Current Research in Food Science (Jan 2022)

Origin geographical classification of green coffee beans (Coffea arabica L.) produced in different regions of the Minas Gerais state by FT-MIR and chemometric

  • Geissy de Azevedo Mendes,
  • Marcone Augusto Leal de Oliveira,
  • Mirian Pereira Rodarte,
  • Virgílio de Carvalho dos Anjos,
  • Maria Jose Valenzuela Bell

Journal volume & issue
Vol. 5
pp. 298 – 305

Abstract

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The present work was proposal the potential evaluation of Fourier-Transform Mid-Infrared (FT-MIR) associated with chemometric approach in green beans, in order to discriminate the origin of special Arabica coffees in a single state that has heterogeneous environments. Partial Least Squares Discriminant Analysis (PLS-DA) model presented as result: 3 latent variables, R2X (cum) = 0.892, R2Y (cum) = 0.659; Q2Y (cum) = 0.494, RMSEP = 0.182387, p-value CV-Anova = 0.009, 100% of both sensitivity and specificity and the prediction classification obtained was: 100, 83.33, 100, 83.33% for class 1, class 2, class 3 and class 4, respectively. These results can be considered adequate for the proposed hypothesis. The obtained results that the regions have markers such as trigonelline, chlorogenic and fatty acids, sensitive to absorption in the mid-infrared and that are able to determine the origin of green coffee beans of Arabica. Thus, the FT-MIR associated with chemometrics has the potential to employ speed, modernity and cost reduction in the certification of origin of coffees.

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