Research on Grain Food Blockchain Traceability Information Management Model Based on Master-Slave Multichain

Area of Science:

• Agricultural Supply Chain Management
• Blockchain Technology
• Information Systems

Background:

• The grain food supply chain faces challenges in traceability due to complex links, numerous participants, and large data volumes.
• Existing blockchain single-chain structures struggle with throughput, data sharing, and traceability efficiency.

Purpose of the Study:

• To propose an improved grain food traceability information management model using a master-slave multichain structure.
• To address the limitations of current blockchain systems in managing complex supply chain data.

Main Methods:

• Developed a master-slave multichain model analyzing grain supply chain processes and data characteristics.
• Designed the PLEW consensus algorithm (Raft + improved PoW) for the master chain and CI-PBFT for the slave chain.
• Implemented the system using Hyperledger Fabric 2.2, anchoring chains via hash locking and using smart contracts for data management.

Main Results:

• The implemented blockchain traceability system demonstrated superior performance compared to single-chain structures in transaction throughput and traceability efficiency.
• Safety analysis confirmed the system's effectiveness for a real-world company's data.
• The model successfully addresses consumer concerns regarding grain food security.

Conclusions:

• The master-slave multichain model offers significant advantages for grain food supply chain traceability.
• This research provides a viable solution for enhancing food safety and traceability through blockchain technology.
• The findings offer valuable insights for future research in grain blockchain traceability information management.