An index to evaluate the acceptance of specialty coffees in consumer groups

Abstract

Numerous factors are related to the individual sensory perception of consumers, which makes it impossible to adapt a model that explains their behavior. In this context and given the scarcity of statistical indexes that evaluate preferences for specialty coffees, new statistical methods should be studied. To this end, our study aimed to create an index that measures the acceptance of specialty coffees. The index was built considering the fit of regression models as a function of principal component scores. Validation was done by significance tests, whose probabilities were obtained by bootstrapping, considering the main measures used in diagnosing outliers as weights, with application to real data from different consumer groups. The coffee varieties Acaia and Bourbon were discriminated in relation to altitude. In conclusion, the index was adequate for the analysis and characterization of specialty coffees grown at different altitudes.