-time measured stacking thickness, stacking time, and dew point temperature are input into their respective mapping tables, and their corresponding influence ratios are automatically matched. The influence ratio values ​​range from 0 to 1.

[0034] In this embodiment, the stacking thickness, stacking time, and dew point temperature are interrelated. For example, the thicker the stack of goods, the worse the internal air circulation, making it difficult for heat and moisture to dissipate, leading to an increase in local temperature and humidity, and a higher dew point temperature. The heat generated by grain respiration is more likely to accumulate in the thick stack, which may cause mold growth and increase the risk of storage accumulation. As the stacking time increases, the grain continues to respire, causing the temperature of the grain pile to gradually rise. The water vapor generated by respiration also moderately increases the local temperature, raising the dew point temperature. Long-term stacking creates conditions for mold growth, increasing the risk of storage accumulation.

[0035] like Figure 2The diagram shown is a mind map of warehouse supervision and adjustment provided in this application embodiment. In the diagram, the warehouse index is the average warehouse risk quantification index, the warehouse index threshold is the average warehouse stacking anomaly threshold, the deviation value is the warehouse stacking anomaly deviation value, and the deviation threshold is the warehouse stacking anomaly deviation threshold. Specifically, it includes: obtaining the average warehouse risk quantification index based on warehouse status parameters obtained through real-time monitoring; quantifying the average warehouse risk quantification index against the average warehouse stacking anomaly threshold; if the average warehouse risk quantification index is less than or equal to the average warehouse stacking anomaly threshold, updating the warehouse status to "normal," maintaining the current warehouse monitoring frequency, and storing the warehouse data using the first storage mode of blockchain; if the average warehouse risk quantification index is greater than the average warehouse stacking anomaly threshold, recording the difference between the average warehouse risk quantification index and the average warehouse stacking anomaly threshold as the warehouse stacking anomaly deviation value. The abnormal deviation value of warehouse stacking is compared with the average abnormal deviation threshold of warehouse stacking. If the abnormal deviation value is less than or equal to the average abnormal deviation threshold of warehouse stacking, the warehouse status is updated to warehouse abnormal, the warehouse monitoring frequency is adjusted according to the average warehouse risk quantification index, and the warehouse data is stored using the first storage mode of blockchain. Otherwise, the warehouse status is updated to warehouse dangerous, the warehouse monitoring frequency is adjusted according to the average warehouse risk quantification index, all regulatory indicators of the warehouse monitoring points are activated, and the warehouse data is stored using the second storage mode of blockchain.

[0036] Specifically, the steps for updating the storage status of grain products based on the obtained agricultural product accumulation assessment results include: obtaining the average storage accumulation anomaly threshold, storage accumulation anomaly threshold, average storage accumulation anomaly deviation threshold, and critical storage accumulation anomaly deviation value from a pre-set agricultural product quality database; comparing the average storage risk quantification index with the average storage accumulation anomaly threshold to accurately identify abnormal accumulation and adjust the storage status in a timely manner, ensuring a safe storage environment and preventing quality problems such as mold; if the average storage risk quantification index is less than or equal to the average storage accumulation anomaly threshold, the storage status is updated to normal; if the average storage risk quantification index is greater than the average storage accumulation anomaly threshold, the storage risk quantification index of each area is analyzed based on the storage accumulation parameters of pre-divided areas of equal volume, and areas with storage risk quantification indices greater than the storage accumulation anomaly threshold are marked as dangerous areas, and backup measures are activated in the dangerous areas. Warehouse monitoring points, including backup monitoring points, are additional monitoring locations preset during the warehousing process to enhance monitoring of potentially hazardous areas. When abnormal storage accumulation or other risk indicators are detected in certain areas, these backup monitoring points are automatically activated. Backup monitoring points can quickly supplement the coverage of existing monitoring, providing more comprehensive data, thereby increasing the monitoring density and response speed of the area, further strengthening the monitoring of hazardous areas, enhancing regulatory measures for hazardous areas, ensuring warehouse safety, and preventing early mold growth. The difference between the average warehouse risk quantification index and the average warehouse accumulation anomaly threshold is recorded as the warehouse accumulation anomaly deviation value. The warehouse accumulation anomaly deviation value is compared with the average warehouse accumulation anomaly deviation threshold: if the warehouse accumulation anomaly deviation value is less than or equal to the average warehouse accumulation anomaly deviation threshold, the warehouse status is updated to warehouse anomaly; otherwise, the warehouse status is updated to warehouse danger.

