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.

Characterisation of complex perfume and essential oil blends using multivariate curve resolution-alternating least squares algorithms on average mass spectrum from GC-MS.

Quality control of essential oil blends and the discovery of potential adulterations and product fraud is a significant challenge within the natural oil and perfume industry. In this research, total chromatogram average mass spectra (TCAMS), created from the GC-MS three-way raw data, were employed for the characterisation of complex samples of perfumes and essential oil blends. A multivariate approach for curve resolution was used to resolve the TCAMS of pure essential oils within such perfume and essential oil blends. Resolved TCAMS, in combination with unsupervised pattern recognition approaches revealed the distillation grade and origin of used ylang-ylang oils in perfume mixtures. TCAMS resolved from the essential oil blends were used with a supervised machine learning classification model to identify oils, used in creating the blends. Quantification was performed using a multivariate curve resolution approach, resulting in relative errors of prediction lower than 17.84% with root mean square errors of prediction smaller than 3.43.

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.

Analyses of the complex essential oil samples using gas chromatography hyphenated with mass spectrometry (GC-MS) generate large three-way data arrays. Processing such large data sets and extracting meaningful information in the metabolic studies of natural products requires application of multivariate statistical techniques (MSTs). From the GC-MS raw data several different input data sets for the MSTs can be created, including total chromatogram average mass spectra (TCAMS), segmented average mass spectra (SAMS) and chemical composition. Herein, we compared the performance of MSTs on average mass spectrum based data sets, TCAMS and SAMS, against chemical composition and attenuated total reflectance - Fourier transformation infrared (ATR-FTIR) spectroscopy in the evaluation of quality of ylang-ylang essential oils, based on their grade, geographical origin and chemical composition, using principal component analysis (PCA), partial least squares regression (PLS) and discriminatory analysis (PLS-DA). PCA based on TCAMS, SAMS and chemical composition showed clear trends amongst the samples based on increase in grade (distillation time). PLS-DA applied to TCAMS, SAMS and ATR-FTIR discriminated between all geographical origins. Predicted relative abundances of the 18 most important compounds, using PLS regression models on TCAMS, SAMS and ATR-FTIR, were successfully applied to ylang-ylang essential oil quality assessment based on comparison with the ISO 3063:2004 standard, where the SAMS data set showed superior performance, compared to other data sets.

Random Forests machine learning applied to gas chromatography - Mass spectrometry derived average mass spectrum data sets for classification and characterisation of essential oils.

Differences in chemical profiles of various essential oils (EOs) come from the fact that each plant species and chemotype has a distinctive secondary metabolism. Therefore, these differences can be used as the chemical markers for EO classification and determination of their quality. Herein, the Random Forests (RF) machine learning algorithm was applied to the classification of 20 different EOs. From three-way raw gas chromatography - mass spectra data, total chromatogram average mass spectra (TCAMS) and segment average mass spectra (SAMS) were created. TCAMS was generated by averaging response of each m/z over the whole chromatogram and SAMS by averaging the response of each fragment across a certain time segment within the chromatogram. The RF model was applied to the two data sets and optimised through the evaluation of pre-processed data, number of trees, and number of variables used in each node split. The performance of the model was evaluated through a cross-validation process, repeated 50 times by dividing the whole sample set into training and validation subsets. The calculated average out-of-bag error (OOBE), over 50 different training TCAMS data sets was 3.22 ±â€¯1.29%, while for SAMS it was found to be 2.28 ±â€¯1.33%. The minimal number of variables necessary for EO classification was determined by a nested cross-validation process. The amount of reduced variables in each step was 10%. It was shown that the TCAMS data set with 6 variables had similar prediction power as the SAMS with 30 variables. OOBE for classification of 20 EOs was 2.89 ±â€¯1.44% and 3.70 ±â€¯1.73%, for TCAMS and SAMS, respectively. Proximity between samples was used to evaluate their qualities. Samples with greater intra-class proximity had good similarity, while the lower ones indicated greater variations in the chemical profiles. The SAMS data set showed superior potential for quality assurance, compared with TCAMS.

Distinct Drimane Chemotypes in Tasmanian Mountain Pepper (Tasmannia lanceolata): Differences in the Profiles of Pungent Leaf Phytochemicals Associated with Altitudinal Cline.

