Maxleene Sandasi

An untargeted metabolomic approach in the chemotaxonomic assessment of two Salvia species as a potential source of α-bisabolol.

α-Bisabolol is a commercially important aroma chemical currently obtained from the Candeia tree (Vanillosmopsis erythropappa). Continuous unsustainable harvesting of the Candeia tree has prompted the urgent need to identify alternative crops as a source of this commercially important sesquiterpene alcohol. A chemotaxonomic assessment of two Salvia species indigenous to South Africa is presented and recommended as a potential source of α-bisabolol. The essential oil obtained by hydrodistillation of the aerial parts was analysed by gas chromatography coupled to mass spectrometry (GC-MS) and mid-infrared spectroscopy (MIRS). Orthogonal projections to latent structures-discriminant analysis (OPLS-DA) were used for multivariate classification of the oils based on GC-MS and MIRS data. Partial least squares (PLS) calibration models were developed on the MIRS data for the quantification of α-bisabolol using GC-MS as the reference method. A clear distinction between Salvia stenophylla and Salvia runcinata oils was observed using OPLS-DA on both GC-MS and MIRS data. The MIR calibration model showed high coefficient of determination (R² = 0.999) and low error of prediction (RMSEP=0.540%) for α-bisabolol content.

Hyperspectral Imaging and Chemometric Modeling of Echinacea — A Novel Approach in the Quality Control of Herbal Medicines

Echinacea species are popularly included in various formulations to treat upper respiratory tract infections. These products are of commercial importance, with a collective sales figure of

Antimicrobial activity and chemometric modelling of South African propolis.

132 million in 2009. Due to their close taxonomic alliance it is difficult to distinguish between the three Echinacea species and incidences of incorrectly labeled commercial products have been reported. The potential of hyperspectral imaging as a rapid quality control method for raw material and products containing Echinacea species was investigated. Hyperspectral images of root and leaf material of authentic Echinacea species (E. angustifolia, E. pallida and E. purpurea) were acquired using a sisuChema shortwave infrared (SWIR) hyperspectral pushbroom imaging system with a spectral range of 920–2514 nm. Principal component analysis (PCA) plots showed a clear distinction between the root and leaf samples of the three Echinacea species and further differentiated the roots of different species. A classification model with a high coefficient of determination was constructed to predict the identity of the species included in commercial products. The majority of products (12 out of 20) were convincingly predicted as containing E. purpurea, E. angustifolia or both. The use of ultra performance liquid chromatography-mass spectrometry (UPLC-MS) in the differentiation of the species presented a challenge due to chemical similarities between the solvent extracts. The results show that hyperspectral imaging is an objective and non-destructive quality control method for authenticating raw material.

The in vitro antimicrobial activity and chemometric modelling of 59 commercial essential oils against pathogens of dermatological relevance.

This study reports on the inhibitory and bactericidal properties of 39 South African (SA) propolis samples and three propolis samples from Brazil.

Chemical composition and antimicrobial activity of Eucalyptus radiata leaf essential oil, sampled over a year

This study reports on the inhibitory concentration of 59 commercial essential oils recommended for dermatological conditions, and identifies putative compounds responsible for antimicrobial activity. Essential oils were investigated for antimicrobial activity using minimum inhibitory concentration assays. Ten essential oils were identified as having superior antimicrobial activity. The essential oil compositions were determined using gas chromatography coupled to mass spectrometry and the data analysed with the antimicrobial activity using multivariate tools. Orthogonal projections to latent structures models were created for seven of the pathogens. Eugenol was identified as the main biomarker responsible for antimicrobial activity in the majority of the essential oils. The essential oils mostly displayed noteworthy antimicrobial activity, with five oils displaying broad‐spectrum activity against the 13 tested micro‐organisms. The antimicrobial efficacies of the essential oils highlight their potential in treating dermatological infections and through chemometric modelling, bioactive volatiles have been identified.

Skullcap and germander: preventing potential toxicity through the application of hyperspectral imaging and multivariate image analysis as a novel quality control method.

Abstract This study investigated the seasonal variation of the chemical composition and antimicrobial activity of Eucalyptus radiata leaf essential oil. Young and mature Eucalyptus radiata leaf material was collected monthly (January 2014 to December 2014), hydrodistilled and analyzed using GC-MS. Essential oil yields ranged from 0.14% to 4.31% (w/w). The major compounds were 1,8-cineole (65.7% ± 9.5), α-terpineol (12.8% ± 4.4) and limonene (6.5% ± 2.4). Chemometric tools were used to determine seasonal variations, which showed slight variance in E. radiata chemistry between seasons. The minimum inhibitory concentration (MIC) assay showed that the highest activity was noted against the Streptococci (0.19–2.00 mg/mL) and Lactobacillus acidophilus (0.19–1.75 mg/mL). The activity of the E. radiata leaf essential oil is dependent on the unique ratio of its compounds. The E. radiata leaf essential oil showed good oil yields, a relatively consistent chemical profile and noteworthy antimicrobial activity that rivals other commercial Eucalypt counterparts.

