Comparative metabolomics profiling reveals the aroma and nutritional diversity of eight wild edible plants

Wild edible plants are important yet undervalued vegetables, due to limited knowledge of their bioactive components and nutritional/functional potential. In this study, we used full-spectrum metabolomics and machine learning to analyze the aroma-related and nutritional components of eight common wild edible plants from Southwest China. The results showed broad differences in the metabolic profiles of these wild edible plants, with Houttuynia cordata and Aralia elata presenting unique metabolic patterns. A total of 1568 volatile metabolites in 12 categories and 4871 nutrient metabolites in 5 categories were detected, mainly terpenoids, esters, amino acids and their derivatives, and organic acids, which are important sources of their aroma and nutrition. In addition, Random Forest analysis screened 82 key metabolites, which are major contributors to the differences between ferns and angiosperms. This study clarifies the diversity of wild edible plants and their flavor-nutrition synergies, offering theoretical support for food development and dietary innovation.