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Characterization and association patterns of Chinese food-medicine homologous species based on big data analytics
Yaqun Liu1,2,3, Chunjuan Zhou1, Yukai Wan4
1School of Life Sciences and Food Technology, Hanshan Normal University, Chaozhou, China.
Background:
This study employs big data analytics to explore the characteristics and association patterns of 102 Chinese food-medicine homologous (CFMH) species recognized by the National Health Commission of China, focusing on their medicinal attributes, flavors, associated meridians, and geographical distributions.
Results:
Our findings reveal that most CFMH species originate from plants, particularly fruits and rhizomes, and are predominantly characterized as warm or neutral with a sweet flavor profile. Significant geographical clustering was identified in southern China, with notable associations between specific CFMH species and therapeutic meridians, supporting potential pathways for therapeutic applications.
Conclusion:
The integration of traditional Chinese medicine insights with modern big data analytics offers a powerful approach to understanding and leveraging the multifunctional nature of CFMH species. This study enhances our knowledge of CFMH species' characteristics and their potential health benefits, providing a foundation for further scientific exploration and application in healthcare. © 2025 Society of Chemical Industry.
