Comprehensive characterisation of ylang-ylang essential oils according to distillation time, origin, and chemical composition using a multivariate approach applied to average mass spectra and segmented average mass spectral data

Flower Power: An Overview on Chemistry and Biological Impact of Selected Essential Oils from Blossoms

Natural raw materials such as essential oils have received more and more attention in recent decades, whether in the food industry, as flavorings and preservatives, or as insecticides and insect repellents. They are, furthermore, very popular as fragrances in perfumes, cosmetics, and household products. In addition, aromatherapy is widely used to complement conventional medicine. This review summarizes investigations on the chemical composition and the most important biological impacts of essential oils and volatile compounds extracted from selected aromatic blossoms, including Lavandula angustifolia, Matricaria recutita, Rosa x damascena, Jasminum grandiflorum, Citrus x aurantium, Cananga odorata, and Michelia alba. The literature was collected from PubMed, Google Scholar, and Science Direct. Blossom essential oils discussed in this work are used in a wide variety of clinical issues. The application is consistently described as safe in studies and meta-analyses, although there are notes that using essential oils can also have side effects, especially dermatologically. However, it can be considered as confirmed that essential oils have positive influences on humans and can improve quality of life in patients with psychiatric disorders, critically ill patients, and patients in other exceptional situations. Although the positive effect of essential oils from blossoms has repeatedly been reported, evidence-based clinical investigations are still underrepresented, and the need for research is demanded.

Probing surface properties of organic molecular layers by scanning tunneling microscopy

In view of the relevance of organic thin layers in many fields, the fundamentals, growth mechanisms, and dynamics of thin organic layers, in particular thiol-based self-assembled monolayers (SAMs) on Au(111) are systematically elaborated. From both theoretical and practical perspectives, dynamical and structural features of the SAMs are of great intrigue. Scanning tunneling microscopy (STM) is a remarkably powerful technique employed in the characterization of SAMs. Numerous research examples of investigation about the structural and dynamical properties of SAMs using STM, sometimes combined with other techniques, are listed in the review. Advanced options to enhance the time resolution of STM are discussed. Additionally, we elaborate on the extremely diverse dynamics of various SAMs, such as phase transitions and structural changes at the molecular level. In brief, the current review is expected to supply a better understanding and novel insights regarding the dynamical events happening in organic SAMs and how to characterize these processes.

Profiling of Aroma-Active Compounds in Ylang-Ylang Essential Oils by Aroma Extract Dilution Analysis (AEDA) and Chemometric Methods

The aroma-active compounds in the extra, first, and third grades of ylang-ylang essential oils (YYEO) from Comoros and Madagascar were identified by gas chromatography-mass spectrometry with olfactometry (GC-MS/O) using an aroma extract dilution analysis (AEDA) technique. In the previous study, the authors investigated differences in volatile compound profiles between YYEO of different grades and regions using GC coupled with a flame ionization detector (FID) and GC-MS. This study follows up with identification of the aroma-active compounds present in YYEO of various grades from both origins and to profile the aroma of those oils. For the first time, principal component analysis (PCA) on AEDA logarithmic flavor dilution (LFD) data was performed, in comparison with the corresponding PCA on GC-FID-MS data. Based on AEDA data, 21 aroma-active compounds were found across all samples and grades of YYEO, with 8 common ones previously identified by GC-FID. Linalool had the highest odor activity and is the major component of YYEO, followed by geraniol, although the latter only appeared as a much smaller peak in the chromatogram. Other trace compounds such as eugenol and vanillin were also found to be significant to the aroma of YYEO. Using PCA on resulting LFD data, YYEO from Comoros were found to have spicier odor qualities as compared to those from Madagascar. The main contributors that determine the difference in a spicy aroma profile of Comoros and Madagascar oils are vanillin, methyl eugenol, and trans-cinnamyl acetate.

Smartphone-based handheld Raman spectrometer and machine learning for essential oil quality evaluation

We present a method, utilising a smartphone-based miniaturized Raman spectrometer and machine learning for the fast identification and discrimination of adulterated essential oils (EOs). Firstly, the approach was evaluated for discrimination of pure EOs from those adulterated with solvent, namely benzyl alcohol. In the case of ylang-ylang EO, three different types of adulteration were examined, adulteration with solvent, cheaper vegetable oil and a lower price EO. Random Forest and partial least square discrimination analysis (PLS-DA) showed excellent performance in discriminating pure from adulterated EOs, whilst the same time identifying the type of adulteration. Also, utilising partial least squares regression analysis (PLS) all adulterants, namely benzyl alcohol, vegetable oil and lower price EO, were quantified based on spectra recorded using the smartphone Raman spectrometer, with relative error of prediction (REP) being between 2.41-7.59%.

Radical scavenging activity and metabolomic profiling study of ylang-ylang essential oils based on high-performance thin-layer chromatography and multivariate statistical analysis

Ylang-ylang (YY) essential oil (EO) is distilled from the fresh-mature flowers of the Annonaceae family tropical tree Cananga odorata [Lam.] Hook. f. & Thomson, and is widely used in perfume and cosmetic industries for its fragrant character. Herein, two different metabolomic profiles obtained using high-performance thin-layer chromatography (HPTLC), applying different stains, namely 2,2-diphenyl-1-picrylhydrazyl (DPPH·) and p-anisaldehyde, were used for discrimination of 52 YY samples across geographical origins and distillation grades. The first profile is developed using the DPPH· stain based on the radical scavenging activity (RSA) of YY EOs. Results of the HPTLC-DPPH· assay confirmed that RSA of YY EOs is in proportion to the length of distillation times. Major components contributing to the RSA of YY EOs were tentatively identified as germacrene D and α-farnesene, eugenol and linalool, by gas chromatography-mass spectrometry (GC-MS) and GC-flame ionisation detector (GC-FID). The second profile was developed using the general-purpose p-anisaldehyde stain based on the general chemical composition of YY EOs. Untargeted metabolomic discrimination of YY EOs from different geographical origins was performed based on the HPTLC-p-anisaldehyde profiles, followed by principal component analysis (PCA). A discrimination and prediction model for identification of YY distillation grade was developed using PCA and partial least squares regression (PLS) based on binned HPTLC-ultraviolet (254 nm) profiles, which was successfully applied to distillation grade determination of blended YY Complete EOs.

Data handling and data analysis in metabolomic studies of essential oils using GC-MS

Gas chromatography electron impact ionization mass spectrometry (GC-EI-MS) has been, and remains, the most widely applied analytical technique for metabolomic studies of essential oils. GC-EI-MS analysis of complex samples, such as essential oils, creates a large volume of data. Creating predictive models for such samples and observing patterns within complex data sets presents a significant challenge and requires application of robust data handling and data analysis methods. Accordingly, a wide variety of software and algorithms has been investigated and developed for this purpose over the years. This review provides an overview and summary of that research effort, and attempts to classify and compare different data handling and data analysis procedures that have been reported to-date in the metabolomic study of essential oils using GC-EI-MS.