Discrimination and geographical origin prediction of washed specialty Bourbon coffee from different coffee growing areas in Rwanda by using electronic nose and electronic tongue

Abstract

The study aimed at discriminating washed specialty Bourbon coffee from major coffee growing areas in Rwanda and evaluating the feasibility of using flavor to predict the geographical origin of Arabica coffees from different origins. Discrimination was achieved by performing a principal component analysis, and a discriminant factorial analysis (DFA) model was used to predict the geographical origin of coffee samples based on their intrinsic flavor. Discrimination results from both e-nose and e-tongue indicated clear grouping of coffee samples from areas within the same geographical sub-regions. A DFA model using e-nose was successful in predicting the geographical origin of coffee samples but not with e-tongue. Therefore, the study demonstrated that aroma could reliably be used to predict the geographical origin of coffee samples from different origins than their taste profile.