Abstract: Agricultural product quality and safety traceability can effectively enhance the trust between supply chain entities and consumers. It is often required for precise quality and safety recall mechanisms to ensure national food safety in recent years. This article aims to systematically summarize the basic concepts and classifications of agricultural product quality and safety traceability in China. The history of traceability was elaborated in three stages: institutional frameworks, platform construction, and digital transformation. The key technologies were successfully integrated, such as the Internet of Things, big data, blockchain, and artificial intelligence. Significant progress was achieved in information perception, data processing, anti-counterfeiting traceability, and intelligent analysis. Its technological empowerment was elucidated across the three-dimensional layer, including the information perception, processing, and decision-making layer. The advantages and disadvantages of these traceability applications were discussed to summarize the existing traceability platforms, national standards, industry standards, and local standards. However, some challenges remained in the data sharing and integration, including the severe data silos, diverse traceability models, as well as the less standards and specifications. Additionally, the high costs and the limited integration of emerging technologies with the traceability framework have restricted the promotion and application of such systems. The traceability technology was also aligned with the market-oriented applications and platform implementation in practice. The optimal systems were gradually improved the standardization frameworks. Future research and application can focus on the following aspects. In the traceability information perception, the intelligent equipment (such as embodied intelligence and low-altitude drones) will play a significant role in the logistics and distribution. Hardware development can also drive toward greater intelligence and automation. In traceability information processing, large-scale models and quantum blockchains can be explored in data processing and intelligent decision-making. In the traceability information interaction, cutting-edge technologies can be applied, like big data, the Internet, and the Internet of Things. Furthermore, the next-generation technologies were integrated with the traceability system, such as 3D printing, the metaverse, and digital twins. The traceability standards can evolve into cross-platform, cross-regional, cross-departmental, and even cross-border collaborative traceability. Application-oriented standard leadership can be strengthened for a unified technical standard system. A traceability standard system can be developed to cover the entire supply chain of agricultural products. Finally, the findings can provide theoretical support and practical guidance to advance the intelligent and collaborative system.