Metabolite Fingerprinting Based on 1H-NMR Spectroscopy and Liquid Chromatography for the Authentication of Herbal Products

The cluster analysis of traditional Chinese medicine authenticity identification technique assisted by chemometrics

This study explore the authenticity identification technique of traditional Chinese medicine (TCM) using chemometrics in conjunction with cluster analysis. A clustering Gaussian mixture model was constructed and applied for the data clustering analysis of four types of TCM. Chemical measurements combined with discrete wavelet transform (DWT), Fourier transform infrared spectroscopy (FTIR), and Fourier self-deconvolution (FSD) were utilized for the detailed differentiation of Bupleurum scorzonerifolium, Bupleurum yinchowense, Bupleurum marginatum, and Bupleurum smithii Wolff var. parvifolium. Differences in the attenuated total reflection-FTIR (ATR-FTIR) spectra among the four TCMs were observed. Utilizing clustering algorithms, the one-dimensional DWT of the infrared spectra of samples was employed for the authentication of Chinese herbal medicines. The model demonstrates optimal performance throughout 2000 rounds of network training. The accuracy (88.6 %), sensitivity (86.5 %), and specificity (82.7 %) of the model constructed in this study significantly surpassed those of the CNN model: accuracy (67.7 %), sensitivity (70.4 %), and specificity (68.5 %) (P < 0.05). By setting the cluster size K = 5 and the number of Gaussian mixture model components to 5, the model effectively fits the actual number of categories within the dataset. Infrared spectroscopy analysis revealed distinct carbon-oxygen stretching vibration absorption peaks between 1025 and 1200 cm-1 for Bupleurum scorzonerifolium, Bupleurum yinchowense, Bupleurum marginatum, and Bupleurum smithii Wolff var. parvifolium, indicating strong absorption peaks of carbohydrates. A comprehensive structural information analysis revealed a similarity of above 0.982 among the four types of TCM. Combined with chemometrics and intelligent algorithm-based cluster analysis, successful and accurate authentication of TCM authenticity was achieved, providing an effective methodology for quality control in TCM.

Non-Targeted Nuclear Magnetic Resonance Analysis for Food Authenticity: A Comparative Study on Tomato Samples

Non-targeted NMR is widely accepted as a powerful and robust analytical tool for food control. Nevertheless, standardized procedures based on validated methods are still needed when a non-targeted approach is adopted. Interlaboratory comparisons carried out in recent years have demonstrated the statistical equivalence of spectra generated by different instruments when the sample was prepared by the same operator. The present study focused on assessing the reproducibility of NMR spectra of the same matrix when different operators performed individually both the sample preparation and the measurements using their spectrometer. For this purpose, two independent laboratories prepared 63 tomato samples according to a previously optimized procedure and recorded the corresponding 1D 1H NMR spectra. A classification model was built using the spectroscopic fingerprint data delivered by the two laboratories to assess the geographical origin of the tomato samples. The performance of the optimized statistical model was satisfactory, with a 97.62% correct sample classification rate. The results of this work support the suitability of NMR techniques in food control routines even when samples are prepared by different operators by using their equipment in independent laboratories.

Magnetic materials as adsorbents for the pre-concentration and separation of active ingredients from herbal medicine

Herbal medicine (HM) is crucial in disease management and contains complex compounds with few active pharmacological ingredients, presenting challenges in quality control of raw materials and formulations. Effective separation, identification, and analysis of active components are vital for HM efficacy. Traditional methods like liquid-liquid extraction and solid-phase extraction are time-consuming and environmentally concerning, with limitations such as sorbent issues, pressure, and clogging. Magnetic solid-phase extraction uses magnetic sorbents for targeted analyte separation and enrichment, offering rapid, pressure-free separation. However, inorganic magnetic particles' aggregation and oxidation, as well as lack of selectivity, have led to the use of various coatings and modifications to enhance specificity and selectivity for complex herbal samples. This review delves into magnetic composites in HM pretreatment, specifically focusing on encapsulated or modified magnetic nanoparticles and materials like silica, ionic liquids, graphene family derivatives, carbon nanotubes, metal-organic frameworks, covalent organic frameworks, and molecularly imprinted polymers.