[0037] Furthermore, the steps for adjusting the storage supervision of grain products based on storage status include: if the storage status is normal, maintaining the current storage monitoring frequency; if the storage status is abnormal, matching the average storage risk quantification index with the storage monitoring frequency adjustment values ​​corresponding to the preset ranges of each average storage risk quantification index in the agricultural product quality database to obtain the storage monitoring frequency adjustment value, and summing the storage monitoring frequency adjustment value with the storage monitoring frequency to obtain the adjusted storage monitoring frequency; if the storage status is hazardous, marking the storage space as a priority inspection space and forcibly reminding preset personnel to conduct inspections; while adjusting the storage monitoring frequency according to the storage monitoring frequency adjustment value, activating all monitoring indicators of the storage monitoring points, including temperature, humidity, oxygen concentration, carbon dioxide concentration, and volatile organic compounds; and adjusting storage data based on blockchain storage mode and storage status, where the blockchain storage mode includes a first blockchain storage mode and a second blockchain storage mode.

[0038] In this embodiment, the storage monitoring frequency adjustment value can be directly obtained from the agricultural product quality database. A mapping table is formed in the agricultural product quality database, showing a one-to-one correspondence between each average storage risk quantification index range and its corresponding storage monitoring frequency adjustment value. These relationships can be one-to-one or many-to-one. When obtaining the storage monitoring frequency, simply input the average storage risk quantification index into the mapping table, and the agricultural product quality database can quickly locate and return the storage monitoring frequency adjustment value corresponding to that average storage risk quantification index range. The same applies to the transportation supervision frequency adjustment value. This invention ensures efficient supervision of grain products during storage and reduces quality risks through refined storage status monitoring and dynamic adjustment. Regarding storage supervision, this invention automatically adjusts the monitoring frequency and method according to the storage status, significantly improving the accuracy and response speed of storage management, ensuring timely detection and handling of storage risks, thereby minimizing quality problems such as mold and spoilage. Simultaneously, the storage monitoring adjustment mechanism and blockchain storage mode ensure data security and transparency, improving the scientific nature and effectiveness of storage management.

[0039] Meanwhile, the storage and adjustment of warehouse data based on the blockchain storage mode and warehouse status means that the first storage mode of the blockchain is used to store warehouse data with warehouse status of normal and abnormal, and the second storage mode of the blockchain is used to store warehouse data with warehouse status of dangerous.

[0040] The first aspect to understand is the primary storage model of blockchain. Specifically, this model involves packaging storage data into storage data packages based on a pre-defined time range (e.g., hourly, daily) in the agricultural product quality database. Then, the records within these storage data packages are divided into storage data blocks according to a pre-defined number of records in the agricultural product quality database. The hash value generated from each storage data block is written to the main blockchain, while the actual storage data content is stored on a sidechain. The blockchain uses the hash value generated from the storage data block as a data fingerprint, writing it to the main blockchain. An index is created for each data package and data block, and lightweight encryption algorithms such as Advanced Encryption Standards (AES) are used to encrypt each data package and data block, generating a unique key. This encryption key is distributed to authorized portable devices for quality traceability. This primary storage model stores the hash value of the data block on the main blockchain and the actual data content on the sidechain. Furthermore, redundant backups are performed on multiple nodes in the blockchain network to prevent data loss due to the failure of a single node.

[0041] The second aspect to understand is the blockchain's second storage mode. Specifically, this mode dynamically stores data based on its volume and priority. When the volume of data to be stored is less than or equal to a preset threshold in the agricultural product quality database, the data is directly encrypted and written to the main blockchain. Otherwise, data with a priority exceeding the preset threshold in the agricultural product quality database is directly encrypted and written to the main blockchain. Data with a priority below the preset threshold is stored using the blockchain's first storage mode. Priority determination is typically based on preset rules such as the degree of data anomaly and the scope of its impact; for example, carbon dioxide concentration data has a higher priority than ordinary temperature and humidity data.

