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1.
Phytochem Anal ; 33(2): 320-330, 2022 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-34708476

RESUMO

INTRODUCTION: Traditional herbal medicines are mostly composed of more than one herb which act synergistically; hence, there is high demand for proper quality control methods to ensure the consistent quality of polyherbal formulations. AIMS: Proposing a simple, reliable, and efficient method for the qualitative and quantitative analysis of a polyherbal product using multivariate analysis of ultraviolet-visible (UV-Vis) spectroscopy or HPLC-PDA data. METHODOLOGY: An antiobesity formula consisting of equal proportions of Trachyspermum ammi, Cuminum cyminum, and Origanum majorana was prepared as well as spiked with one of each herb simultaneously, representing accepted and unaccepted samples. Full factorial design (2k ) was applied to study the effect of temperature, sonication, and stirring time for extraction optimisation. The HPLC and UV spectral fingerprints were separately subjected to multivariate analysis. The soft independent modelling of class analogy (SIMCA) and partial least squares (PLS) models were developed to segregate the accepted from the unaccepted samples and to predict the herbal composition in addition to the thymol content in each sample. RESULTS: The SIMCAuv and SIMCAhplc models showed correct discrimination between the accepted and unaccepted samples with excellent selectivity and sensitivity. The PLSuv , PLShplc , and PLSthym models showed excellent linearity and accuracy with R2  > 0.98, slope close to 1, intercept close to 0, low root mean square error of calibration (RMSEC), and root mean square error of prediction (RMSEP) (close to 0). On validation, the PLS models correctly predicted the quantity of the three herbs and thymol content with ±5% accuracy. CONCLUSION: This study demonstrates the reliability and efficiency of HPLC and UV spectroscopy coupled with multivariate statistical analysis (MVA) for ensuring the consistency of polyherbal preparations.


Assuntos
Cromatografia Líquida de Alta Pressão , Cromatografia Líquida de Alta Pressão/métodos , Análise dos Mínimos Quadrados , Análise Multivariada , Controle de Qualidade , Reprodutibilidade dos Testes
2.
Saudi J Biol Sci ; 25(2): 377-382, 2018 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-29472794

RESUMO

This study aims at distinguishing honey based on botanical and geographical sources. Different floral honey samples were collected from diverse geographical locations of Saudi Arabia. UV spectroscopy in combination with chemometric analysis including Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA), and Soft Independent Modeling of Class Analogy (SIMCA) were used to classify honey samples. HCA and PCA presented the initial clustering pattern to differentiate between botanical as well as geographical sources. The SIMCA model clearly separated the Ziziphus sp. and other monofloral honey samples based on different locations and botanical sources. The results successfully discriminated the honey samples of different botanical and geographical sources validating the segregation observed using few physicochemical parameters that are regularly used for discrimination.

3.
J Agric Food Chem ; 61(32): 7722-9, 2013 Aug 14.
Artigo em Inglês | MEDLINE | ID: mdl-23837891

RESUMO

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.


Assuntos
Contaminação de Alimentos/análise , Mel/análise , Espectrofotometria Ultravioleta/métodos , Análise Discriminante , Análise de Componente Principal , Iêmen
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