Flower Species Ingredient Verification Using Orthogonal Molecular Methods

Flowers are gaining considerable interest among consumers as ingredients in food, beverages, cosmetics, and natural health products. The supply chain trades in multiple forms of botanicals, including fresh whole flowers, which are easier to identify than dried flowers or flowers processed as powdered or liquid extracts. There is a gap in the scientific methods available for the verification of flower species ingredients traded in the supply chains of multiple markets. The objective of this paper is to develop methods for flower species ingredient verification using two orthogonal methods. More specifically, the objectives of this study employed both (1) DNA-based molecular diagnostic methods and (2) NMR metabolite fingerprint methods in the identification of 23 common flower species ingredients. NMR data analysis reveals considerable information on the variation in metabolites present in different flower species, including color variants within species. This study provides a comprehensive comparison of two orthogonal methods for verifying flower species ingredient supply chains to ensure the highest quality products. By thoroughly analyzing the benefits and limitations of each approach, this research offers valuable insights to support quality assurance and improve consumer confidence.

Application of HPLC-UV combined with chemometrics for the detection and quantification of 'true cinnamon' adulteration

Cinnamon is one of the most popular spices used in cuisines worldwide. Among its different species, Ceylon cinnamon ("true cinnamon") is the one with the most health benefits due to its high concentration in the antioxidant eugenol and the ultra-low content of the hepatotoxic compound coumarin. However, the higher price of Ceylon cinnamon makes it vulnerable to fraudulent adulteration with more economic species of cinnamon, such as Cassia and Saigon. Thus, for the detection of frauds in cinnamon samples, a HPLC-UV method was developed for the determination of 4 characteristic cinnamon compounds: eugenol, cinnamaldehyde, coumarin and cinnamic acid. The obtained data were analyzed by PLS to attain not only the authentication of cinnamon species but also the detection and quantification of partial adulterations. Several mixtures prepared in the laboratory using different cinnamon powder samples considered 'pure' Ceylon, Cassia or Saigon were tested, concluding that the proposed approach allows a clear identification of Ceylon cinnamon and a suitable quantification of the Ceylon: non-Ceylon ratio regardless of the commercial sample selected (RMSE <0.06 for both training and test sets).

Classification and Authentication of Lonicerae Japonicae Flos and Lonicerae Flos by Using 1H-NMR Spectroscopy and Chemical Pattern Recognition Analysis

Lonicerae japonicae flos and Lonicerae flos are increasingly widely used in food and traditional medicine products around the world. Due to their high demand and similar appearance, they are often used in a confused or adulterated way; therefore, a rapid and comprehensive analytical method is highly required. In this case, the comparative analysis of a total of 100 samples with different species, growth modes, and processing methods was carried out by nuclear magnetic resonance (1H-NMR) spectroscopy and chemical pattern recognition analysis. The obtained 1H-NMR spectrums were employed by principal component analysis (PCA), partial least-squares discriminant analysis (PLS-DA), orthogonal partial least-squares discriminant analysis (OPLS-DA), and linear discriminant analysis (LDA). Specifically, after the dimensionality reduction of data, linear discriminant analysis (LDA) exhibited good classification abilities for the species, growth modes, and processing methods. It is worth noting that the sample prediction accuracy from the testing set and the cross-validation predictions of the LDA models were higher than 95.65% and 98.1%, respectively. In addition, the results showed that macranthoidin A, macranthoidin B, and dipsacoside B could be considered as the main differential components of Lonicerae japonicae flos and Lonicerae Flos, while secoxyloganin, secologanoside, and sweroside could be responsible for distinguishing cultivated and wild Lonicerae japonicae Flos. Accordingly, 1H-NMR spectroscopy combined with chemical pattern recognition gives a comprehensive overview and provides new insight into the quality control and evaluation of Lonicerae japonicae flos.

Application of Chromatographic and Spectroscopic-Based Methods for Analysis of Omega-3 (ω-3 FAs) and Omega-6 (ω-6 FAs) Fatty Acids in Marine Natural Products

Omega-3 fatty acids v(ω-3 FAs) such as EPA (eicosapentaenoic acid) and DHA (docosahexaenoic acid) and omega-6 fatty acids (ω-6 FAs) such as linoleic acid and arachidonic acid are important fatty acids responsible for positive effects on human health. The main sources of ω-3 FAs and ω-6 FAs are marine-based products, especially fish oils. Some food, supplements, and pharmaceutical products would include fish oils as a source of ω-3 FAs and ω-6 FAs; therefore, the quality assurance of these products is highly required. Some analytical methods mainly based on spectroscopic and chromatographic techniques have been reported. Molecular spectroscopy such as Infrared and Raman parallel to chemometrics has been successfully applied for quantitative analysis of individual and total ω-3 FAs and ω-6 FAs. This spectroscopic technique is typically applied as the alternative method to official methods applying chromatographic methods. Due to the capability to provide the separation of ω-3 FAs and ω-6 FAs from other components in the products, gas and liquid chromatography along with sophisticated detectors such as mass spectrometers are ideal analytical methods offering sensitive and specific results that are suitable for routine quality control.

