An interventional study of Hedonic mapping and Ad libitum risotto test meal in Taste Sensitivity, Umami Taste Perception and Food Intake Regulation, sponsored by Wageningen University. Completed at 1 site in Netherlands. Open to participants aged 18 Years to 55 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-02-19.
Sponsored by Wageningen University · Not applicable, Interventional, and Basic science
Sweet and salty tastes can influence food intake. Increased intensity of these tastes has been shown to decrease food intake and increase satiation compared to the less intense taste, independent of palatability. Umami taste intensity has been shown to reduce subsequent food intake, especially when paired with protein content in foods. Taste can be related with nutrient content of the diet, with sweet foods having carbohydrates, salty foods containing sodium, and umami foods containing protein.
However, no study has yet investigated the impact of umami and food intake, using the approach of similar palatability and differing taste intensity levels. Given its relationship with nutrient signaling, it is important to explore the relationship between umami intensity and satiation. Therefore, this study aims to compare ad libitum food intake of two levels with similar palatability and differing umami taste intensities (high and low) to food intake from a meal with optimum taste intensity.
Study population 40-50 healthy, normal weight participants from Wageningen and surroundings will be included. Previous studies have applied this method in sweet and salty tastes with 15-59 participants.
Test session 1: Hedonic mapping Determine individual's most preferred level of umami taste in 6 risotto samples, using pairwise staircase comparison. Samples will contain a fixed level of salt (0.2 w/w%), and MSG concentrations ranging from 0.2-2.1 w/w%. Per individual, The optimal tasting MSG intensity will be selected based on forced choice.
Test session 2, 3 and 4: ad libitum risotto lunch meals In a randomized cross-over design, participants will receive the optimum, high and low MSG risotto. The following will be measured:
Study procedures Subjects will be provided with a standardized breakfast and to not consume anything between breakfast and lunch session. This will be validated upon arrival to the lunch meal. They will also be asked to refrain from eating for one hour after the test session. Participants will be asked to fill in the tasteFFQ, to investigate the link between dietary taste patterns and hedonic umami taste ratings.
Data analysis Data will be analyzed using Rstudio. First, normality will be assessed, and data will be normalized if needed. Difference in food intake in grams between the three intensities will be compared using ANOVA. A post-hoc test will be applied if statistical outcomes are significant. Categorical variables will be compared using Chi-square test.
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Exclusion Criteria:
The low umami intensity meal will have a taste intensity corresponding with a lower than ideal than the MSG concentration in the sample that came out as 'winner' by forced choice during the first test session in which umami taste preferences per individual will be assessed by hedonic mapping (PCA). The palatability ratings of the lower than ideal will correspond to the palatability ratings of the higher than ideal condition.
Other: Hedonic mapping · Other: Ad libitum risotto test meal
The ideal umami intensity meal will have a taste intensity corresponding with the MSG concentration in the sample that came out as 'winner' by forced choice during the first test session in which umami taste preferences per individual will be assessed by hedonic mapping (PCA).
Other: Hedonic mapping · Other: Ad libitum risotto test meal
The high umami intensity meal will have a taste intensity corresponding with a higher than ideal than the MSG concentration in the sample that came out as 'winner' by forced choice during the first test session in which umami taste preferences per individual will be assessed by hedonic mapping (PCA). The palatability ratings of the higher than ideal will correspond to the palatability ratings of the lower than ideal condition.
Other: Hedonic mapping · Other: Ad libitum risotto test meal
During the first session, participants will be presented with 2 risotto samples simultaneously, differing in MSG content and thus umami taste intensity, by PCA. First, samples will be presented in ascending concentration, with the best rated sample (forced choice) from the previous round, and the next concentration. This will be replicated in descending order. Based on these individual outcomes, umami taste intensities of the ad libitum test meals will be calculated per participant.
During the ad libitum test meal, participants will be presented with 1200 grams of risotto with either high-, low-, or optimum umami taste intensity.
Difference in food intake from ad libitum test meal between taste intensity conditions
Difference in food intake in volume (grams) from the ad libitum test meal between the three (high-, low- and ideal) umami taste intensities.
Time frame: Test session 2, 3 and 4 (week 2, 3 and 4)
Difference in test meal liking between taste intensity conditions
Difference in test meal liking (VAS) between the three (high-, low- and ideal) umami taste intensities.
Time frame: Test session 2, 3 and 4 (week 2, 3 and 4)
Absolute difference in umami taste intensity ratings of the ad libitum test meal between taste intensity conditions
Difference in absolute taste intensity ratings of the ad libitum test meal between the three (high-, low- and ideal) umami taste intensities. This will be rated after each lunch meal on a visual analogue scale (VAS).
Time frame: Test session 2, 3 and 4 (week 2, 3 and 4)
Relative difference in umami taste intensity ratings of the ad libitum test meal between taste intensity conditions
Relative taste intensity ratings based on ranking. Participants will be asked to rank the three meals based on umami taste intensity after the 3rd lunch meal. Ranking will be used, with anchors "least intense" to "most intense".
Time frame: Test session 4 (week 4)
Difference in water consumption during the ad libitum test meal between taste intensity conditions
Difference in water consumption in volume (grams) from the ad libitum test meal between the three (high-, low- and ideal) umami taste intensities
Time frame: Test session 2, 3 and 4 (week 2, 3 and 4)
Difference in reported appetite and fullness ratings between the three conditions
Before and after the ad libitum test meals, appetite and fullness ratings of participants will be assessed on a Visual Analogue Scale (VAS). Differences of these rating between umami taste intensity conditions (low-, high- and ideal umami taste intensity) will be assessed. VAS 0-100 will be used, with anchors "Not at all" to "Extremely".
Time frame: Test session 2, 3 and 4 (week 2, 3 and 4)
Difference in test meal liking between taste intensity conditions
Difference in test meal liking (VAS) between the three (high-, low- and ideal) umami taste intensities. VAS 0-100 will be used, with anchors "Not tasty at all" to "Extremely tasty".
Time frame: Test session 2, 3 and 4 (week 2, 3 and 4)
Habitual taste exposure
Habitual taste exposure will be measured with a food frequency questionnaire (tasteFFQ) specifically designed to assess relative food intake based on taste cluster. Individual optimum umami intensity will be compared to habitual dietary taste exposure to the salt, umami and fat taste cluster, as well as to the intake of umami tasting food items. Participants will fill in the tasteFFQ directly after the first (hedonic mapping session) visit. The tasteFFQ inquires average daily food intake, measured with a reference period of the previous four weeks.
Time frame: Participants will fill in the TasteFFQ directly after the first visit (hedonic mapping). The TasteFFQ captures average daily food intake over the previous four weeks (so food intake prior to study enrollment).
Plan to share: Yes — Individual study participant data will be shared after anonymization upon study publication in an open data repository (e.g. DANS or Yoda).
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