EVALUATION OF THE COMPOSITION EFFECT OF HARVESTED COFFEE IN THE ORGANOLEPTIC PROPERTIES OF COFFEE DRINK
DOI:
https://doi.org/10.17533/udea.vitae.v24n1a06Keywords:
Coffea arabica, wet processing, coffee ripeness stages, specialty coffees, fuzzy logic.Abstract
Background: The current flourishing of the specialty coffee market has motivated the development of this research on the basis that the harvested coffee fruits are a determining factor in drink quality. Objectives: The aim of this study was to evaluate the effect of the composition of harvested coffee (Coffea arabica L.) regarding the organoleptic quality of the coffee drink for the varieties Caturra and Colombia. Methods: Treatments for the assessed varieties were defined with different percentage compositions of coffee fruits M1 (100R), M2 (80R, 13OV, 7SR), M3 (60R, 26OV, 12SR, 2UR) and the control M4, which included fruits in different ripening stages, ripe (R), overripe (OV), semi-ripe (SR) and unripe (UR), in different proportions in experimental units of 10 kg of harvested coffee. The experimental design envisaged 3 rounds (repetitions) of harvest. The harvested coffee was classified manually according to its ripening stage using a previously developed scale based on colorimetry and recording the degrees Brix of 50 fruits in each ripening stage. The standardized wet processing method was carried out; a Q Grader cupping panel of five members was used for the sensory analysis of the coffee drink. Results: The results showed that for the variety Caturra statistical differences in cup quality between treatments were not found, whereas for the variety Colombia, treatments M1 and M3 showed similar behavior, with statistically significant differences regarding M2 and M4. Finally, the mathematical modeling obtained to predict the cup score depending on the coffee ripening stages composition, counted with coefficients of determination R2 of 0.833 and 0.852 with an error of 1.85 and 1.03% for the varieties Caturra and Colombia, respectively. Conclusions: The model developed with fuzzy logic and validated with information from other farms, presented an error of less than 2% in the estimation of the cup as a function of the ripening stages composition of the coffee varieties Caturra and Colombia.
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