Many fruits are promoted for their health benefits, but their full chemical profiles are often not well understood. Rosa roxburghii is known for its high vitamin C content and is widely used in functional foods. However, scientists still lacked a detailed map of the metabolites responsible for its nutritional value.
This study used untargeted LC–MS metabolomics combined with feature-based molecular networking, a technique that groups similar metabolites into related clusters. This finding helps researchers discover unknown compounds more efficiently.
The researchers identified 251 metabolites and revealed that Rosa roxburghii contains a broader range of vitamin C-related compounds than previously known. In particular, they discovered 17 novel ascorbic acid derivatives, suggesting that vitamin C may exist in multiple modified forms in nature.
In simple terms, the method works like building a “chemical family tree,” allowing researchers to identify new compounds that share similar structures. This discovery could support future work in nutrition science, functional food innovation, and natural-product chemistry.
Reference
Y. Cao, Y. Liu, Q. Yu, J. Zhang, Y. Zhu, Y. Zhang, and Z. Zhang, “Discovery of novel ascorbic acid derivatives and other metabolites in fruit of Rosa roxburghii Tratt through untargeted metabolomics and feature-based molecular networking,” Food Chemistry, vol. 452, p. 139598, 2024, doi: 10.1016/j.foodchem.2024.139598
