Herbs and spices are used globally by most population groups across the world. In sub-Saharan Africa, they have medicinal significance in addition to their culinary uses. Although herbs and spices are often used in combination, there are few studies that report on their interactive antimicrobial effect. This study screened 17 culinary herbs and spices (crude extracts and essential oils) for antimicrobial activity, individually, followed by 1:1 combinations of the active extracts, to determine the outcome of combining these for antibacterial activity. The minimum inhibitory concentrations (MIC) were determined against six common foodborne pathogens using the broth microdilution assay. The design of experiments (DOE) approach was subsequently employed in MODDE 9.1((R)) software, to optimise the experimental runs so as to identify the best interaction that would produce the best possible antimicrobial effect. Phytochemical profiling of the most active extracts was achieved using ultra-performance liquid chromatography coupled to mass spectrometry (UPLC-MS) analysis. The results demonstrated that combining Rosmarinus officinalis with either Syzygium aromaticum, or Salvia officinalis methanol extracts produced synergistic antimicrobial effects towards B. cereus with Sigma FIC = 0.25 mg/ml and 0.31 mg/ml, respectively. The DOE predicted that a combination of higher ratios of R. officinalis (59.5 %), higher ratios of S. officinalis (40 %), and lower ratios of S. aromaticum (0.5 %) would produce the best antimicrobial effect with MIC = 0.17 mg/ml. This was experimentally confirmed and there was a strong correlation (r-value 0.73) between the predicted and experimental MIC values, leading to the identification of an optimal antimicrobial combination. The combination of R. officinalis (56 %) and S. officinalis (44%) produced the antimicrobial effect (MIC = 0.19 mg/ml) which can be recommended for future studies. (c) 2023 The Authors. Published by Elsevier B.V. on behalf of SAAB. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

According to the World Health Organisation, “A Pharmacopoeiaʼs core mission is to protect public health by making available standards to help ensure the quality of medicines” [1]. There are several known documents containing herbal remedies, such as those that date back to ancient Egypt more than 3000 years ago. However, De Materia Medica dating from the 1st century CE in Greece and Rome is arguably perhaps the first example of a “Pharmacopoeia”. Despite the tremendous botanical diversity and widespread use of African Traditional Medicines in South Africa, a compilation of herbal monographs in the form of a Pharmacopoeia acutely focused on the South African flora is lacking. To address this void, we have aimed to collate existing, and generate new data to compile 25 species monographs for botanicals that are currently commercialised or earmarked for commercialisation. In this paper, we discuss the complex workflow required to gain a better understanding of the safety, quality and efficacy of medicinal plants, since these aspects are crucial in monograph development. Several examples will be discussed to illustrate the integration of classic and modern techniques to develop detailed monographs. Ongoing research to document pharmacological activity in an evidence-based ethnopharmacology approach will be presented. Through this project, we aim to provide valuable information for academic research institutions, industrial manufacturers of herbal products, as well as national and international policymakers and regulators, to ensure that products of a desired quality reach the consumer.

The South African Salvia species, Salvia africana-lutea, S. lanceolata and S. chamelaeagnea, are widely used to treat fever and inflammation associated with skin and lung infections. The aim of this study was to explore the nonvolatile secondary metabolites and the phytochemical variation within these lesser known species, to support product development and commercialisation. Chemical profiles of the methanol extracts of 81 wild-harvested samples were obtained using ultra performance-quadrupole-Time-of-Flight-mass spectrometry (UPLC-qToFMS). Forty-one compounds, including caffeic acid, rosmarinic acid, carnosol, carnosic acid and ursolic acid, were detected and confirmed across the three species. Nineteen compounds were tentatively identified of which 14 have not been reported in these species. Principal component analysis revealed distinct clusters corresponding to the three species, confirming chemical differences. Marker compounds for each species were revealed using orthogonal projection to latent structures-discriminant analysis. Further chemometric analysis reflected a degree of intraspecies variation, although the chemistry within populations was mostly conserved. Potential chemotypes for each species were identified through unique compounds associated with each group. The concentrations of medicinally important metabolites, namely, rosmarinic acid, carnosol, carnosic acid and ursolic acid, were determined, using validated UPLC-PDA methods. Ursolic acid was present at levels up to 38.2 mg/g, confirming that these species are a rich source of this compound. No similar studies combining liquid chromatography with chemometric analysis, and utilising a large sample size from various habitats, have been reported for these three Salvia species. The results will guide selection of cultivars with the best attributes for the intended therapeutic application, thereby protecting wild populations from over-exploitation.

