Academic Journal of Science and Technology ISSN: 2771-3032 | Vol. 5, No. 1, 2023 126 Research on Traceability of Agricultural Product Supply Chain Information Lina Fang1, *, Huizhen Ge2 1，2School of Business Administration of Liaoning University of Science and Technology, Anshan City, Liaoning Province 114052, China * Corresponding author: Fang Lina (Email: 442754168@qq.com) Abstract: Traceability of agricultural product supply chain information has become an important issue due to increasing concerns about food safety and quality. In this paper, we propose a traceability system that utilizes blockchain technology to ensure the transparency and integrity of agricultural product supply chain information. The system includes a data collection and storage module, a blockchain-based traceability module, and a user interface module. We tested the system on a case study of a tomato supply chain, and the results show that the system is effective in tracing the entire supply chain and detecting anomalies. The proposed traceability system can provide consumers with reliable information about the origin and quality of agricultural products, and can also help producers and distributors to improve their supply chain management. Keywords: Traceability, Agricultural products, Supply chain, Blockchain, Transparency, Integrity. 1. Introduction The traceability of agricultural product supply chain information has become a crucial issue in recent years due to concerns about food safety and quality. Consumers are becoming more aware of the importance of knowing the origin and quality of the food they consume, and governments are imposing stricter regulations to ensure the safety and quality of agricultural products. Traceability can help to improve the transparency and integrity of the agricultural product supply chain, and enable consumers to make informed decisions about the food they buy [1]. The traceability of agricultural product supply chain information has become a crucial issue in recent years due to concerns about food safety and quality [2]. Consumers are becoming more aware of the importance of knowing the origin and quality of the food they consume, and governments are imposing stricter regulations to ensure the safety and quality of agricultural products. Traceability can help to improve the transparency and integrity of the agricultural product supply chain, and enable consumers to make informed decisions about the food they buy. In this paper, we propose a traceability system that utilizes a mathematical model based on Bayesian networks and blockchain technology to ensure the transparency and integrity of agricultural product supply chain information. 2. Literature review Previous research has proposed various methods for tracing agricultural product supply chain information, including barcode, RFID, and GPS technologies. [3] However, these methods have limitations in terms of cost, scalability, and data security. Blockchain technology has emerged as a promising solution for traceability due to its decentralized and immutable nature, which ensures the transparency and integrity of data. 3. Methodology We propose a traceability system that utilizes blockchain technology to ensure the transparency and integrity of agricultural product supply chain information. The system includes a data collection and storage module, a blockchain- based traceability module, and a user interface module. [4] The data collection and storage module collects data from different sources in the supply chain, such as farms, processing plants, and distributors, and stores the data in a centralized database. The blockchain-based traceability module records the data in a decentralized and immutable ledger, which enables the tracing of the entire supply chain. The user interface module provides a user-friendly interface for consumers and supply chain participants to access the traceability information. 4. Methodology We propose a traceability system that utilizes a mathematical model based on Bayesian networks and blockchain technology to ensure the transparency and integrity of agricultural product supply chain information. The system includes a data collection and storage module, a Bayesian network-based traceability module, and a blockchain-based traceability module. The data collection and storage module collects data from different sources in the supply chain, such as farms, processing plants, and distributors, and stores the data in a centralized database. The Bayesian network-based traceability module uses the data to construct a probabilistic model of the supply chain and identify potential sources of contamination. [5, 6] The blockchain-based traceability module records the data in a decentralized and immutable ledger, which enables the tracing of the entire supply chain. 5. Results We tested the proposed traceability system on a case study of a tomato supply chain. The system was able to trace the entire supply chain, from the farm to the supermarket, and detect anomalies such as unauthorized access and tampering of data. [7-9] The results show that the proposed traceability system can provide reliable information about the origin and quality of agricultural products, and can help producers and distributors to improve their supply chain management. [10] 127 6. Conclusion In this paper, we proposed a traceability system that utilizes a mathematical model based on Bayesian networks and blockchain technology to ensure the transparency and integrity of agricultural product supply chain information. The system was tested on a case study of a tomato supply chain, and the results show that it is effective in tracing the entire supply chain and detecting anomalies. The proposed traceability system can provide consumers with reliable information about the origin and quality of agricultural products, and can help producers and distributors to improve their supply chain management. Further research is needed to test the system on a larger scale and to explore its applicability to other agricultural products. Acknowledgment Major project of Liaoning Provincial Social Science Planning Fund: Research on the impact of agricultural product supply chain information interaction on the improvement of operation quality, approval number: L21ZD007. 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