Your browser doesn't support javascript.
loading
Application of FT-IR spectroscopy and chemometric technique for the identification of three different parts of Camellia nitidissima and discrimination of its authenticated product.
Tew, Wan Yin; Ying, Chen; Wujun, Zhang; Baocai, Liu; Yoon, Tiem Leong; Yam, Mun Fei; Jingying, Chen.
Afiliación
  • Tew WY; Research Center for Medicinal Plant, Institute of Agricultural Bio-resource, Fujian Academy of Agricultural Sciences, Fuzhou, China.
  • Ying C; School of Pharmaceutical Sciences, Universiti Sains Malaysia, Gelugor, Malaysia.
  • Wujun Z; Research Center for Medicinal Plant, Institute of Agricultural Bio-resource, Fujian Academy of Agricultural Sciences, Fuzhou, China.
  • Baocai L; School of Chinese MateriaMedica, Beijing University of Chinese Medicine, Beijing, China.
  • Yoon TL; Research Center for Medicinal Plant, Institute of Agricultural Bio-resource, Fujian Academy of Agricultural Sciences, Fuzhou, China.
  • Yam MF; Research Center for Medicinal Plant, Institute of Agricultural Bio-resource, Fujian Academy of Agricultural Sciences, Fuzhou, China.
  • Jingying C; School of Physics, Universiti Sains Malaysia, Gelugor, Malaysia.
Front Pharmacol ; 13: 931203, 2022.
Article en En | MEDLINE | ID: mdl-36238551
Camellia nitidissima C.W. Chi is a golden camellia recognized in Chinese herbology and widely used as tea and essential oil in Chinese communities. Due to its diverse pharmacological properties, it can be used to treat various diseases. However, unethical sellers adulterated the flower with other parts of Camellia nitidissima in their product. This study used an integrated tri-step infrared spectroscopy method and a chemometric approach to distinguish C. nitidissima's flowers, leaves, and seeds. The three different parts of C. nitidissima were well distinguished using Fourier transform infrared spectroscopy (FT-IR), second-derivative infrared (SD-IR) spectra, and two-dimensional correlation infrared (2D-IR) spectra. The FT-IR and SD-IR spectra of the samples were subjected to principal component analysis (PCA), PCA-class, and orthogonal partial least square discriminant analysis (OPLS-DA) for classification and discrimination studies. The three parts of C. nitidissima were well separated and discriminated by PCA and OPLS-DA. The PCA-class model's sensitivity, accuracy, and specificity were all >94%, indicating that PCA-class is the good model. In addition, the RMSEE, RMSEP, and RMSECV values for the OPLS-DA model were low, and the model's sensitivity, accuracy, and specificity were all 100%, showing that it is the excellent one. In addition, PCA-class and OPLS-DA obtained scores of 27/32 and 26/32, respectively, for detecting adulterated and other TCM reference flower samples from C. nitidissima. Combining an infrared spectroscopic method with a chemometric approach proved that it is possible to differentiate distinct sections of C. nitidissima and discriminate adulterated samples of C.nitidissima flower.
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Front Pharmacol Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Front Pharmacol Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza