Exploring the relationships between perceived umami intensity, umami components and electronic tongue responses in food matrices.

Umami intensity promotes food flavor blending and food choice, while a universal quantification procedure is still lacking. To evaluate perceived umami intensity (PUI) in seven categories of foods, modified two-alternative forced choice (2-AFC) method with monosodium glutamate as reference was applied. Meanwhile, we explored whether equivalent umami concentration (EUC) by chemical analysis and electronic tongue (E-tongue) are applicable in PUI quantification. The results indicated that EUC was appropriate in quantifying PUI of samples from meat, dairy, vegetable and mushroom groups (r = 1.00, p < 0.05). Moreover, models with a good prediction capacity for PUI and EUC (R > 0.99) were established in separated food categories by back propagation neural networks, where E-tongue data were set as input. This study explored the effectiveness of the three methods in evaluating the PUIs of various foods, which provides multiple choices for the food industry.