Prediction of the bitterness of single, binary- and multiple-component amino acid solutions using a taste sensor

The purpose of this study was to develop a quick, quantitative, prediction method for the determination of the bitterness of solutions containing one or more of five amino acids ( l-isoleucine, l-leucine, l-valine, l-phenylalanine, and l-tryptophan), using an artificial taste sensor. The bitterness of various solutions containing different concentrations (1, 3, 10, 30, and 100 mM) of five amino acids, singly and in combination, was estimated using a multichannel taste sensor and compared with the results of human gustatory sensation tests with nine volunteers. The relative response electric potential patterns were similar for all five amino acids. Large sensor outputs were observed in channels 1–4 (which are negatively charged) while there were no responses in channels 5–8 (positively charged). The sensor output for channel 1, which was the largest output value, was used for prediction of bitterness. The change of membrane potential caused by adsorption (CPA), which corresponds to aftertaste, could not be used as an explanatory variable since the adsorption of the amino acids to the sensor membrane was weak and CPA values were small. The bitterness intensity scores for single, binary, and multi-component amino acid solutions, could be easily predicted on the basis of the sensor output value of channel 1 using regression analysis. Principal component analysis of the sensor output data suggested that the sourness, astringency and/or smell of the solutions also played a role in the perception of bitterness.