Multidimensional Chromatographic Fingerprinting Combined with Chemometrics for the Identification of Regulated Plants in Suspicious Plant Food Supplements

The popularity of plant food supplements has seen explosive growth all over the world, making them susceptible to adulteration and fraud. This necessitates a screening approach for the detection of regulated plants in plant food supplements, which are usually composed of complex plant mixtures, thus making the approach not so straightforward. This paper aims to tackle this problem by developing a multidimensional chromatographic fingerprinting method aided by chemometrics. To render more specificity to the chromatogram, a multidimensional fingerprint (absorbance × wavelength × retention time) was considered. This was achieved by selecting several wavelengths through a correlation analysis. The data were recorded using ultra-high-performance liquid chromatography (UHPLC) coupled with diode array detection (DAD). Chemometric modelling was performed by partial least squares-discriminant analysis (PLS-DA) through (a) binary modelling and (b) multiclass modelling. The correct classification rates (ccr%) by cross-validation, modelling, and external test set validation were satisfactory for both approaches, but upon further comparison, binary models were preferred. As a proof of concept, the models were applied to twelve samples for the detection of four regulated plants. Overall, it was revealed that the combination of multidimensional fingerprinting data with chemometrics was feasible for the identification of regulated plants in complex botanical matrices.

Untargeted 1H NMR-based metabolomics and multi-technique data fusion: A promising combined approach for geographical and processing authentication of thyme by multivariate statistical analysis

Thyme is a culinary herb highly susceptible to increasing mislabeling occurring in the spice industry. In this study, proton nuclear magnetic resonance spectroscopy (¹H NMR) combined with multivariate statistics was successfully applied with two authenticity purposes: (1) tracing thyme metabolic differences among three relevant geographical regions (Morocco, Spain, and Poland), and (2) assessing the influence of sterilization processing on the metabolic fingerprint. Multivariate data analysis provided six and seven key geographical and processing markers, respectively, including thymol, organic acids, chlorogenic acid, and some carbohydrates (e.g., sucrose). Additionally, for the first time, a mid-level data fusion approach was tested for thyme authenticity combining three complementary and synergic analytical platforms: gas and liquid chromatography coupled with high-resolution mass spectrometry, and ¹H NMR spectroscopy, providing a comprehensive metabolomics insight into the origin and processing effects on thyme fingerprinting, and opening the path to new metabolomics approaches for quality control in the spice industry.

Quality assessment of African herbal medicine: A systematic review and the way forward

BACKGROUND

In Africa, herbalism supplements allopathic medicine's efforts to ensure Universal Health Coverage attainment. This review was conducted to identify and to summarise current literature on methodological approaches used for quality control of herbal medicines in Africa, to evaluate the gaps associated with existing strategies within context of best practices, and make recommendations for future improvements.

METHODS

A systematic search was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Articles were screened and assessed for eligibility.

RESULTS

118 articles were included into the study. There was a high preference for impurity profiling tests (77%) indicating the prioritization for tests that guarantee safety despite the limited analytical resources available. Other classes of tests reported included identification tests (29%), physicochemical tests (18%), and content assays (12%). Although standard methods exist in preparing samples for impurity tests, different techniques were observed in different studies, and this could lead to differences in analytical outcomes. Content assays focused on single marker assessments, which may be inadequate to comprehensively assess the quality of products.

CONCLUSION

This review provides knowledge of existing strengths and challenges for herbal medicine quality assessments in Africa. For future it is recommended to implement more studies on contaminants (e.g. mycotoxins) and pharmaceutical adulterants. The use of chemometrics to develop analytical methods should be promoted. Also, stakeholders in the medicine quality industry in Africa need to effectively collaborate to establish a well co-ordinated and harmonized system to provide a sustainable framework for the GACP and GMP guided production and quality assurance of herbal medicines.