This study assesses whether the distinct altitudinal cline in leaf morphology (decreased leaf width and length with increased altitude) in Tasmanian mountain pepper (Tasmannia lanceolata) is associated with changes in the leaf chemistry of wild populations from different ecological landscapes and altitudes. The presence of distinct pungent drimane sesquiterpenoid chemotypes was identified: subalpine woodland and wet sclerophyll forest chemotypes. Isolation studies and analysis of extracts revealed that wet sclerophyll forest T. lanceolata populations featured polygodial as the principal terpenoid, with profiles similar to the commercial cultivars sampled. In contrast, the subalpine woodland populations contained the drimane sesquiterpenoids 1ß-acetoxy-9-deoxyisomuzigadial and 3ß-acetoxydrimenin and the conspicuous absence of the pungent principle polygodial.

Low-Cost Passive Sampling Device with Integrated Porous Membrane Produced Using Multimaterial 3D Printing.

Multimaterial 3D printing facilitates the rapid production of complex devices with integrated materials of varying properties and functionality. Herein, multimaterial fused deposition modeling (MM-FDM) 3D printing was applied to the fabrication of low-cost passive sampler devices with integrated porous membranes. Using MM-FDM 3D printing, the device body was produced using black polylactic acid, with Poro-Lay Lay-Felt filament used for the printing of the integrated porous membranes (rubber-elastomeric polymer, porous after removal of a water-soluble poly(vinyl alcohol) component). The resulting device consisted of two interlocking circular frames, each containing the integrated membrane, which could be efficiently sealed together without the need for additional O-rings, and prevented loss of enclosed microparticulate sorbent. Scanning electron microscopy (SEM) analysis of the purified composite filament confirmed the porous properties of the material, an average pore size of ∼30 nm. The printed passive samplers with various membrane thicknesses, including 0.5, 1.0, and 1.5 mm, were evaluated for their ability to facilitate the extraction of atrazine as the model solute onto the internal sorbent, under standard conditions. Gas chromatography-mass spectrometry was used to determine the uptake of atrazine by the device from standard water samples and also to evaluate any chemical leaching from the printed materials. The sampler with 0.5 mm thick membrane showed the best performance with 87% depletion and a sampling rate of 0.19 Ld-1 ( n = 3, % RSD = 0.59). The results obtained using these printed sampling devices with integrated membranes were in close agreement to devices fitted with a standard poly(ether sulfone) membrane.

Phytochemical profile of the rare, ancient clone Lomatia tasmanica and comparison to other endemic Tasmanian species L. tinctoria and L. polymorpha.

An investigation of the previously unexamined ancient Tasmanian clone Lomatia tasmanica W. M. Curtis (Proteaceae) and two other endemic species Lomatia tinctoria R. Br. and Lomatia polymorpha (Labill.) R. Br. was undertaken. This represents the first extensive natural products study in which individual phytochemical components have been isolated and identified from these three Lomatia species. Extraction of L. tasmanica leaves provided the naphthoquinone juglone (0.34% w/w), and n-alkanes nonacosane and heptacosane (0.30% w/w combined). L. polymorpha afforded the flavonoid glycosides dihydroquercetin 3-O-ß-D-xyloside (0.22% w/w) and quercetin 3-O-ß-d-glucose (0.14% w/w), as well as the naphthalene glucoside 1,4,8-trihydroxynaphthalene-1-O-ß-d-glucose (0.04% w/w) and 4-O-p-coumaroyl-d-glucose (0.03% w/w). In addition, both L. polymorpha and L. tinctoria contained juglone (0.32% w/w and 0.58% w/w, respectively). L. polymorpha provided tetracosan-1-ol, hexacosan-1-ol and octacosan-1-ol (0.07% w/w combined), while L. tinctoria gave nonacosane (0.13% w/w). Analysis of three individual specimens from each of the three species demonstrated consistency in the respective phytochemical profiles of these populations and tentatively suggests limited intraspecific variation.

Chemotyping of new hop (Humulus lupulus L.) genotypes using comprehensive two-dimensional gas chromatography with quadrupole accurate mass time-of-flight mass spectrometry.

