Abstract: The quality of traditional Chinese medicine (TCM) is the lifeline for TCM industry. The development of artificial intelligence (AI) has provided new means for the quality management of Chinese medicinal materials (CMM). In this paper, we take the quality marker (Q-marker) as a breakthrough point, focused on the research strategy from chemical markers to Q-markers, picked up the characteristics of the Q-markers from the near infrared spectrum (NIRS), and explored the feasibility of establishing the NIRS assay based on Q-marker. After integrated the biological activity detection and artificial neural network algorithm, we try to establish the relationship between the spectral properties of NIRS and specific efficacy of the CMM. Finally, the bottlenecks will be solved that related to the transmission and traceability of quality attributes in the process of TCM production, quantity change, overall quality management and so on. This system is going to improve TCM quantity scientific and intelligent supervision, and promote the upgrading of traditional TCM industry.