DIFFERENTIATION OF ARABICA COFFEE GENOTYPES BY THE RAMAM SPECTROSCOPY METHOD

Coffee has great worldwide economic importance. It is estimated that between 75 and 125 million people are connected to the coffee sector and that the global coffee consumption is approximately 155 million 60/kg bags per year. The specialty coffee segment has been prominent in the international market. While the regular coffee market increases 2% a year, the specialty coffee segment increases between 10% and 15% annually. The objective of this study was to evaluate the use of Raman spectroscopy to identify the genotype of green coffee beans. We evaluated two genotypes of Arabic coffee (Coffea arabica L.). The harvest was selected using a wet process method, being one cultivar of the Mundo Novo genotype and three cultivars of the Bourbon genotype. Raman spectra of the samples were obtained using a FT-Raman RFS/100 spectrometer in the spectral range of 3500-400cm־¹. In parallel, sensory analysis was performed according to SCA scores on a scale of 10 points. The data were treated using chemometric tools of unsupervised classification (principal component analysis, PCA), and supervised analysis (partial least squares-discriminant analysis PLS-DA). It was possible to notice the discrimination between coffee genotypes analyzed with PCA through the spectral differences in the bands that are characteristic of fatty acids and kahweol. The discriminant analysis by (PLS-DA) performed to discriminate the Mundo Novo (G1) and Bourbon (G2, G3 and G4) samples was efficient, separating them into groups. Discrimination between coffee genotypes is interesting once the Bourbons, due to their potential for producing specialty coffees, have a higher added value in the market. Thus, a methodology for discriminating genotypes is relevant to avoid fraud.