Coffea arabica (arabica) and Coffea canephora (robusta) are the most important coffee species. Arabica has higher commercial value and, in general, more favorable sensory characteristics. After roasting, analytical methods are required to differentiate species. Blends with different proportions of arabica/robusta coffees, roasted at three degrees were studied. Color parameters and the levels of chlorogenic (5-CQA) and nicotinic acids, caffeine, and trigonelline were evaluated. Hydrosoluble compounds were analyzed by their efficiency to discriminate coffee species, considering different roast degrees. Caffeine was a good discriminator, regardless of roast degree. The roast degree influenced the efficiency of discrimination of the other hydrosoluble compounds. A model using color parameters and the variables Ratio (5-CQA/caffeine contents ratio) and Sum (sum of nicotinic acid and trigonelline contents) was proposed to the estimation of roasting degree. Considering the use of heat-labile compounds, the discrimination among coffee species should be carried out in two steps: first, the characterization of roasting degree, and subsequently the appropriate parameters are defined for each roasting degree. Thus, the combined use of color parameters and hydrosoluble compounds could be useful to help the differentiation of coffee species in blends of roasted samples. OPEN ACCESSBeverages 2015, 1 128

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A reverse phase high-performance liquid chromatography (HPLC) method was developed for the simultaneous quantification of kahweol and cafestol in tissues of fresh fruits, leaves, and roasted coffee beans. The best resolution was obtained with isocratic elution of acetonitrile/water (55/45% v/v) and UV detection. A single sample preparation method carried out by direct saponification and extraction with organic solvent was standardized for all matrices. Good recovery (average of 99% for kahweol and 94% for cafestol), repeatability, and linearity were obtained. Detection limits of 2.3 and 3.0 mg/100 g were observed for kahweol and cafestol. The HPLC method was effective in quantifying these diterpenes in the different coffee matrices. The endosperm and perisperm of Coffea arabica cv. IAPAR 59 showed elevated amounts of kahweol as compared to the pericarp and leaves. On the other hand, cafestol was detected in all samples except in leaves from Coffea canephora cv. Apoatā.

Chemical analyses and sensory evaluation are the most applied methods for quality control of roasted and ground coffee (RG). However, faster alternatives would be highly valuable. Here, we applied infrared-photoacoustic spectroscopy (FTIR-PAS) on RG powder. Mixtures of specific defective beans were blended with healthy (defect-free) Coffea arabica and Coffea canephora bases in specific ratios, forming different classes of blends. Principal Component Analysis allowed predicting the amount/fraction and nature of the defects in blends while partial Least Squares Discriminant Analysis revealed similarities between blends (=samples). A successful predictive model was obtained using six classes of blends. The model could classify 100% of the samples into four classes. The specificities were higher than 0.9. Application of FTIR-PAS on RG coffee to characterize and classify blends has shown to be an accurate, easy, quick and "green" alternative to current methods.