Uzara – A quality control perspective of Xysmalobium undulatum

Scutellaria lateriflora (skullcap) is a medicinal herb that has a long history of use in the treatment of ailments such as insomnia and anxiety. Commercial herbal formulations claiming to contain S. laterifolia herba have flooded the consumer markets. However, due to intentional or unintentional adulteration, cases of hepatotoxicity have been reported. Possible adulteration with the potentially hepatotoxic Teucrium spp., T. canadense and T. chamaedrys has been reported. In this study, hyperspectral imaging in combination with multivariate image analysis methods was used to differentiate S. laterifolia, T. canadense, and T. chamaedrys raw materials in a non-destructive manner. Furthermore, the ability to detect adulteration of raw materials using the developed multivariate models was also investigated. Chemical images were captured using a shortwave infrared pushbroom imaging system in the wavelength range 920-2514 nm. Principal component analysis was applied to the images to investigate chemical differences between the species. Partial least squares discriminant analysis was used to model pre-assigned class images, and the classification model predicted the levels of adulteration in spiked raw materials. UHPLC-MS as an independent analytical technique was used to confirm chemical differences between the three species. The ability of hyperspectral chemical imaging as a non-destructive technique in the differentiation of the three species was achieved with three distinct clusters in the score scatter plot. A 92.3 % variation in modelled data using PC1 and PC2 was correlated to chemical differences between the three species. Near infrared signals in the regions 1924 nm and 2092 nm (positive P1), 1993 nm and 2186 nm (negative P1), 1918 nm, 2092 nm, and 2266 nm (positive P2), as well as 1993 nm and 2303 nm (negative P2) were identified as containing discriminating information using the loadings line plots. Chemical imaging of spiked samples showed spatial orientation of contaminants within the powdered samples, and percentage adulteration was accurately predicted at levels ≥ 40 % adulteration based on pixel abundance.

The Application of Vibrational Spectroscopy Techniques in the Qualitative Assessment of Material Traded as Ginseng

Abstract Context: Xysmalobium undulatum (L.) Aiton f var. (Asclepiadaceae), commonly known as uzara, is an ethnomedicinally important plant from southern Africa used to treat a variety of ailments. In addition to local use in African Traditional Medicine (ATM), formulations containing uzara have been successfully marketed by a number of pharmaceutical companies. Despite its commercialization, published adequate quality control (QC) protocols are lacking. Objective: The study was conducted to develop QC protocols for uzara based on chromatographic and spectroscopic techniques. Materials and methods: High performance thin layer chromatography (HPTLC) and liquid chromatography coupled to mass spectrometry (LC-MS) were used to develop phytochemical fingerprints of ethanolic root extracts of 47 uzara samples collected from eight distinct localities in South Africa. Mid-infrared (MIR) spectroscopy was also explored as a suitable alternative technique for rapid and economic quantification of uzarin. Results: Adequate chromatographic profiles were obtained using both HPTLC and LC-MS analyses. The chromatographic patterns showed qualitative similarities among plants collected from different locations. The levels of uzarin, the major constituent of uzara, were highly variable between locations, ranging from 17.8 to 139.9 mg/g (dry weight). A good coefficient of determination (R2 = 0.939) and low root mean square error of prediction (RMSEP = 7.9 mg/g) confirmed the accuracy of using MIR-PLS calibration models for the quantification of uzarin. Discussion and conclusion: Both HPTLC and LC-MS can be used as tools in developing quality control procedures for uzara. MIR in combination with chemometrics provides a fast alternative method for the quantification of uzarin.

Identification of potential anti-quorum sensing compounds in essential oils: a gas chromatography-based metabolomics approach

The name “ginseng” is collectively used to describe several plant species, including Panax ginseng (Asian/Oriental ginseng), P. quinquefolius (American ginseng), P. pseudoginseng (Pseudoginseng) and Eleutherococcus senticosus (Siberian ginseng), each with different applications in traditional medicine practices. The use of a generic name may lead to the interchangeable use or substitution of raw materials which poses quality control challenges. Quality control methods such as vibrational spectroscopy-based techniques are here proposed as fast, non-destructive methods for the distinction of four ginseng species and the identification of raw materials in commercial ginseng products. Certified ginseng reference material and commercial products were analysed using hyperspectral imaging (HSI), mid-infrared (MIR) and near-infrared (NIR) spectroscopy. Principal component analysis (PCA) and (orthogonal) partial least squares discriminant analysis models (OPLS-DA) were developed using multivariate analysis software. UHPLC-MS was used to analyse methanol extracts of the reference raw materials and commercial products. The holistic analysis of ginseng raw materials revealed distinct chemical differences using HSI, MIR and NIR. For all methods, Eleutherococcus senticosus displayed the greatest variation from the three Panax species that displayed closer chemical similarity. Good discrimination models with high R2X and Q2 cum vales were developed. These models predicted that the majority of products contained either /P. ginseng or P. quinquefolius. Vibrational spectroscopy and HSI techniques in tandem with multivariate data analysis tools provide useful alternative methods in the authentication of ginseng raw materials and commercial products in a fast, easy, cost-effective and non-destructive manner.

Application of hyperspectral imaging in the quality control of medicinal plants and products

ABSTRACT Quorum sensing is a form of bacterial cell-to-cell communication, which plays an important role in bacterial pathogenicity. Due to increasing drug resistance, quorum sensing has been identified as a potential target to reduce the risk of developing drug resistance. The current study aims at investigating the antiquorum sensing activity of 40 commercial essential oils of therapeutic relevance. The agar well diffusion method, microdilution assay and spectrophotometric quantification of violacein production, assessed antiquorum sensing in Chromobacterium violaceum. Gas chromatography coupled to mass spectrometry (GC-MS) profiled essential oil constituents. A correlation between antiquorum sensing activity and essential oil chemistry was investigated in SIMCA-P + 14.0. The essential oils that displayed remarkable antiquorum sensing activity (inhibition ≥ 90%) at 0.25 mg/ml were; Cymbopogon sp., Citrus limon, Eucalyptus dives, Eugenia caryphyllus, Mentha sp., Myrtus communis and Pinus ponderosa. Eugenol, geraniol, geranial, menthol and pulegone were identified as putative biomarkers correlated to the active oils.