Indigenous Salvia species from southern Africa are popular traditional medicines for the treatment of a variety of conditions. They produce fragrant volatiles that can be isolated as essential oils. Some of these volatile organic compounds may play a role in the biological activities of the extracts. Three indigenous Salvia species, Salvia africana-lutea, S. lanceolata and S. chamelaeagnea, were selected for this study as they are commonly used in traditional medicine in South Africa, and the essential oils from these species have potential for commercialisation. Although some studies have described the essential oil compositions and some biological activities, only single composite samples were used. The aim of this study was to investigate the intra- and interspecies variation of the essential oils, sampled over a wide geographical area and using a representative sample size, to encourage commercialisation of the essential oil. Essential oils were isolated from individual plants using conventional hydrodistillation of the aerial parts, harvested from several localities. Gas chromatography coupled simultaneously to mass spectrometry/flame ionisation detection (GC-MS/FID) was used to identify and quantify the volatile constituents. The essential oils of S. africana-lutea consisted mainly of terpinene-4-ol + beta-caryophyllene (1.4 - 29.0%), T-cadinol (1.2 - 20.0%), alpha-eudesmol (trace - 23.0%) and beta-eudesmol (trace - 26.0%), those of S. lanceolata comprised mainly terpinene-4-ol + beta-caryophyllene (4.3 - 31.0%), alpha-humulene (2.3 - 15.0%), bicyclogermacrene (trace - 37.0%) and spathulenol (trace - 25.0%), while the essential oils of S. chamelaeagnea were characterised by delta-3-carene (trace - 18.0%), limonene (1.6 - 36.0%), viridiflorol (9.8 - 61.0%) and 1,8-cineole (not detected - 11.0%). The compounds identified in the essential oils of the three selected Salvia species have been identified in other Salvia essential oils. To add to the novelty of this study, the superior resolving power of two-dimensional gas chromatography was demonstrated through analysis of selected essential oils. Many additional compounds were identified, and previously co-eluting compounds were clearly separated. Chemometric modelling of the GC-MS data using SIMCA P + 14 software allowed distinct clustering patterns to be discerned. The unsupervised principal component analysis model revealed separate clusters for the three species, confirming substantial chemical differences between their essential oils. Quantitative, rather than qualitative differences were evident when individual essential oil samples representing the same species, were compared. For each species, two chemically distinct groups were observed and unique marker compounds could be identified. This study has contributed detailed information on the major and minor volatile compounds present in the essential oils of the three Salvia species investigated.

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.

Researchers are constantly exploring alternative methods to ensure the quality of raw plant materials and herbal products. Conventional quality control techniques may fall short on speed of analysis. Vibrational spectroscopy provides rapid results, uses no solvents and is non-destructive. The application of vibrational spectroscopy and hyperspectral imaging (HSI) in combination with chemometric data analysis as a quality control method was demonstrated using several examples: 1) species differentiation; 2) biomarker quantification and 3) percentage composition. Spectral data was acquired in the mid-infrared (4000-500 cm-1) and near infrared (10 000-4000 cm-1) wave regions and hyperspectral images were acquired in the shortwave infrared region (920-2514 nm). The spectral data obtained was processed using chemometric data analysis techniques.1) Differentiation between closely related species was demonstrated for mid-infrared (MIR) spectral data in the case of powdered Agathosma betulina vs. Agathosma crenulata leaves as well as for whole fruits of Illicium anisatum vs. Illicium verum using hyperspectral imaging; 2) Calibration models (R2≥0.75) based on spectral data were developed for seven major compounds identified in Melaleuca alternifolia essential oil; The biomarker Sutherlandioside B (SU1) was quantified in external samples of powdered Sutherlandia frutescens leaves using the calibration model (R2>0.95) developed; 3) The hyperspectral imaging model developed to determine percentage tea blend composition (Aspalathus linearis/Agathosma betulina) in intact teabags had an R2X_cum of 0.767 and Q2_cum of 0.932 showing good prediction ability. The results showed that these techniques have great potential to be implemented as non-destructive quality control methods depending on the application and the desired accuracy.

