新一代信息技术对农产品追溯系统智能化影响的综述

从为应对疯牛病问题至今,追溯系统作为农产品及食品质量安全保障的有效手段引入已有近30a,如何降低追溯断链化、增强追溯可信度、提升质量预警力,已成为追溯系统研究的热点,也是应用中亟待解决的问题。该文基于国内外相关文献,瞄准热点问题,综述了新一代信息技术对农产品追溯系统智能化的影响。首先,提出了追溯系统从1.0到3.0的发展历程,总结了追溯系统1.0以信息记录为主、2.0以数据整合为主、3.0以智能决策为主的核心特征;其次,描述了以物联网、大数据、云计算、人工智能、区块链等为核心的新一代信息技术之间在信息感知、数据处理、高效计算、智能分析、加密防伪等方面各有侧重又相互关联的内在关系,分析了大数据、人工智能及区块链的发展趋势;最后,从人工智能技术降低追溯过程断链程度、大数据技术提升质量安全预警能力、区块链技术增强全程追溯可信度等3个方面,综述了相关研究,结合发展趋势提出了深入研究的方向,即人工智能从供应链内部及供应链之间提升追溯粒度,大数据从微观、中观及宏观层面实现预测与优化,区块链从追溯区块结构优化、隐私保护及共识算法等方面增强追溯可信度。该文为把握农产品追溯系统发展趋势、研究热点、应用瓶颈提供有益参考。

Review on agricultural products smart traceability system affected by new generation information technology

From the problem of mad cow disease to date, the traceability system as effective means to ensure food safety has been introduced for nearly 30 years. Now, reducing breakage degree for traceability chain, enhancing traceability credibility, and improving early warning capacity for agri-food quality and safety, these has increasingly become hot topics of traceability system research, which is also urgent problems in traceability system application. Focusing on these issues, the agricultural products smart traceability system affected by new generation information technologies based on the relevant literature was summarized and analyzed. Firstly, the development stages of traceability system from 1.0 to 3.0 were presented. The features of the three stages were information recording for 1.0, data integration for 2.0, and intelligent decision-making for 3.0 , respectively. Secondly, the relationship of new generation information technology including internet of things (IoT), big data, cloud computing, blockchain, artificial intelligence (AI) was described. The new generation of information technology is not only the vertical promotion of single technology, but also the horizontal penetration of technology integration. The development trend about big data, artificial intelligence and block chain were summarized. Finally, the relevant research on the issues of reducing the breakage degree for traceability with AI, improving early warning capability for agri-food quality and safety with big data, and enhancing the traceability credibility of the whole supply chain with blockchain were summarized. The orientation of in-depth study was put forward in the light of the technology development trend. For combing AI, traceability granularity should be improved from within and among supply chains through establishment some flexible and intelligent traceability models. For coming big data, prediction quality and optimization processing model should be enhanced through data mining and analysis from different levels. For coming blockchain, traceability block structure optimization, privacy protection, block chain consensus algorithm should be performed to meet the requirement agri-food. In fact, AI, big data, block chain and other technologies have different characteristics. In order to improve the intelligent level for traceability system, the different technologies should be integrated deeply. This paper provides a useful reference for grasping the development trend of traceability system, for knowing the research hot spot and for understanding the application bottleneck.