This study aims to verify the potential of proton nuclear magnetic resonance (1H‐NMR) combined with partial least square regression to determine the composition of herbal mixtures. NMR one‐dimensional nuclear Overhauser effect spectroscopy (1D‐NOESY) spectra were analyzed to extract significant information from the raw data. The best performing model included four factors explaining 88.70 and 83.77% of the total variance in X and Y, respectively. These promising results have laid the basis for further development of the method, useful also for the analysis of commercial herbal infusions.

HR‐1H NMR spectroscopy and multivariate statistical analysis to determine the composition of herbal mixtures for infusions / Marchetti, Lucia; Rossi, Maria Cecilia; Pellati, Federica; Benvenuti, Stefania; Bertelli, Davide. - In: PHYTOCHEMICAL ANALYSIS (ONLINE). - ISSN 1099-1565. - 32:(2021), pp. 544-553. [10.1002/pca.3002]

HR‐1H NMR spectroscopy and multivariate statistical analysis to determine the composition of herbal mixtures for infusions

Lucia Marchetti;Maria Cecilia Rossi;Federica Pellati;Stefania Benvenuti;Davide Bertelli
2021

Abstract

This study aims to verify the potential of proton nuclear magnetic resonance (1H‐NMR) combined with partial least square regression to determine the composition of herbal mixtures. NMR one‐dimensional nuclear Overhauser effect spectroscopy (1D‐NOESY) spectra were analyzed to extract significant information from the raw data. The best performing model included four factors explaining 88.70 and 83.77% of the total variance in X and Y, respectively. These promising results have laid the basis for further development of the method, useful also for the analysis of commercial herbal infusions.
14-ott-2020
32
544
553
HR‐1H NMR spectroscopy and multivariate statistical analysis to determine the composition of herbal mixtures for infusions / Marchetti, Lucia; Rossi, Maria Cecilia; Pellati, Federica; Benvenuti, Stefania; Bertelli, Davide. - In: PHYTOCHEMICAL ANALYSIS (ONLINE). - ISSN 1099-1565. - 32:(2021), pp. 544-553. [10.1002/pca.3002]
Marchetti, Lucia; Rossi, Maria Cecilia; Pellati, Federica; Benvenuti, Stefania; Bertelli, Davide
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11380/1212160
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