Li Jiali, Chen Yu, Qian Jianping, Zhang baoyan, Yang han, Chen qian. Improvement of the precise up-chain mechanism of the agricultural products blockchain traceability system integrating the HACCP system[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2022, 38(20): 276-285. DOI: 10.11975/j.issn.1002-6819.2022.20.031
    Citation: Li Jiali, Chen Yu, Qian Jianping, Zhang baoyan, Yang han, Chen qian. Improvement of the precise up-chain mechanism of the agricultural products blockchain traceability system integrating the HACCP system[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2022, 38(20): 276-285. DOI: 10.11975/j.issn.1002-6819.2022.20.031

    Improvement of the precise up-chain mechanism of the agricultural products blockchain traceability system integrating the HACCP system

    • Abstract: Food safety has been an essential requirement for human survival in recent years. Fortunately, the traceability system can be expected to serve as an important way for the safety of agricultural products. The whole chain information of agricultural products can be traced from the place of origin to the table. The high quality and safety of agricultural products can be obtained to reduce the cost of a food recall, indicating a high increase in consumer confidence. Among them, blockchain technology can be used for trusted traceability without tampering after uploading the chain. It is still lacking in how to determine the information that is uploaded to the chain, and then verify the information before the chain in the current blockchain application. Taking the fruit as an example, the hazard analysis and critical control point (HACCP) system was integrated with blockchain technology to improve the up-chain mechanism in the current blockchain traceability system of agricultural products. Firstly, the up-chain information was mined to extract the five critical control points (CCP1 production, CCP2 processing, CCP3 storage, CCP4 logistics, and CCP5 sales) using the hazard analysis of the fruit supply chain. The limit value was then determined for the information on the chain, according to the key information, determine whether the information on the chain is within the limit value. If it is within the threshold range, the information will be uploaded to the chain.A data anomaly and quality warning model was established to monitor the information after the up-chain at the critical control point in real time, and then to provide intelligent feedback after the chain. Secondly, an improved up-chain mechanism was constructed with the key information mining before the up-chain, the information fact determination in the up-chain, and the information intelligent feedback after the up-chain. After that, three contracts of threshold determination, data upload, and data intelligent feedback were written to realize the improved up-chain mechanism. Thirdly, a traceability system was developed to deploy the architecture and environment using the Hyperledger Fabric platform. Some functions were then implemented, such as the traceability query, security warning, and decision analysis. Finally, the performance of the improved system was verified in a fruit enterprise in Beijing, China. A better performance was achieved in the improved traceability system. Specifically, an average throughput of 350 Transactions per second, and 40 key transaction data were completed concurrently on the chain within seconds, which was 14.85% higher than the original system, fully meeting the needs of the traceability system. In addition, there were a total of 13 early warning notices of risks during the three-month on-site monitoring. The emergency measures were then taken to effectively ensure the quality and safety of products with the cost saving, according to the level of early warning. The findings can provide a strong reference to optimize the blockchain traceability system for the high credibility of key links.
    • loading

    Catalog

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return