[0042] In this embodiment, the first blockchain storage mode effectively improves the security and efficiency of data storage by packaging and segmenting warehouse data according to a preset time range and the number of data records. Warehouse data is packaged into data packets according to the time range, then segmented according to the preset number of records. The generated hash value is written into the main blockchain, while the data content is stored in the sidechain. The main chain ensures the immutability of the data, while the sidechain optimizes storage efficiency, avoids overloading the main chain, and improves the accuracy and speed of data traceability. This not only improves storage efficiency but also ensures data security, transparency, and efficient management, enabling effective monitoring and traceability of agricultural product quality data. The second blockchain storage mode effectively improves the flexibility and efficiency of data storage by dynamically storing data based on the amount and priority of the data to be stored. It allows for flexible storage according to real-time data needs, optimizes the utilization of storage resources, ensures the security, transparency, and efficiency of data storage, and guarantees the reasonable scheduling and efficient management of data with different priorities, thereby improving the management and traceability capabilities of agricultural product quality data. This invention adjusts warehouse data storage based on blockchain storage models and warehouse status, satisfying the different security and traceability requirements of data with varying risk levels while achieving rational allocation and efficient utilization of storage resources. It strikes a balance between data security and storage efficiency, contributing to the construction of a safe and efficient agricultural product quality traceability and regulatory data storage system. Leveraging the immutable and decentralized characteristics of blockchain, this invention preserves the original state of data to the greatest extent possible, providing a solid and reliable data basis for potential accountability and traceability needs, and effectively maintaining the credibility and authority of the data.

[0043] Furthermore, the steps for assessing transportation anomalies of cereal products under transportation conditions based on the acquired transportation status parameters include: obtaining reference data for transportation status parameters from a pre-set agricultural product quality database, specifically including: critical cereal volume percentage, critical transportation time, and critical transportation weight; weighting and coupling the results of relative proportion convergence calculations between the transportation status parameters and their corresponding reference data using the influence ratios of the transportation status parameters to obtain a transportation risk quantification index. The transportation risk quantification index represents the quantified data of the degree of influence of the transportation status parameters on the transportation status of cereal products under transportation conditions; the transportation status parameters include cereal volume percentage, transportation time, and transportation weight, and the influence ratios of the transportation status parameters include the influence ratios of cereal volume percentage, transportation time, and transportation weight.

[0044] The transportation risk quantification index is obtained as follows:

[0045]

[0046] In the formula, TR represents the transportation risk quantification index, ρ4 represents the proportion of influence of grain volume, ρ5 represents the proportion of influence of transportation time, and ρ6 represents the proportion of influence of transportation weight.

[0047] VP represents the volume percentage of grains, which is the ratio of the volume of cereal agricultural products in the transportation space to the total volume of the transportation space. VP0 represents the critical volume percentage of grains. TT represents the transportation time, which is the cumulative time from the transportation origin to the latest monitoring point. It can be obtained directly from the logistics management system. TT0 represents the critical transportation time. TW represents the transportation weight, which can be obtained directly from the logistics management system. TW0 represents the critical transportation weight.

[0048] In the agricultural product quality database, ρ4, ρ5, and ρ6 represent the influence ratios corresponding to the grain volume percentage, transportation time, and transportation weight, respectively. These influence ratios quantitatively characterize the contribution of the aforementioned transportation status parameters to the transportation risk quantification index. Specifically, grain volume percentage, transportation time, and transportation weight are each configured with independent mapping tables, containing one-to-one or many-to-one correspondences. These tables record each possible transportation status parameter value and its corresponding influence ratio. In practical applications, the real-time measured grain volume percentage, transportation time, and transportation weight are input into their respective mapping tables, and their corresponding influence ratios are automatically matched. The influence ratio values ​​range from 0 to 1.

