Phytochemical and Functional Diversity of Enzyme-Assisted Extracts from Hippophae rhamnoides L., Aralia cordata Thunb., and Cannabis sativa L.
Viktorija JanuskeviceAna Maria Pereira GomesSérgio SousaJoana Cristina BarbosaRita VedorPaulina MartuseviceMindaugas LiaudanskasVaidotas ZvikasPranas ViškelisLaima CesonieneAiste BalciunaitieneJonas ViskelisSonata SzonnDalia UrbonavicienePublished in: Antioxidants (Basel, Switzerland) (2024)
Plant leaves are a source of essential phenolic compounds, which have numerous health benefits and can be used in multiple applications. While various techniques are available for recovering bioactive compounds from by-products, more data are needed on enzyme-assisted extraction (EAE). The aim of this study was to compare EAE and solid-liquid extraction (SLE), to evaluate the impact on bioactive compounds' extraction yield, phytochemical composition, and the antioxidant, antimicrobial, and antidiabetic properties of Aralia cordata leaves and roots, sea buckthorn Hippophae rhamnoides, and hemp Cannabis sativa leaves. The results indicate that EAE with Viscozyme L enzyme (EAE_Visc) extracts of the tested plant leaves possess the highest yield, antioxidant activity, and total phenolic content. Moreover, the EAE_Visc extract increased by 40% the total sugar content compared to the control extract of A. cordata root. Interestingly, the sea buckthorn leaf extracts exhibited α-glucosidase inhibitory activity, which reached an almost 99% inhibition in all extracts. Furthermore, the sea buckthorn leaves SLE and EAE_Visc extracts possess antibacterial activity against Staphylococcus aureus . Additionally, scanning electron microscopy was used to examine changes in cell wall morphology after EAE. Overall, this study shows that EAE can be a promising method for increasing the yield and improving the functional properties of the resulting extracts in a fast and sustainable way compared to SLE.
Keyphrases
- systemic lupus erythematosus
- staphylococcus aureus
- cell wall
- electron microscopy
- oxidative stress
- essential oil
- public health
- disease activity
- mental health
- anti inflammatory
- machine learning
- risk assessment
- pseudomonas aeruginosa
- cystic fibrosis
- molecular docking
- big data
- social media
- molecular dynamics simulations