Comprehensive two-dimensional gas chromatography with quadrupole accurate mass time-of-flight mass spectrometry (GC×GC-Q-TOFMS) is employed to profile Humulus lupulus L. (hop) essential oils. Comparison of characterised essential oils allows discrimination among chemotypes. Experimental and commercial hop genotypes displayed distinguishable chemotypic patterns among the volatile secondary metabolites making up their essential oils. In total, 210-306 unique compounds were detected (depending on specific genotype), with 99 of these compounds either positively or tentatively identified. Identified volatile secondary metabolites were grouped into esters, monoterpene hydrocarbons, oxygenated monoterpenes, sesquiterpene hydrocarbons, oxygenated sesquiterpenes and ketones. Terpenoids were the dominant chemical families across all hop genotypes analysed, representing between 67% and 90% of the total ion count. The multidimensional chromatographic profiles of hop essential oils are extremely information-rich, making GC×GC-Q-TOFMS useful for fast screening of new hybrid hop genotypes, and therefore informing breeding strategies to derive new commercial hop cultivars for the development of distinctive and desirable beers.

Parallel comprehensive two-dimensional gas chromatography.

We introduce an information rich analytical approach called parallel comprehensive two-dimensional gas chromatography (2GC×2GC). This parallel chromatography approach splits injected samples into two independent two-dimensional column ensembles and provides two GC×GC separations by using contra-directional thermal modulation. The first-dimension (1D) and second-dimension (2D) columns are connected using planar three-port microchannel devices, which are supplied with supplementary flow via two pressure controller modules. Precise carrier gas flow control at the junction of the 1D and 2D columns permits independent control of flow conditions in each separation column. The 2GC×2GC approach provides two entirely independent GC×GC separations for each injection. Analysis of hop (Humulus lupulus L.) essential oils is used to demonstrate the capability of the approach. The analytical performance of each GC×GC separation in the 2GC×2GC experiment is comparable to individual GC×GC separation with matching column configurations. The peak capacity of 2GC×2GC is about 2 times than that of single GC×GC system. The dual 2D chromatograms produced by this single detector system provide complementary separations and additional identification information by harnessing different selectivity provided by the four separation columns.

Direct Production of Microstructured Surfaces for Planar Chromatography Using 3D Printing.

Through optimization of the printing process and orientation, a suitably developed surface area has been realized upon a 3D printed polymer substrate to facilitate chromatographic separations in a planar configuration. Using an Objet Eden 260VS 3D printer, polymer thin layer chromatography platforms were directly fabricated without any additional surface functionalization and successfully applied to the separation of various dye and protein mixtures. The print material was characterized using gas chromatography coupled to mass spectrometry and spectroscopic techniques such as infrared and Raman. Preliminary studies included the separation of colored dyes, whereby the separation performance could be visualized optically. Subsequent separations were achieved using fluorescent dyes and fluorescently tagged proteins. The separation of proteins was affected by differences in the isoelectric point (pI) and the ion exchange properties of the printed substrate. The simple chromatographic separations are the first achieved using an unmodified 3D printed stationary phase.

Porous, High Capacity Coatings for Solid Phase Microextraction by Sputtering.

We describe a new process for preparing porous solid phase microextraction (SPME) coatings by the sputtering of silicon onto silica fibers. The microstructure of these coatings is a function of the substrate geometry and mean free path of the silicon atoms, and the coating thickness is controlled by the sputtering time. Sputtered silicon structures on silica fibers were treated with piranha solution (a mixture of concd H2SO4 and 30% H2O2) to increase the concentration of silanol groups on their surfaces, and the nanostructures were silanized with octadecyldimethylmethoxysilane in the gas phase. The attachment of this hydrophobic ligand was confirmed by X-ray photoelectron spectroscopy and contact angle goniometry on model, planar silicon substrates. Sputtered silicon coatings adhered strongly to their surfaces, as they were able to pass the Scotch tape adhesion test. The extraction time and temperature for headspace extraction of mixtures of alkanes and alcohols on the sputtered fibers were optimized (5 min and 40 °C), and the extraction performances of SPME fibers with 1.0 or 2.0 µm of sputtered silicon were compared to those from a commercial 7 µm poly(dimethylsiloxane) (PDMS) fiber. For mixtures of alcohols, aldehydes, amines, and esters, the 2.0 µm sputtered silicon fiber yielded signals that were 3-9, 3-5, 2.5-4.5, and 1.5-2 times higher, respectively, than those of the commercial fiber. For the heavier alkanes (undecane-hexadecane), the 2.0 µm sputtered fiber yielded signals that were approximately 1.0-1.5 times higher than the commercial fiber. The sputtered fibers extracted low molecular weight analytes that were not detectable with the commercial fiber. The selectivity of the sputtered fibers appears to favor analytes that have both a hydrophobic component and hydrogen-bonding capabilities. No detectable carryover between runs was noted for the sputtered fibers. The repeatability (RSD%) for a fiber (n = 3) was less than 10% for all analytes tested, and the between-fiber reproducibility (n = 3) was 0-15%, generally 5-10%, for all analytes tested. The repeatabilities of our sputtered fibers and the commercial 7 µm PDMS fiber are essentially the same. Fibers could be used for at least 300 extractions without loss of performance. More than 50 compounds were identified in a gas chromatography-mass spectrometry headspace analysis of a real world botanical sample with the 2.0 µm fiber.