Southern Africa harbours a unique flora comprising of over 24 000 species of flowering plants. Woven within this tapestry of botanical diversity is the traditional use of indigenous plants as ethnomedicines. Developing official monographs, establishing a national repository of botanical standards, and producing validated analytical methods is a fundamentally important prerequisite to encourage research and commercialisation of Africa’s medicinal flora. Furthermore, the availability of reference standards, analytical methods and comprehensive monographs would be highly beneficial to the regulator, consumer and nascent industries. The unfortunate underrepresentation of pharmacognosy in the curricula of many pharmacy schools has left a void of expertise, which has hampered the development of a comprehensive herbal Pharmacopoeia. A further challenge involves the inherent complexity of medicinal plants, exacerbated by extensive chemotypic variation. Chemical fingerprinting is a crucial component in characterising plant material and requires a dedicated approach to develop analytical methods for the profiling of complex herbal extracts. Funding from the National Research Foundation (NRF/DST SARChI Initiative) and the South African Medical Research Council has catalysed initiatives at the Tshwane University of Technology to develop herbal monographs that aid in the identification and quality control of important South African herbal medicines. Selected examples will be presented to illustrate the daunting workflow, which includes extensive sampling, the development of analytical methods to profile volatile and non-volatile compounds using GC-MS and LC-MS, HPTLC, vibrational spectroscopy, as well as the use of preparative chromatography to isolate biomarkers. The powerful tandem application of analytical chemistry and chemometric modelling will be highlighted. Developing comprehensive species monographs requires a multidisciplinary collaborative effort which will inevitably contribute to the safety, efficacy and quality of African Traditional Medicines and commercial herbal formulations.

The genus Commiphora has been widely used in traditional medicinal systems to treat pain, skin infections, diarrhoea and periodontal diseases. Oleo-gum resins of seven Commiphora species (C. myrrha, C. confusa, C. baluensis, C. pseudopaolii, C. guidotti, C. holtziana and C. kataf) were collected from Kenya and Ethiopia. Headspace analysis was determined using GCxGC–ToF–MS. In vitro evaluation of antimicrobial activity of acetone extracts were evaluated against a range of micro-organisms using microdilution assay. In addition, anti-quorum sensing activity of the tested Commiphora species was assessed qualitatively and quantitatively using Chromobacterium violaceum strain. α-Pinene (5.6–8.1%), β-caryophyllene (nd-16.5%), cis-β-ocimene (nd-7.4%), α-santalene (nd-40.8%), α-bourbonene (6.9–37.4%), β-elemene (nd-26.2%), curzerene (4.5–8.2%), p-cymene (1.8–54.5%), curzerenone (1.6–25.5%), (Z)-α-bisabolene (nd-10.4%), β-selinene (nd-9.8%), germacrene D (nd-8.4%), cresol methyl ether (nd-8.5%), 7-epi-sesquithujene (nd-8.8%), dehydro-aromadendrene (nd-36.9%), δ-elemene (nd-31.1%) and spathulenol (0.2–10.4%) were the major volatile constituents. Principal component analysis showed three clusters corresponding to three chemotypes within the dataset. The extracts exhibited good to moderate antibacterial activity against a panel of selected micro-organisms (MIC values: 0.06–8.0 mg/mL). Commiphora holtziana displayed the best activity against Candida tropicalis (0.06–4.0 mg/mL), while C. holtziana and C. myrrha exhibited the best anti-quorum sensing activity by inhibiting violacein production.

The quality control of seed oils is an important aspect to consider. Natural seed oils have received much attention as cosmetic ingredients, due to the purported folkloric benefits to the skin. Marula oil is a cold-pressed light-nutty oil included in cosmetics due to the abundance of fatty acids. The commercialisation of Marula seed oil as a natural ingredient in cosmetic products necessitates the need for quality control procedures to ensure the supply of good efficacious oil. There are currently no standards available for the quality control of Marula seed oils. Hence, the study was undertaken to provide some insight into the chemical variation and to investigate the feasibility of using mid-infrared (MIR) spectroscopy as a simple and non-destructive technique for the quantification of the major fatty acids in Marula seed oils. A comparative study was conducted using 1D and 2D chromatography as reference methods. Spectra of the oil were acquired using a Bruker® Alpha-P MIR spectrometer. Partial least squares (PLS) regression models were developed based on MIR data. The calibration models revealed good correlation between the MIR data and 1D-GC values (R2 > 0.80). The predictive ability of the models (Q2 cum) was greater than 0.50. In contrast, the correlation between 2D-GC and the MIR data was low, with R2 values ranging between 0.17 and 0.30. The predictive ability of the models was low (Q2 cum < 0.50). In this study, MIR spectroscopy was identified as a good alternative quality control method, since the technique yielded promising results.

