Mentha pulegium L.: A Plant Underestimated for Its Toxicity to Be Recovered from the Perspective of the Circular Economy.
Lucia CaputoLaura CornaraFrancesco Maria RaimondoVincenzo De FeoStefano VaninMarcella DenaroDomenico TrombettaAntonella SmeriglioPublished in: Molecules (Basel, Switzerland) (2021)
The aim of the study was to investigate the micromorphology of Mentha pulegium leaves and flowers harvested in three different Sicilian (Italy) areas with peculiar pedo-climatic conditions, and to characterize the phytochemical profile, the phytotoxic activity, and the eco-compatibility of their essential oils (EOs) for potential use as safe bioherbicides. Light microscopy (LM) and scanning electron microscopy (SEM) highlighted that M. pulegium indumentum consists of non-glandular and glandular trichomes of different types. Peltate trichomes of plants from the different sites showed few significant differences in dimension and abundance, but they were characterized by a surprisingly high number of secretory cells both in leaves and flowers. Phytochemical analyses showed that oxygenated monoterpenes were the most abundant class in all the EOs investigated (92.2-97.7%), but two different chemotypes, pulegone/isomenthone and piperitone/isomenthone, were found. The complex of morphological and phytochemical data indicates that soil salinity strongly affects the expression of the toxic metabolite pulegone, rather than the EO yield. Phytotoxicity tests showed a moderate activity of EOs against the selected species as confirmed by α-amylase assay. Moreover, the low toxicity on brine shrimp provided a rationale for the possible use of investigated EOs as eco-friendly herbicides.
Keyphrases
- electron microscopy
- induced apoptosis
- high throughput
- high resolution
- oxidative stress
- poor prognosis
- atomic force microscopy
- microbial community
- cell cycle arrest
- clinical trial
- single molecule
- electronic health record
- binding protein
- optical coherence tomography
- endoplasmic reticulum stress
- big data
- signaling pathway
- risk assessment
- cell proliferation
- cell death
- human health
- deep learning