Monodimensional (GC-FID and GC-MS) and comprehensive two-dimensional gas chromatography for the assessment of volatiles and fatty acids from Ruta chalepensis aerial parts.

INTRODUCTION: Ruta chalepensis L. (Rutaceae) is widespread in the Mediterranean area. This plant has a solid tradition in ethnomedicine because of its various biological activities. Based on previous reports, the main volatile constituents of R. chalepensis are 2-undecanone and 2-nonanone, but most are still unknown, particularly fatty acid composition. OBJECTIVE: To exhaustively characterise the chemical composition of the aerial parts from R. chalepensis plants collected from the wild in Sicily, within a project aiming at the evaluation and characterisation of medicinal plants from the Mediterranean flora. The study was directed toward the determination of volatiles and fatty acids in samples of R. chalepensis obtained from different aerial plant parts and from plants harvested at different times. METHODS: GC with flame ionisation detection, GC-MS and two-dimensional gas chromatography (GC × GC) advanced techniques, with support of dedicated mass spectral databases provided with retention index (RI) information, were applied to determine both volatiles and fatty acids. Samples were extracted by hydrodistillation and underwent methylic transesterification in order to be transformed into the correspondent fatty acid methyl esters (FAMEs). RESULTS: The monodimensional analysis by GC-MS with RI confirmed that 2-nonanone and 2-undecanone are the predominant components in all the plant parts, followed by esters and monoterpenes. A different distribution was observed of the main compounds in the various plant parts depending on the life cycle of the plant (vegetative or reproductive stage). The multidimensional GC × GC analysis allowed for a complete screening of the fatty acids. About 65% of the total were polyunsaturated fatty acids (PUFA), followed by 30% of saturated fatty acids (SFA). CONCLUSION: A detailed GC volatile fingerprint of R. chalepensis flowers, leaves, fruits and stems was established, highlighting the compositional differences depending on plant organs and life cycle. The results indicated R. chalepensis as a good source of fatty acids from the w3 and w6 series. In both essential oil and lipidic extract, many compounds were determined for the first time.

Characterisation of lipid fraction of marine macroalgae by means of chromatography techniques coupled to mass spectrometry.

In this work the characterisation of the lipid fraction of several species of marine macro algae gathered along the eastern coast of Sicily is reported. Two species of green marine algae (Chloropyceae), two species of red marine algae (Rhodophyceae) and four species of brown marine algae (Pheophyceae) were evaluated in terms of fatty acids, triacylglycerols, pigments and phospholipids profile. Advanced analytical techniques were employed to fully characterise the lipid profile of these Mediterranean seaweeds, such as GC-MS coupled to a novel mass spectra database supported by the simultaneous use of linear retention index (LRI) for the identification of fatty acid profile; LC-MS was employed for the identification of triacylglycerols (TAGs), carotenoids and phospholipids; the determination of accurate mass was carried out on carotenoids and phospholipids. Quantitative data are reported on fatty acids and triacylglycerols as relative percentage of total fraction.

Rapid collection and identification of a novel component from Clausena lansium Skeels leaves by means of three-dimensional preparative gas chromatography and nuclear magnetic resonance/infrared/mass spectrometric analysis.

