Food Full-Process and All-Information traceability based on Multi-Chain blockchain and trusted transmission protocols

Abstract

Food quality and safety are crucial for human health and social stability, and full-process and all-information traceability is a key factor in ensuring food quality and safety. The food supply chain is characterized by numerous participants, complex data structures, and difficulties in cross-domain information sharing, leading to challenges in ensuring the trustworthiness of data sources and secure data flow. To address these issues, blockchain technology has been gradually applied to food traceability. However, challenges such as low storage capacity and low consensus efficiency of single-chain blockchain systems remain, and issues related to the unreliability of data collection from various stakeholders have not been effectively resolved.This paper is based on the multi-chain theory of blockchain and integrates active data collection carrier technology based on trusted transmission protocols to study and verify a full-process and all-information traceability model for food throughout the supply chain based on a master–slave multi-chain architecture. Firstly, the study constructs a full-process and all-information traceability model for the food blockchain throughout the supply chain based on master–slave multi-chain architecture by integrating multi-modal storage, cryptography, and TBFT consensus mechanisms, following an analysis of full-process and all-information in the food supply chain. Secondly, using this model as a foundation, the research constructs a trusted collection model architecture based on blockchain and trusted transmission protocols, integrating active data collection carrier technology. An active data collection carrier based on RFID suitable for full-process and all-information traceability of food was developed, and protocol processes and trusted collection were verified. Finally, the traceability system was designed and implemented based on the ChainMaker open-source framework, and simulations were conducted to analyze the trustworthiness of data interactions, traceability accuracy, and traceability query efficiency, comparing the results with other classic solutions. The results demonstrate that the average data upload success rate is 98.86%, the average time for querying public data traceability is 1.489 s, and the average time for querying private data traceability is 1.812 s. The traceability model and system solution studied in this paper meet the requirements for efficient and secure full-process and all-information traceability of food, ensuring the trustworthiness of data sources and providing a feasible reference for food quality safety assurance and traceability, thereby significantly enhancing food safety.