Mapping sleep-promoting volatiles in aromatic plants with machine learning: a comprehensive survey of 2300 molecules

Key Points

• This research aims to identify and map sleep-promoting volatiles in aromatic plants using machine learning techniques.
• Applied machine learning algorithms to analyze a database of 2300 molecules from aromatic plants.
• Conducted in vivo validation to confirm sleep-promoting effects of identified volatiles.
• Examined the distribution of these volatiles across 991 different aromatic plants.
• Successfully identified several volatiles with sleep-promoting properties.
• Mapped the occurrence of these volatiles among a wide variety of aromatic plants.
• Provided insights into potential natural sources for sleep aids.