The present research reports the use of a three-dimensional preparative gas chromatography (prep GC) system, equipped with three Deans-switch devices and 5%diphenyl/wax/mid-polarity ionic liquid stationary phases, for the isolation of volatile components from a complex natural source, namely wampee essential oil (derived from Clausena lansium Skeels leaves). Collection was performed by using a simple and effective lab-constructed trapping device. Initially, an unknown (and abundant) wampee oil constituent was erroneously identified as α-sinensal, through an MS database search (a low similarity match was attained), performed after a GC-quadMS experiment., The unknown compound was then the isolated by using the novel prep GC system, in a highly pure form (at the mg level), and was correctly identified by using nuclear magnetic resonance (NMR), Fourier transform infrared spectroscopy (FTIR) and mass spectrometry (MS). Both FTIR and MS data were used to confirm the NMR information. The name given to the molecule was (2E,6E)-2-methyl-6-(4-methylcyclohex-3-enylidene)hept-2-enal. The results herein described will demonstrate the need for a high-resolution GC step, prior to analyte collection, in the prep GC analysis of complex samples.

Multiple headspace-solid-phase microextraction: an application to quantification of mushroom volatiles.

Multiple headspace-solid phase microextraction (MHS-SPME) followed by gas chromatography/mass spectrometry (GC-MS) and flame ionization detection (GC-FID) was applied to the identification and quantification of volatiles released by the mushroom Agaricus bisporus, also known as champignon. MHS-SPME allows to perform quantitative analysis of volatiles from solid matrices, free of matrix interferences. Samples analyzed were fresh mushrooms (chopped and homogenized) and mushroom-containing food dressings. 1-Octen-3-ol, 3-octanol, 3-octanone, 1-octen-3-one and benzaldehyde were common constituents of the samples analyzed. Method performance has been tested through the evaluation of limit of detection (LoD, range 0.033-0.078 ng), limit of quantification (LoQ, range 0.111-0.259 ng) and analyte recovery (92.3-108.5%). The results obtained showed quantitative differences among the samples, which can be attributed to critical factors, such as the degree of cell damage upon sample preparation, that are here discussed. Considerations on the mushrooms biochemistry and on the basic principles of MHS analysis are also presented.

Reliable identification and quantification of volatile components of sage essential oil using ultra HRGC.

Salvia officinalis (common sage) essential oil was chemically characterized by means of GC-MS, using 100 meter capillary columns with two different stationary phases. Identification of the analytes was carried out by means of the FFNSC mass spectrum library and the use of the Linear Retention Index (LRI) as an extra criterion of library searching. Quantitative analysis was also carried out by means of GC-FID with the internal standard method and the use of relative response factors determined for each chemical class of components. A total of 45 compounds were identified and quantified and reported with their experimental LRI values.

Application of a multidimensional gas chromatography system with simultaneous mass spectrometric and flame ionization detection to the analysis of sandalwood oil.

The production and trade of Indian sandalwood oil is strictly regulated, due to the impoverishment of the plantations; for such a reason, Australian sandalwood oil has been evaluated as a possible substitute of the Indian type. International directives report, for both the genuine essential oils, specific ranges for the sesquiterpene alcohols (santalols). In the present investigation, a multidimensional gas chromatographic system (MDGC), equipped with simultaneous flame ionization and mass spectrometric detection (FID/MS), has been successfully applied to the analysis of a series of sandalwood oils of different origin. A detailed description of the system utilized is reported. Three santalol isomers, (Z)-α-trans-bergamotol, (E,E)-farnesol, (Z)-nuciferol, epi-α-bisabolol and (Z)-lanceol have been quantified. LoD (MS) and LoQ (FID) values were determined for (E,E)-farnesol, used as representative of the oxygenated sesquiterpenic group, showing levels equal to 0.002% and 0.003%, respectively. A great advantage of the instrumental configuration herein discussed, is represented by the fact that identification and quantitation of target analytes are carried out in one step, without the need to perform two separate analyses.

The Mediterranean red alga Asparagopsis: a source of compounds against Leishmania.

Crude extracts and column fractions from the red algae Asparagopsis taxiformis and A. armata from the Strait of Messina (Italy) were screened for the production of antimicrobial compounds. Extracts from both species revealed remarkable antiprotozoal activity against Leishmania, revealing such algae as a great source of natural antiprotozoal products.