Detecting the Bitterness of Milk-Protein-Derived Peptides Using an Electronic Tongue

• Published in: Chemosensors Vol. 10; no. 6; p. 215
• Main Authors: Nath, Arijit, Eren, Burak Atilla, Zinia Zaukuu, John-Lewis, Koris, András, Pásztorné-Huszár, Klára, Szerdahelyi, Em?ke, Kovacs, Zoltan
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.06.2022
• Subjects: Amino acids; Analysis; Bioavailability; Bitterness; correlative analysis of bitterness; Cow's milk; Discriminant analysis; Electronic equipment and supplies; electronic tongue; Electronic tongues; enzymatic hydrolysis; Enzymes; Evaluation; Experiments; Field effect transistors; Food industry; Glucose; Heat exchangers; Heat treatment; Hydrolysis; Methods; microbial hydrolysis; Microorganisms; Milk; Milk proteins; milk-protein-derived peptides; Peptides; Principal components analysis; Proteins; Quinine; Semiconductor devices; Sensor arrays; Sensors; Software; Stainless steel; Trypsin; Voltammetry; Hungary; Germany
• ISSN: 2227-9040; 2227-9040
• DOI: 10.3390/chemosensors10060215

Bitterness is a considerable limiting factor for the application of bioactive peptides in the food industry. The objective of this study was to compare the level of bitterness of milk-protein-derived peptides using an electronic tongue (E-tongue). Liquid milk protein concentrate (LMPC) was prepared from ultra-heat-treated skimmed cow’s milk. It was initially hydrolyzed with different concentrations of trypsin, namely, 0.008 g·L−1, 0.016 g·L−1 and 0.032 g·L−1. In a later exercise, tryptic-hydrolyzed LMPC (LMPC-T) was further hydrolyzed using Lactobacillus bulgaricus and Streptococcus thermophilus. The effect of glucose in microbial hydrolysis was studied. The bitterness of peptides was evaluated with respect to quinine, a standard bittering agent. The level of bitterness of the peptides after microbial hydrolysis of LMPC-T (LMPC-T-F and LMPC-T-FG) was evaluated using a potentiometric E-tongue equipped with a sensor array that had seven chemically modified field-effect transistor sensors. The results of the measurements were evaluated using principal component analysis (PCA), and subsequently, a classification of the models was built using the linear discriminant analysis (LDA) method. The bitterness of peptides in LMPC-T-F and LMPC-T-FG was increased with the increase in the concentration of trypsin. The bitterness of peptides was reduced in LMPC-T-FG compared with LMPC-T-F. The potential application of the E-tongue using a standard model solution with quinine was shown to follow the bitterness of peptides.