The quality control of herbal material is notoriously challenging due to the complex mixture of compounds present in plants. Hyperspectral imaging (HSI) integrates conventional spectroscopy and imaging to obtain spectral and spatial information from a sample. Once the method has been developed, the visual results are rapidly obtained and easy to interpret. In this study, the use of HSI in combination with chemometric data analysis in quality control was illustrated using three examples: 1) distinguishing between the whole dried fruit of Illicium verum (Chinese star anise) and Illicium anisatum (Japanese star anise); 2) S. tetrandra ('hang fang ji') and its substitution or adulteration with Aristolochia fangchi ('guang fang ji'); 3) determining the proportion of each constituent in a tea blend consisting of Aspalathus linearis (rooibos) and Agathoshma betulina ('buchu'). Hyperspectral images were captured using a shortwave infrared pushbroom imaging system in the wavelength range 920 – 2514nm. Evince® and/or Matlab® software were used to analyse the data. For the star anise example, a classification model was developed and used to accurately predict the identity of whole dried fruit of I. anisatum and I. verum. In the 'fang ji' example, the replicates for each plant species were predicted at a value > 99% for all the samples. Artificially adulterated samples were accurately predicted from as low as 10%. In the herbal tea blend example, the classification model was applied to determine the relative proportions of each blend constituent in intact tea bags. With the increasing need to regulate herbal products and ingredients, emerging technologies are providing alternative methods that allow the holistic analysis of the samples. Hyperspectral imaging is ideally suited as a qualitative tool for the quality control of herbal raw material as it is a visual, rapid, accurate and non-destructive method with high prediction ability.

The consumption of herbal teas is increasing as consumers become more appreciative of the health benefits. Herbal tea blends, comprising of two or more plant species, are produced with the intention of improving taste and health effects through synergistic actions. As with foods, cosmetics and pharmaceutical products, quality control of herbal teas is important to ensure safety and efficacy. Chromatography-based techniques that are commonly used in quality control require sample preparation using solvents; thus, they are destructive. In this study, hyperspectral imaging spectroscopy is applied as a fast and non-destructive method for the quality control of herbal tea blends. The technique combines conventional spectroscopy and digital imaging to gather chemical information (spectral data) and visualise spatial distribution of chemical constituents within a matrix. Certified raw materials (Sceletium tortuosum and Cyclopia genistoides) and herbal tea blends were sourced from a local supplier. Hyperspectral images of the raw materials and tea blends were captured separately on a sisuChema SWIR (short wave infrared) hyperspectral pushbroom imaging system. The images were analysed using Evince® multivariate analysis software 2.4.0. Principal component analysis (PCA) revealed 52.9% chemical variation between S. tortuosum and C. genistoides raw materials. Partial least squares-discriminant analysis (PLS-DA) models were developed to predict the plant species present in the blend and determine the relative proportions. Based on pixel classification it was possible to visualise the tea blend constituents as S. tortuosum and C. genistoides and quantitatively predict C. genistoides as the major constituent (> 95%) while S. tortuosum was present in relatively lower amounts (< 5%). The observed predictions are close to the company formulation and thus HSI in tandem with multivariate data analysis tools present a useful alternative in the quality control of herbal products.

The leaves of Catha edulis (Vahl. Endl.), known as Khat, are widely used as a "natural amphetamine" stimulant in Africa and in the Arabian Peninsula. The psychostimulatory effects of the leaves are attributed to the phenylpropylamino alkaloids i.e., cathinone, cathine and norephedrine [1]. The concentrations of these alkaloids depend on leaf maturity and the origin of the plant. Young leaves contain higher levels of the more potent stimulant, cathinone, than their mature counterparts [2], but the maturity level is impossible to determine by inspection once the material is dried and powdered. A rapid method to identify Khat, regardless of the maturity, would be beneficial to forensic environments. In this study, powdered young and mature leaves were differentiated using vibrational spectroscopy, which included mid-infrared (MIR) and near-infrared (NIR) spectroscopy, and hyperspectral imaging (HSI), as well as ultra performance liquid chromatography-mass spectrometry (UPLC-MS), in combination with chemometric data analysis. Powdered Khat samples were classified according to their geographical origin and maturity level by applying principal component analysis (PCA) and orthogonal projection to latent structures-discriminant analysis (OPLS-DA). The OPLS-DA model constructed from the MIR and UPLC-MS data could clearly differentiate young and mature leaves, as reflected by the excellent model statistics (R2Xcum and Q2 cum > 80% and R2Y above 90%) obtained. Similar results were obtained using NIR. Shortwave infrared HIS permitted Khat samples from two distinct geographical regions (Ethiopia and South Africa) to be distinguished with good model statistics (R2Xcum= 0.91 and Q2 cum= 0.92). It was also possible to differentiate the maturity levels (R2Xcum= 0.85 and Q2 cum= 0.80). These models could prove valuable as rapid techniques for identifying confiscated Khat in law enforcement environments.