[0049] In this embodiment, the volume ratio of grains, transportation time, and transportation weight are interrelated. For example, the greater the transportation weight, the more agricultural products are usually transported, resulting in a larger volume ratio of grains. This is because the volume and weight of grain agricultural products are often directly proportional. During transportation, due to vehicle vibration and bumps, the grains may rearrange, leading to increased pressure on the lower layer of grains. The longer the transportation time, the higher the density of the lower layer of grains may be, resulting in a smaller volume ratio of grains. At the same time, the extended transportation time may worsen the transportation conditions because the heat and water vapor generated by the respiration of the lower layer of grains cannot be dissipated, increasing the risk of quality problems such as rot and mold.

[0050] like Figure 3 The diagram shown is a mind map of transportation supervision and adjustment provided in this application embodiment. In the diagram, the transportation index is a transportation risk quantification index, and the threshold is a transportation risk threshold. Specifically, it includes: comparing the transportation time with the estimated time; if the transportation time does not exceed the estimated time, the transportation status is updated to "normal transportation," the current transportation supervision frequency is maintained, and the transportation data is stored using the first blockchain storage mode; if the transportation time exceeds the estimated time, the transportation risk quantification index is compared with the transportation risk threshold; if the transportation risk quantification index is less than or equal to the transportation risk threshold, the transportation status is updated to "abnormal transportation," the transportation supervision frequency is dynamically adjusted according to the transportation risk quantification index, and the transportation data is stored using the first blockchain storage mode; otherwise, the transportation status is updated to "dangerous transportation," and while dynamically adjusting the transportation supervision frequency according to the transportation risk quantification index, all supervision indicators of the transportation monitoring points are activated, including temperature, humidity, oxygen concentration, carbon dioxide concentration, and volatile organic compounds, and the transportation data is stored using the second blockchain storage mode.

[0051] Specifically, the steps for updating the transportation status of cereal agricultural products based on the obtained agricultural product transportation assessment results include: obtaining the estimated time and transportation risk threshold from the preset agricultural product quality database; comparing the transportation time with the estimated time, and if the transportation time does not exceed the estimated time, updating the transportation status to normal transportation; if the transportation time exceeds the estimated time, comparing the transportation risk quantification index with the transportation risk threshold, and if the transportation risk quantification index is less than or equal to the transportation risk threshold, updating the transportation status to abnormal transportation, otherwise updating the transportation status to dangerous transportation.

[0052] Furthermore, the steps for adjusting the transportation supervision of grain products based on transportation status include: if the transportation status is normal, maintaining the current transportation supervision frequency; if the transportation status is abnormal, matching the transportation risk quantification index with the transportation supervision frequency adjustment values ​​corresponding to the preset ranges of each transportation risk quantification index in the agricultural product quality database to obtain the transportation supervision frequency adjustment value, and adjusting the transportation supervision frequency according to the transportation supervision frequency adjustment value; if the transportation status is dangerous, adjusting the transportation supervision frequency according to the transportation supervision frequency adjustment value while activating all supervision indicators of the transportation monitoring points; and adjusting transportation data storage based on blockchain storage mode and transportation status.

[0053] The steps for adjusting transportation data storage based on blockchain storage modes and transportation status include: storing transportation data with normal or abnormal transportation status using the first blockchain storage mode; packaging and dividing the data into blocks according to a preset time range; writing the generated hash value into the main blockchain; and storing the data content in the blockchain sidechain, ensuring the immutability, transparency, and efficient storage of the data; and storing transportation data with a second blockchain storage mode for transportation data with a dangerous transportation status; dynamically storing the data according to its storage volume and priority; directly encrypting and writing high-priority data into the main blockchain, while storing low-priority data using the first storage mode, ensuring the timely storage and security of emergency data, and rationally allocating storage resources.

