Feature-Based Molecular Network-Assisted Cannabinoid and Flavonoid Profiling of Cannabis sativa Leaves and Their Antioxidant Properties.

Abstract

Cannabis sativa (C. sativa) leaves are rich in cannabinoids and flavonoids, which play important antioxidant roles. Since the environmental factors may influence the accumulation of antioxidants in herbal medicines, which affects their activity, this study aimed to investigate the correlation between the chemical composition of C. sativa leaves and their geographical origin and antioxidant activity. Firstly, a high-resolution mass spectrometry method assisted by semi-quantitative feature-based molecular networking (SQFBMN) was established for the characterization and quantitative analysis of C. sativa leaves from various regions. Subsequently, antioxidant activity analysis was conducted on 73 batches of C. sativa leaves, and a partial least squares regression (PLS) model was employed to assess the correlation between the content of cannabinoids and flavonoids in the leaves and their antioxidant activity. A total of 16 cannabinoids and 57 flavonoids were annotated from C. sativa, showing a significant regular geographical distribution. The content of flavonoid-C glycosides in Sichuan leaves is relatively high, and their antioxidant activity is also correspondingly high. However, the leaves in Shaanxi and Xinjiang were primarily composed of flavonoid-O glycosides, and exhibited slightly lower antioxidant activity. A significant positive correlation (p < 0.001) was found between the total flavonoids and cannabinoids and the antioxidant activity of the leaves, and two flavonoids and one cannabinoid were identified as significant contributors.