Exploratory and discriminative studies of commercial processed Brazilian coffees with different degrees of roasting and decaffeinated - Teófilo, Reinaldo Francisco; Ribeiro, Juliano Souza; Salva, Terezinha de Jesus Garcia; Augusto, Fabio; Ferreira, Marcia Miguel Castro (Brazilian Journal of Food Technology, 2013)
The fingerprints of the volatile compounds of 21 commercial Brazilian coffee samples submitted to different industrial processing i.e. decaffeinated or different roasting degrees (traditional and dark) were studied. The volatiles were collected by headspace solid phase microextraction (HS-SPME) and analyzed by GC-FID and GC-MS. The chromatographic data matrices (fingerprints) obtained were explored by the principal component analysis (PCA) and partial least squares – discriminative analysis (PLS-DA). Initially the chromatographic profiles were aligned by the algorithm correlation optimized warping (COW). The PCA showed the discrimination of the decaffeinated coffees from the others with both the SPME fibres used. This separation probably occurred due to the loss of some volatile precursors during the decaffeination process, such as sucrose. For both the fibres tested, PDMS/DVB and CX / PDMS SPME, the PLS-DA models correctly classified 100% of the samples according to their roasting degree: (medium and dark), the main differences being the concentrations of some of the volatile compounds such as 2-methyl furan, 2-methylbutanal, 2,3-pentanedione, pyrazine, 2-carboxyaldehyde pyrrole, furfural and 2-furanmethanol.

Neste trabalho, foram estudados os perfis cromatográficos dos compostos voláteis de 21 amostras de cafés comerciais brasileiros submetidos a diferentes processos industriais, i.e., descafeinados e com diferentes graus de torra (médio e extraforte). Os voláteis foram coletados por microextração em fase sólida (HS-SPME) e analisados por GC-FID e GC-MS. As matrizes de dados cromatográficos (perfis) obtidas, a partir dessas análises, foram exploradas por análise de componentes principais (PCA) e análise discriminante por quadrados mínimos parciais (PLS-DA). Inicialmente, os dados cromatográficos foram alinhados utilizando-se o algorítimo correlation optimized warping (COW). A PCA demonstrou a diferenciação dos cafés descafeinados em relação às outras classes de café, com ambas as fibras de SPME utilizadas. Essa separação, provavelmente, ocorreu em razão do desaparecimento de algumas espécies precursoras de voláteis durante o processo de descafeinação, tal como sacarose. Os modelos PLS-DA, para ambas as fibras testadas, PDMS/DVB e CX/PDMS, classificaram corretamente 100% das amostras, de acordo com o grau de torra (médio e extraforte); a principal diferença entre as classes foi a diferença de concentração de alguns compostos voláteis, tais como 2-metilfurano, 2-metilbutanal, 2,3-pentanodiona, pirazina, 2-pirrol carboxaldeído, furfural e 2-furan metanol.
Keywords: Processed coffee; Solid Phase Microextraction (SPME); Correlation optimized warping; Principal component analysis; Partial least squares – discriminative analysis