[0054] In this embodiment, the present invention effectively improves the transportation safety and quality control of cereal agricultural products through multi-level transportation status assessment and regulatory adjustment. Firstly, by comparing actual and estimated transportation times, the transportation status can be updated in real time and potential risks identified. If the transportation time exceeds the estimated time, the transportation risk is quantified and compared with a threshold to further determine whether the transportation status is abnormal or dangerous, thus providing data support for subsequent regulatory measures. Based on different transportation statuses, the system dynamically adjusts the frequency of transportation supervision to ensure timely enhancement of supervision in cases of abnormal or dangerous transportation, while optimizing resource allocation to avoid unnecessary frequent supervision and improve efficiency. For transportation statuses of "dangerous," in addition to adjusting the supervision frequency, the system also increases the monitoring indicators at monitoring points, strengthening the monitoring of high-risk links and further reducing the risk of quality problems such as mold. Furthermore, through a blockchain-based storage model, transportation data under different statuses is accurately stored and adjusted, ensuring data transparency, traceability, and security, effectively preventing information tampering or loss, improving quality monitoring and data management during transportation, ensuring data accuracy and real-time performance, enhancing data traceability capabilities, reducing risk management costs, and thus providing strong data support for transportation management. This invention not only improves the efficiency of quality supervision in the transportation of cereal agricultural products, but also provides a more accurate early warning mechanism for preventing risks such as mold, thus ensuring the safety and quality control of agricultural products during transportation.

[0055] like Figure 4The diagram shown illustrates the structure of a blockchain-based portable agricultural product quality traceability and supervision system provided in this embodiment. This system includes: a stacking anomaly assessment module, a storage supervision and adjustment module, a transportation anomaly assessment module, a transportation supervision and adjustment module, and an agricultural product quality database. The stacking anomaly assessment module is used to assess the stacking anomalies of grain products under storage conditions based on acquired storage stacking parameters for each region, and to update the storage status of grain products based on the obtained agricultural product stacking assessment results. The storage supervision and adjustment module is used to perform storage supervision and adjustment on grain products according to their storage status, including monitoring storage data. The system includes: a monitoring and adjustment module to improve the consistency between monitoring frequency and storage status, and a storage data adjustment module to improve the timeliness of quality traceability of grain products via blockchain during storage; a transportation anomaly assessment module to assess transportation anomalies of grain products based on acquired transportation status parameters, and to update the transportation status of grain products based on the assessment results; and a transportation supervision and adjustment module to regulate the transportation of grain products according to their transportation status, including adjusting transportation data monitoring to improve the consistency between monitoring frequency and transportation status, and adjusting transportation data storage to improve the timeliness of quality traceability of grain products via blockchain during transportation.

[0056] In summary, this application embodiment achieves comprehensive monitoring of the quality and safety of agricultural products by conducting status assessments and updating the corresponding storage and transportation status during the storage and transportation processes of cereal agricultural products. Specifically, the storage status assessment can directly reflect the quality status of agricultural products in the storage environment, thereby improving the level of quality monitoring and risk management, promptly identifying anomalies and making corresponding storage adjustments, and effectively reducing risks such as loss and mold. In the transportation process, the transportation status assessment allows for timely adjustment of environmental conditions during transportation, ensuring that agricultural products are in a suitable condition during transport and avoiding quality degradation due to environmental issues.

[0057] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0058] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0059] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0060] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0061] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0062] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A portable method for tracing and supervising the quality of agricultural products based on blockchain, characterized in that: Includes the following steps: Based on the obtained storage and stacking parameters, an assessment of stacking anomalies of grain products under storage conditions is conducted, and the storage status of grain products is updated based on the obtained agricultural product stacking assessment results. Based on the storage status, the storage supervision and adjustment of grain products are carried out. The storage supervision and adjustment includes adjusting the storage data monitoring to improve the consistency between the monitoring frequency and the storage status, and adjusting the storage data of the storage to improve the timeliness of quality traceability of grain products through blockchain under the storage status. Based on the acquired transportation status parameters, an assessment of transportation anomalies is performed on cereal products under transportation status. The transportation status of cereal agricultural products is updated based on the obtained agricultural product transportation assessment results. The transportation status represents the status corresponding to the process of transporting cereal agricultural products in storage to the outbound destination. The transportation supervision and regulation of cereal products are carried out according to the transportation status. The transportation supervision and regulation includes adjusting the transportation data monitoring to improve the consistency between the monitoring frequency and the transportation status, and adjusting the transportation data storage to improve the timeliness of quality traceability of cereal products through blockchain under the transportation status.

