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Multi-wavelength high-performance liquid chromatographic fingerprints and chemometrics to predict the antioxidant activity of Turnera diffusa as part of its quality control

Tipo de material: TextoTextoSeries ; Journal of Chromatography A, 23(7), p.10275-10287, 2021Trabajos contenidos:
  • Lucio-Gutiérrez, J. Ricardo
  • Garza-Juárez, Aurora
  • Coello, J
  • Maspocha, S
  • Salazar-Cavazos, M.L
  • Salazar-Aranda, Ricardo
  • Waksman De Torres, Noemi
Tema(s): Recursos en línea: Resumen: The determination of the antioxidant activity of Turnera diffusa using partial least squares regression (PLSR)on chromatographic data is presented. The chromatograms were recorded with a diode array detector and, for each sample, an enhanced fingerprint was constructed by compiling into a single data vector the chromatograms at four wavelengths (216, 238, 254 and 345 nm). The wavelengths were selected from a contour plot, in order to obtain the greater number of peaks at each of the wavelengths. A further pretreatment of the data that included baseline correction, scaling and correlation timized warping was performed. Optimal values of the parameters used in the warping were found by means of simplex optimization. A PLSR model with four latent variables (LV)explained 52.5
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Documentos solicitados Documentos solicitados CICY Documento préstamo interbibliotecario Ref1 B-18731 (Browse shelf(Opens below)) Available

The determination of the antioxidant activity of Turnera diffusa using partial least squares regression (PLSR)on chromatographic data is presented. The chromatograms were recorded with a diode array detector and, for each sample, an enhanced fingerprint was constructed by compiling into a single data vector the chromatograms at four wavelengths (216, 238, 254 and 345 nm). The wavelengths were selected from a contour plot, in order to obtain the greater number of peaks at each of the wavelengths. A further pretreatment of the data that included baseline correction, scaling and correlation timized warping was performed. Optimal values of the parameters used in the warping were found by means of simplex optimization. A PLSR model with four latent variables (LV)explained 52.5

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