Search

Sustainable agro-waste revaluation is critical to enhance the profitability and environmental footprint of the olive oil industry. Herein, the valorization of olive leaf pruning waste from five cultivars ('Caiazzana', 'Carolea', 'Itrana', 'Leccino', and 'Frantoio') employed green extraction methods to recover compounds with potential health benefits. Sequential ultrasound-assisted maceration (UAM) in n-hexane and ethanol was compared with a compressed fluid extraction strategy consisting of supercritical fluid extraction (SFE) and pressurized liquid extraction (PLE) for their efficiency in recovering distinct classes of bioactives. Chemical profiling by UHPLC-HR-MS/MS (ultra-high-performance liquid chromatography high-resolution tandem mass spectrometry) and GC-MS (gas chromatography mass spectrometry) showed that UAM-EtOH effectively extracted polyphenols (especially luteolin derivatives) and triterpenes (notably maslinic acid), while PLE yielded the highest amount of secoiridoids (e.g., secologanoside). PLE extracts showed better antiradical activities, putatively due to a higher content of flavonoids, secoiridoids, and HCA derivatives than UAM-EtOH ones, as these latter also contained 20–40% (cultivar-dependent) of triterpenes. SFE extracts with a higher concentration of fatty acids and triterpenes showed moderate antioxidant activities but very high AChE inhibition. This study highlights the importance of selecting appropriate extraction methodologies based on the target bioactive compounds and underscores the potential of olive leaf extracts for sustainable bio-products. [ABSTRACT FROM AUTHOR]

Introduction: The genus Salvia L., a member of the family Lamiaceae, is a keystone genus with a wide range of medicinal properties. It possesses a rich metabolite source that has long been used to treat different disorders., Objectives: Due to a deficiency of untargeted metabolomic profiling in the genus Salvia, this work attempts to investigate a comprehensive mass spectral library matching, computational data annotations, exclusive biomarkers, specific chemotypes, intraspecific metabolite profile variation, and metabolite enrichment by a case study of five medicinal species of Salvia., Material and Methods: Aerial parts of each species were subjected to QTRAP liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis workflow based on untargeted metabolites. A comprehensive and multivariate analysis was acquired on the metabolite dataset utilizing MetaboAnalyst 6.0 and the Global Natural Products Social Molecular Networking (GNPS) Web Platform., Results: The untargeted approach empowered the identification of 117 metabolites by library matching and 92 nodes annotated by automated matching. A machine learning algorithm as substructural topic modeling, MS2LDA, was further implemented to explore the metabolite substructures, resulting in four Mass2Motifs. The automated library newly discovered a total of 23 metabolites. In addition, 87 verified biomarkers of library matching, 58 biomarkers of GNPS annotations, and 11 specific chemotypes were screened., Conclusion: Integrative spectral library matching and automated annotation by the GNPS platform provide comprehensive metabolite profiling through a workflow. In addition, QTRAP LC-MS/MS with multivariate analysis unveiled reliable information about inter and intraspecific levels of differentiation. The rigorous investigation of metabolite profiling presents a large-scale overview and new insights for chemotaxonomy and pharmaceutical studies., (© 2024 John Wiley & Sons Ltd.)