2. The portable agricultural product quality traceability and supervision method based on blockchain as described in claim 1, characterized in that: The steps for assessing stacking anomalies of grain products under storage conditions based on the obtained storage stacking parameters include: The reference data for storage and stacking parameters are obtained from the pre-set agricultural product quality database, including: critical stacking thickness, critical stacking time, and critical dew point temperature. The storage stacking parameters are compared with the storage stacking parameter reference data to calculate the degree of similarity in proportion. Then, the influence ratio of the storage stacking parameters is used to weight and couple the results of the degree of similarity calculation to obtain the average storage risk quantification index. The average storage risk quantification index represents the quantification data of the average degree of influence of the storage stacking parameters of each region on the stacking status of grain products under storage conditions. The storage stacking parameters include stacking thickness, stacking time, and dew point temperature. The influence ratios of the storage stacking parameters include the influence ratios of stacking thickness, stacking time, and dew point temperature.

3. The portable agricultural product quality traceability and supervision method based on blockchain as described in claim 2, characterized in that: The step of updating the storage status of cereal products based on the obtained agricultural product stacking assessment results includes: Obtain the average storage and stacking anomaly threshold, storage and stacking anomaly threshold, average storage and stacking anomaly deviation threshold, and critical storage and stacking anomaly deviation value from the preset agricultural product quality database. The average warehouse risk quantification index is compared with the average warehouse stacking anomaly threshold: If the average warehouse risk quantification index is less than or equal to the average warehouse stacking anomaly threshold, the warehouse status will be updated to normal. If the average warehouse risk quantification index is greater than the average warehouse stacking anomaly threshold, then based on the warehouse stacking parameters of each area with equal volume pre-divided, the warehouse risk quantification index of each area is analyzed and obtained. Areas with warehouse risk quantification index greater than the warehouse stacking anomaly threshold are recorded as dangerous areas, and backup warehouse monitoring points in dangerous areas are activated. The difference between the average warehouse risk quantification index and the average warehouse stacking anomaly threshold is recorded as the warehouse stacking anomaly deviation value. The warehouse stacking anomaly deviation value is then compared with the average warehouse stacking anomaly deviation threshold. If the abnormal deviation value of warehouse stacking is less than or equal to the average abnormal deviation threshold of warehouse stacking, the warehouse status will be updated to warehouse abnormal; otherwise, the warehouse status will be updated to warehouse dangerous.

4. The portable agricultural product quality traceability and supervision method based on blockchain as described in claim 3, characterized in that: The steps for regulating and adjusting the storage of grain products based on their storage status include: If the warehouse status is normal, then maintain the current warehouse monitoring frequency; If the storage status is abnormal, the average storage risk quantification index is matched with the storage monitoring frequency adjustment value corresponding to each average storage risk quantification index range preset in the agricultural product quality database to obtain the storage monitoring frequency adjustment value, and the storage monitoring frequency is adjusted according to the storage monitoring frequency adjustment value. If the storage status is hazardous, the storage space will be marked as a priority inspection space. While adjusting the storage monitoring frequency according to the storage monitoring frequency adjustment value, all regulatory indicators of the storage monitoring point will be activated. Warehouse data storage is adjusted based on blockchain storage modes and warehouse status, wherein the blockchain storage modes include a first blockchain storage mode and a second blockchain storage mode.

5. The portable agricultural product quality traceability and supervision method based on blockchain as described in claim 4, characterized in that: The storage data adjustment based on blockchain storage mode and storage status means using the first blockchain storage mode to store storage data with storage status of normal and abnormal, and using the second blockchain storage mode to store storage data with storage status of dangerous. The first storage mode of the blockchain is as follows: the storage data is packaged into storage data packages according to the preset time range in the agricultural product quality database, and the records in the storage data packages are divided into storage data blocks according to the preset number of records in the agricultural product quality database. The hash value calculated by the storage data blocks is written into the main chain of the blockchain, and the storage data content is stored in the side chain of the blockchain. The second storage mode of the blockchain is as follows: dynamic storage is performed based on the amount and priority of the data to be stored. When the amount of data to be stored is less than or equal to the preset data volume threshold in the agricultural product quality database, the data to be stored is directly encrypted and written to the main blockchain. Otherwise, the data to be stored with a priority exceeding the preset priority threshold in the agricultural product quality database is directly encrypted and written to the main blockchain. The data to be stored with a priority not exceeding the preset priority threshold in the agricultural product quality database is stored using the first storage mode of the blockchain.

