Application of electronic tongue for distinguishing coffee samples and predicting sensory attributes

Abstract

Efforts have been made to predict the sensory profile of coffee samples by instrumental measurement results. The objective of the work was to evaluate the most important sensory attributes of coffee samples prepared from ground roasted coffee by electronic tongue and by sensory panel. Further aim was to predict the Arabica concentration and the main sensory attributes of the different coffee blends by electronic tongue and to analyze the sensitivity of the electronic tongue to the detection of poor quality coffee samples. Five coffee blends with known Arabica and Robusta concentration ratio, five commercially available coffee blends and a poor quality coffee were analyzed. The electronic tongue distinguished the coffee samples according to the Arabica and Robusta content. The sensory panel was able to discriminate the samples based on global aroma, bitterness and coffee aroma intensity (p < 0.01). The Arabica concentration was predicted from the electronic tongue results by PLS with close correlation and low prediction error. Models were developed to predict sensory attributes of the tested coffee samples from the results obtained by the electronic instrument.

Vision system and electronic tongue application to detect coffee adulteration with barley

“…This phenomenon was observed in case of our previous experiments (VÁRVÖLGYI et al, 2012), when the sample points of 100% A (Arabica) and those of 75% A-25% R were close to each other. Hence, LDA is applied to classify adulterated samples.…”

“…Considering the authentication and thus especially the analysis of coffee as well as the usage of potentiometric sensors, most of the analysis are accomplished to classify different beverages (LEGIN et al, 1997) or to obtain sensory profi les of coffee samples (TOKO, 1998). The possibility to detect adulteration by electronic tongue was tested on wine (PARRA et al, 2006;STÓJ, 2011) and on cherry tomato juices (HONG et al, 2014) However, a lack of analysis to confi rm authentication of coffee is observed using ISFET sensors although the ability to discriminate coffee blends with different Arabica-Robusta ratios was tested successfully (VÁRVÖLGYI et al, 2012;SOÓS et al, 2013). Hence, the objective of this investigation is to establish an optical method and to extend the application of the electronic tongue for the detection of fraudulent barley in coffee.…”