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Chemometric comparison of almond oxidation rates using kinetic parameters obtained by infrared spectroscopy.

Iván P Román FalcóMaría Soledad Prats MoyaSalvador E Maestre PérezMaria L Martín CarrataláNuria Grané Teruel
Published in: Journal of the science of food and agriculture (2020)
Kinetic coefficients and induction times were easily obtained as the absorbance values (from difference spectra) fitted to pseudo-first-order kinetics after the induction time. Principal component analysis was applied to the kinetic parameters to visualize which variables could be useful to classify the almond cultivars based on their resistance to thermal oxidation processes. It was found that selecting only the induction times corresponding to the bands 3470, 3006, 1630 and 970 cm-1 a separate classification of the Californian cultivars from the Spanish ones was possible. Finally, a linear discriminant analysis was assayed using only the four induction times previously selected. Validated classification and correct in 100% of the cases was obtained for all the samples based on their Spanish or Californian origin. © 2020 Society of Chemical Industry.
Keyphrases
  • machine learning
  • deep learning
  • hydrogen peroxide