6. The portable agricultural product quality traceability and supervision method based on blockchain as described in claim 1, characterized in that: The step of assessing transportation anomalies of cereal products under transportation conditions based on the acquired transportation status parameters includes: Reference data on transportation status parameters are obtained from a pre-set agricultural product quality database, including: critical grain volume percentage, critical transportation time, and critical transportation weight. By using the influence ratio of transportation status parameters, the results of relative proportion convergence calculations between transportation status parameters and their corresponding reference data are weighted and coupled to obtain a transportation risk quantification index. The transportation risk quantification index represents the quantified data of the degree of influence of transportation status parameters on the transportation status of grain products under transportation conditions. The transportation status parameters include the grain volume percentage, transportation time, and transportation weight. The influence ratio of the transportation status parameters includes the influence ratio of the grain volume percentage, the influence ratio of the transportation time, and the influence ratio of the transportation weight.

7. The portable agricultural product quality traceability and supervision method based on blockchain as described in claim 6, characterized in that: The step of updating the transportation status of cereal agricultural products based on the obtained agricultural product transportation assessment results includes: Obtain estimated time and transportation risk thresholds from a pre-set agricultural product quality database; The transportation time is compared with the estimated time. If the transportation time does not exceed the estimated time, the transportation status is updated to transportation normal. If the transportation time exceeds the estimated time, the transportation risk quantification index will be compared with the transportation risk threshold. If the transportation risk quantification index is less than or equal to the transportation risk threshold, the transportation status will be updated to transportation abnormal; otherwise, the transportation status will be updated to transportation dangerous.

8. The portable agricultural product quality traceability and supervision method based on blockchain as described in claim 7, characterized in that: The steps for regulating and controlling the transportation of cereal products based on transportation status include: If the transportation status is normal, the current transportation monitoring frequency will be maintained. If the transportation status is abnormal, the transportation risk quantification index is matched with the transportation supervision frequency adjustment value corresponding to each preset transportation risk quantification index range in the agricultural product quality database to obtain the transportation supervision frequency adjustment value, and the transportation supervision frequency is adjusted according to the transportation supervision frequency adjustment value. If the transportation status is dangerous, the transportation supervision frequency will be adjusted according to the transportation supervision frequency adjustment value, and all supervision indicators of the transportation monitoring points will be activated. Transportation data storage and adjustment are based on blockchain storage model and transportation status.

9. The portable agricultural product quality traceability and supervision method based on blockchain as described in claim 8, characterized in that: The steps for adjusting transportation data storage based on blockchain storage mode and transportation status include: The first storage mode of blockchain is used to store transportation data with transportation statuses of normal and abnormal. The second storage mode of blockchain is used to store transportation data in the transportation status of transportation danger.

10. A blockchain-based portable agricultural product quality traceability and supervision system, employing the blockchain-based portable agricultural product quality traceability and supervision method as described in any one of claims 1-9, characterized in that: It includes a stacking anomaly assessment module, a warehousing supervision and adjustment module, a transportation anomaly assessment module, a transportation supervision and adjustment module, and an agricultural product quality database; The stacking anomaly assessment module is used to assess the stacking anomaly of grain products under storage conditions based on the obtained storage stacking parameters of each region, and update the storage status of grain products based on the obtained agricultural product stacking assessment results. The warehouse supervision and adjustment module is used to perform warehouse supervision and adjustment on grain products according to the warehouse status. The warehouse supervision and adjustment includes adjusting the warehouse data monitoring to improve the consistency between the monitoring frequency and the warehouse status, and adjusting the warehouse data storage to improve the timeliness of quality traceability of grain products through blockchain under the warehouse status. The transportation anomaly assessment module is used to assess the transportation anomalies of cereal products under transportation status based on the acquired transportation status parameters, and update the transportation status of cereal agricultural products based on the obtained agricultural product transportation assessment results. The transportation supervision and adjustment module is used to regulate the transportation of grain products according to the transportation status. The transportation supervision and adjustment includes adjusting the transportation data monitoring to improve the consistency between the monitoring frequency and the transportation status, and adjusting the transportation data storage to improve the timeliness of quality traceability of grain products through blockchain during transportation.

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