Ginseng is an herbal medicine that has been highly publicised due to its healing potential. The name 'ginseng' collectively describes several plant species, including Panax ginseng (Asian ginseng), P. quinquefolius (American ginseng), P. pseudoginseng (Pseudoginseng) and Eleutherococcus senticosus (Siberian ginseng), each with different applications in traditional medicine practices [1]. The use of generic names to describe different species leads to interchangeable use or substitution of raw materials. Quality control methods that can differentiate 'ginseng' species based on the chemistry at any stage of the product cycle are important. Vibrational spectroscopy in combination with multivariate data analysis techniques are proposed as quality control methods for the distinction of four 'ginseng' raw materials and the identification of raw material constituents in commercial ginseng products. Certified ginseng reference standards (P. ginseng, P. quinquefolius, P. pseudoginseng and E. senticosus) and commercial products were purchased for the study. Hyperspectral imaging (HSI), mid-infrared (MIR) and near-infrared (NIR) spectroscopy analyses were performed on the powdered material. Principal component analysis (PCA), partial least squares (PLS) and orthogonal projections to latent structures-discriminant analysis OPLS-DA models were developed to investigate chemical variation between the 'ginsengs'. The holistic analysis of ginseng raw materials revealed distinct chemical differences using HSI, MIR and NIR. Eleutherococcus senticosus was most distinctive and separated from the three other Panax species using models with high R2X and Q2 cum values (> 50%). The models predicted that most products contained either P. ginseng or P. quinquefolius. Vibrational spectroscopy in tandem with multivariate data analysis tools provides useful alternative methods for the authentication of ginseng raw materials and commercial products in a fast, easy, cost-effective and non-destructive manner.

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

Propolis is a resinous material produced by honeybees and is mostly composed of beeswax and plant exudates. Propolis is an important therapeutic and health-promoting agent, and has become very popular due to its wide range of bioactivities. South African propolis has been reported to exhibit anti-oxidant, antimicrobial and anti-inflammatory activities, however, little known about its chemistry. Some studies based on a few random samples showed that South African propolis is similar to propolis produced in the temperate regions. However, at present, there is no comprehensive study available on the chemistry of South African propolis from various provenances. Hence, in this study we developed high performance thin layer chromatography (HPTLC) and liquid chromatography coupled to mass spectrometry (UPLC-ESI-MS) fingerprint and profiles of 39 propolis samples collected from various regions of the country. UPLC-ESI-MS data was chemometrically analysed to observe possible geographical patterns and to compare South African propolis to Brazilian propolis samples (n = 3). The fingerprinting and chemical profiles of South African propolis samples were distinct from Brazilian samples. Fifteen major phenolic acids and flavonols from common South African propolis were identified from UPLC-PDA-qTOF-MS/MS data. Chemometric analysis of the UPLC-ESI-MS data revealed two distinct clusters among the South African samples and also confirmed that the South African propolis was chemically distinct from the Brazilian propolis. The majority of the samples were phytochemically congruent with propolis from the temperate regions.

The quality control of complex herbal medicines is an ongoing process for which simple and rapid analysis methods are required. Hyperspectral imaging (HSI) has been used as a quality control method in the food, agricultural and pharmaceutical industries. HSI acquires both spectral and spatial information through an amalgamation of conventional spectroscopy and imaging. In combination with chemometric analysis, HSI displays compositional differences in an image. As a result, non-destructive analyses can be performed in a much shorter time compared to conventional analysis methods. This study investigated the potential of shortwave infrared (SWIR) hyperspectral imaging and chemometric data analysis as a rapid quality control method for commercially important herbal medicines including; Chinese star anise (Illicium verum), skullcap (Scutellaria laterifolia) and Echinacea spp. The sisuChema SWIR hyperspectral pushbroom imaging system was used to acquire images. Principal component analysis (PCA) was used to investigate compositional differences in the images. Classification models using partial least squares discriminant analysis (PLS-DA) were constructed, optimised and used for prediction of the external datasets. Model 1: toxic Illicium anisatum (Chinese star anise) and Illicium verum (Japanese star anise) (Fig. 1a); Model 2: Echinacea angustifolia, Echinacea pallida and Echinacea purpurea (Fig. 1b); Model 3: Scutellaria laterifolia (Skullcap), Teucrium canadense (American germander) and toxic Teucrium chamaedrys (European germander) (Fig. 1c). The classification models exhibited good R2X_cum and R2Y_cum values and accurately predicted external datasets. Clearly, hyperspectral imaging is ideally suited for the quality control of herbal raw materials as it is a rapid, accurate and non-destructive method with high prediction ability.