人工智能赋能下的中外食品快速检测技术发展路径比较分析与展望

Comparative analysis and prospective outlook on the development pathways of food rapid detection technology in China and abroad under the empowerment of artificial intelligence

中文关键词:  食品快速检测  胶体金免疫层析  手持式拉曼光谱  纳米传感器  人工智能

英文关键词:food rapid detection technology  colloidal gold immunochromatography  handheld Raman spectroscopy  nanosensors  artificial intelligence

中文摘要:

      食品安全问题日益受到全球关注, 发展快速、准确且适用于现场的检测技术成为迫切需求, 而智能化与快速检测技术的融合为此提供了重要发展方向。本文旨在系统梳理人工智能(artificial intelligence, AI)与食品快速检测技术融合的最新进展, 并以此为核心分析视角, 对比考察其在中国及主要发达国家技术发展路径中的不同角色、融合模式与驱动逻辑。对比国内外发展路径可知, 我国利用胶体金多联卡等技术建立起适合于基层监管使用的快速筛查体系, 而发达国家则着重于发展高精度生物传感技术, 并建立起覆盖整个产业链的精密检测网。快速检测技术在我国目前仍存在诸如核心材料制备工艺未完全成熟、基层检测人员的操作水平不符合智能化设备要求等问题。未来, 多元多源融合的方向将是重要的发展趋势之一, 主要体现在AI与生物传感器的深度融合, 例如拉曼光谱与深度学习的耦合, 不仅能实现复杂食品基质的快速准确检测, 更能推动检测系统从单一工具向智能决策系统的转变。此外, 本文提出为提升智能化食品快检技术发展脉络的把握和我国技术研发布局的优化水平需促进对检测标准的国际合作互认, 积极参与到食品检测国际技术联盟中来, 为推进全球食品安全治理体系协同发展做出更多的努力。

英文摘要:

      Food safety issues have garnered increasing global attention, creating an urgent need for the development of rapid, accurate and on-site detection technology, and the integration of intelligent and rapid detection methods provides a crucial direction for future development. This paper aimed to systematically review the latest advances in the integration of artificial intelligence (AI) and rapid food detection technology. Using this as the core analytical perspective, it compared and examined the different roles, integration modes and driving logics of such integration in the technological development paths of China and major developed countries. A comparison of development paths between China and other countries revealed that China had established a rapid screening system suitable for grassroots regulatory use through technologies like colloidal gold multi-test card. In contrast, developed countries had focused more on high-precision biosensing technologies and established comprehensive precision detection networks that cover the entire industry chain. Rapid detection technologies in China currently faced challenges, including incomplete maturation of core material preparation processes and the operational proficiency of grassroots testing personnel not meeting the requirements of intelligent equipment. In the future, the direction of multi-source and multi-element fusion would become one of the important development trends, which was mainly reflected in the in-depth integration of AI with biosensors. For instance, the coupling of Raman spectroscopy with deep learning could not only achieve rapid and accurate detection of complex food matrices, but also derived the evolution of detection systems from a single-purpose tool into intelligent decision-making systems. Furthermore, this paper proposed that to enhance the grasp of the development trajectory of intelligent food rapid detection technology and improve rove China’s technology research and development layout, it was important to strengthen international cooperation and mutual recognition of detection standards. Active participation in the International Technical Alliance for Food Detection was essential to contribute greater efforts toward advancing the global food safety governance system.