A Food Traceability System Based on Blockchain and Radio Frequency Identification Technologies

The frequent occurrence of food safety accidents at the global level has triggered consumer sensitivity. Establishing a food traceability system can effectively guarantee food safety and increase consumer confidence and satisfaction. Existing food traceability systems often ignore environmental factors that affect food quality at all stages of the supply chain, and the authenticity of the information obtained through traceability is difficult to guarantee. In this study, a food supply chain traceability model was established based on blockchain and radio frequency identification (RFID) technologies. The model focused on the traceability of environmental data during the various stages of the food supply chain and combined a centralized database and blockchain for data storage. The lot identification data of the various supply chain stages were stored in a centralized database, while the environmental data were stored in a blockchain. Thereby, the authenticity and accuracy of the traceability data were ensured. The blockchain part of the model has been simulated in the Ethereum test environment, and the experiment has achieved traceability of temperature data.

A Food Traceability Framework Based on Permissioned Blockchain

In recent years,food safety problems have become increasingly serious.The traditional supply chain traceability solution faces some serious problems,such as centralization,data tampering,and high communication costs.To solve these problems,this paper proposes a food traceability framework based on permissioned blockchain.The proposed framework is decentralized,and the supply chain data of the framework cannot be tampered with.The framework divides supply chain entities into five organizations,and each organization deploys its own chaincode onto the blockchain.The chaincode specifies the query permission of each organization,which can effectively protect the user’s sensitive information.The PBFT consensus algorithm adopted by the framework improves the performance of processing transactions.The transactional throughput experiment shows that the proposed framework can achieve a high number of transactions per second.Query efficiency experiment demonstrates that the framework has lower query latency and good user experience.

BC driven IoT-based food quality traceability system for dairy product using deep learning model

Food traceability is a critical factor that can ensure food safety for enhancing the credibility of the product,thus achieving heightened user satisfaction and loyalty.The Perishable Food SC(PFSC)requires paramount care for ensuring quality owing to the limited product life.The PFSC comprises of multiple organizations with varied interests and is more likely to be hesitant in sharing the traceability details among one another owing to a lack of trust,which can be overcome by using Blockchain(BC).In this research,an efficient scheme using BC-Deep Residual Network(BC-DRN)is developed to provide food traceability for dairy products.Here,food traceability is determined by using various modules,like the Internet of Things(IoT),BC data management,Food traceability BC architecture,and DRN-based food quality evaluation modules.The devised BC-DRN-based food quality traceability system is examined based on its performance metrics,like sensitivity,response time,and testing accuracy,and it has attained better values of 0.939,109.564 s,and 0.931.

Agricultural cooperatives and the role of organisational models in new intelligent traceability systems and big data analysis

Traceability systems are key to assuring food safety,creating a benefit for food supply chain components.Currently,the appearance of new technologies such as IoT and Big Data Analysis leads to a new generation of more functional,but complex,traceability systems.Organisational models based on cooperation of multiple small/medium size agents,for example of small/family farming cooperatives,play an important role in high standard agricultural production and commercialization processes.These function as both social and economic networks,with high social and economic impact in the rural areas.The case of Almeria as an example of this model was used to analyze its cooperative model.The actual traceability systems in the Almeria model were studied,taking account of the different networked agents and their interrelation.This study includes two main parts:a)analysis of the net-chains that constitute the food supply chains and their different relationships,and b)actual traceability.The next step studied how the net-chain model,including many diverse agents,may be applied to develop a new generation of traceability systems based of IoT and Big Data.This implies extending the special and functional scope of the actual systems and defining clear rules of exchange of the results of the Big Data Analysis,taking account of the adequate Privacy Rules.This work analyses the current organisation as a base for a new generation of traceability systems considered in the European project IoF2020(Internet of the Food and Farm 2020).Some parallels between Almeria’s model and certain areas in China,mainly in the areas of Beijing-Tianjin-Hebei and Shandong were detected.Another of the objectives of this work is to deepen the understanding of these similarities and analyze the possible adaptation of the results from Almeria to China.

Blockchain or Not?Optimal Decisions for Food Retailers Considering Consumer Expertise

This paper studies the benefit of the blockchain food traceability system(BFTS).Based on game theory and the willingness-to-pay model,pricing models are formulated considering important factors like the proportion of consumer with high expertise in traceability,risk attitude to doubtful traceability information and perceived convenience of traceability information checking.By compared the optimal total welfare under the BFTS and that under the traditional food traceability system in valuation analysis,conditions where applying the BFTS is more valuable than applying the TFTS are figured out.Finally,insightful management implications are given.