A Comprehensive Insight on the Health Benefits and Phytoconstituents of Camellia sinensis and Recent Approaches for Its Quality Control.

Tea, Camellia sinensis, which belongs to the family Theaceae, is a shrub or evergreen tree up to 16 m in height. Green tea is very popular because of its marked health benefits comprising its anticancer, anti-oxidant, and antimicrobial activities, as well as its effectiveness in reducing body weight. Additionally, it was recognized by Chinese people as an effective traditional drink required for the prophylaxis against many health ailments. This is due to the complex chemical composition of green tea, which comprises different classes of chemical compounds, such as polyphenols, alkaloids, proteins, minerals, vitamins, amino acids, and others. The beneficial health effects of green tea ultimately led to its great consumption and increase its liability to be adulterated by either low-quality or non-green tea products with concomitant decrease in activity. Thus, in this review, green tea was selected to highlight its health benefits and phytoconstituents, as well as recent approaches for its quality-control monitoring that guarantee its incorporation in many pharmaceutical industries. More research is needed to find out other more biological activities, active constituents, and other simple and cheap techniques for its quality assurance that ascertain the prevention of its adulteration.

Authentication and discrimination of green tea samples using UV-vis, FTIR and HPLC techniques coupled with chemometrics analysis.

Green tea is a popular beverage consumed worldwide. Its quality should be controlled adequately as the quality is influenced by several factors in addition to adulterations. This study aimed to develop a simple method for assessing the quality of green tea samples obtained from the South and the East Asian regions. The UV-vis, FTIR and HPLC data from 38 samples were subjected to multivariate analyses using the unsupervised recognition techniques comprising Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA). The model for their authentication was constructed and validated by applying the supervised recognition techniques as Soft Independent Modeling of Class Analogy (SIMCA) and Partial Least Square Discriminant Analysis (PLS-DA). The percentages of caffeine in the identified samples were determined using a validated HPLC assay in addition to in vitro determination of their antioxidant activity using DPPH radical-scavenging capacity assay. HCA and PCA based on UV data successfully distributed the tested samples into informative clusters. However, that obtained from visible data could only differentiate samples with respect to their powdered condition. On the contrary, PCA from FTIR and HPLC data could hardly discriminate any of the samples. The models constructed using SIMCA and PLS-DA showed a good class separation between the South and the East Asian samples. The percentages of caffeine in the identified samples and the IC50 in DPPH assay are greatly diverse among all the tested samples. Thus, UV spectroscopy and chemometrics have provided a simple and quick tool for the quality control of commercial green tea samples.

Authentication of monofloral Yemeni Sidr honey using ultraviolet spectroscopy and chemometric analysis.

This work describes a simple model developed for the authentication of monofloral Yemeni Sidr honey using UV spectroscopy together with chemometric techniques of hierarchical cluster analysis (HCA), principal component analysis (PCA), and soft independent modeling of class analogy (SIMCA). The model was constructed using 13 genuine Sidr honey samples and challenged with 25 honey samples of different botanical origins. HCA and PCA were successfully able to present a preliminary clustering pattern to segregate the genuine Sidr samples from the lower priced local polyfloral and non-Sidr samples. The SIMCA model presented a clear demarcation of the samples and was used to identify genuine Sidr honey samples as well as detect admixture with lower priced polyfloral honey by detection limits >10%. The constructed model presents a simple and efficient method of analysis and may serve as a basis for the authentication of other honey types worldwide.

A modern approach to the authentication and quality assessment of thyme using UV spectroscopy and chemometric analysis.

INTRODUCTION: Recently, the fields of chemometrics and multivariate analysis have been widely implemented in the quality control of herbal drugs to produce precise results, which is crucial in the field of medicine. Thyme represents an essential medicinal herb that is constantly adulterated due to its resemblance to many other plants with similar organoleptic properties. OBJECTIVE: To establish a simple model for the quality assessment of Thymus species using UV spectroscopy together with known chemometric techniques. The success of this model may also serve as a technique for the quality control of other herbal drugs. MATERIALS AND METHODS: The model was constructed using 30 samples of authenticated Thymus vulgaris and challenged with 20 samples of different botanical origins. The methanolic extracts of all samples were assessed using UV spectroscopy together with chemometric techniques: principal component analysis (PCA), soft independent modeling of class analogy (SIMCA) and hierarchical cluster analysis (HCA). RESULTS: The model was able to discriminate T. vulgaris from other Thymus, Satureja, Origanum, Plectranthus and Eriocephalus species, all traded in the Egyptian market as different types of thyme. The model was also able to classify closely related species in clusters using PCA and HCA. The model was finally used to classify 12 commercial thyme varieties into clusters of species incorporated in the model as thyme or non-thyme. CONCLUSION: The model constructed is highly recommended as a simple and efficient method for distinguishing T. vulgaris from other related species as well as the classification of marketed herbs as thyme or non-thyme.

Application of chemometrics in authentication of herbal medicines: a review.

INTRODUCTION: Herbal medicines (HM) and their preparations have been widely used for hundreds of years all over the world. However, they have not been officially recognised due to a lack of adequate or accepted research methodology for their evaluation. OBJECTIVE: To present a concise overview of the recent applications of chemometrics in solving the ambiguity of herbal medicine authentication during the last two decades. METHODOLOGY: Studies involving the applications of chemometric analysis in combination with different analytical methods were classified according to the method of analysis used including chromatographic (HPLC, GC and CE), spectroscopic (NMR, IR, UV and ICP) and genetic analysis (RAPD). The purpose of each of these studies was classified into one of three main categories: taxonomic discrimination, quality assessment or classification between plants of different geographic origins. RESULTS: This review comprises over 150 studies, covering the past two decades, emphasising the significance of chemometric methods in the discrimination of many herbs from closely related species and from adulterants, based on the principal bioactive components and phytochemical diversity. Furthermore, the differentiation between varieties and hybrids was achieved in addition to the prediction of the active components by quantitative methods of analysis. Discrimination according to geographical origin and localities, processing methods, DNA profiling and metabolomics were also efficiently investigated. CONCLUSION: Chemometric methods have provided an efficient and powerful tool for the quality control and authentication of different herbs.