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FUZZY LOGIC IN THE SPATIAL AND TEMPORAL DISTRIBUTION IN THE QUALITY OF THE BEVERAGE IN CONILON COFFEE
Author(s) -
Abel Souza da Fonseca,
Julião Soares de Souza Lima,
Samuel de Assis Silva,
Maria Christina Junger Delôgo Dardengo,
Alexandre Cândido Xavier
Publication year - 2019
Publication title -
coffee science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.268
H-Index - 15
eISSN - 1984-3909
pISSN - 1809-6875
DOI - 10.25186/cs.v14i2.1563
Subject(s) - mathematics , fuzzy logic , statistics , sweetness , geostatistics , flavor , artificial intelligence , spatial variability , computer science , food science , chemistry
The objective in this study was to evaluate the spatial and temporal variability of the beverage quality by applying the fuzzy classification in the final global sensory analysis, for Coffea canephora Pierre ex A. Froehner, in two consecutive harvests. The studied variables were: fragrance (aroma), flavor, bitterness (sweetness), set, balance, cleaning, aftertaste, mouth feel, uniformity, salinity (acidity) and drink (global note). To the average overall scores of the drinks obtained on the cup-tasting at 80.0 points of a sampling, the mesh has applied the function of association of the fuzzy classification linear model to determine the degree of pertinence. The data were analyzed by the descriptive statistics and then by geostatistics to verify the existence and quantify the degree of spatial dependence of the variables. In the interval classified as “very good coffee” is found in the global average grade, in the two harvests. The methodology fuzzy applied in the global beverage note of the coffee conilon seminal made it possible to determine their spatial variability in the same distribution pattern in the two harvests, close ranges, and adjustments to the spherical model, which was confirmed by the spatial correlation of 61.6% among the fuzzy maps for the global score

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