Sydney Tankard, Penn State Food Science MS Graduate Student

- https://foodscience.psu.edu/events/seminar-consumer-perception-of-fat-content-changes-in-milkshakes-and-ice-cream
- Seminar - Consumer Perception of Fat Content Changes in Milkshakes and Ice Cream
- 2025-04-17T16:00:00-04:00
- 2025-04-17T17:00:00-04:00
- Sydney Tankard, Penn State Food Science MS Graduate Student
When April 17, 2025, 4:00 PM - 5:00 PM
Where 252 Erickson Food Science Building
The food industry continues to prioritize calorie reduction in products, with fat serving as a common target due to its high caloric density (9 kcal/gram) compared to carbohydrates and proteins (4 kcal/gram). Despite its caloric content, fat is integral to the flavor, mouthfeel, and texture that consumers enjoy in many foods, particularly dairy-based products such as ice cream. Reducing Milkfat in frozen desserts presents challenges, as it requires maintaining the delicate balance of ingredients within these complex matrices. Additionally, previous literature has shown that fat changes in solid dairy systems are more difficult for consumers to detect compared to liquid dairy systems. To further explore consumer sensitivity to fat reduction, this study evaluated the Just Noticeable Differences (JNDs) in fat content for two dairy systems: milkshakes (liquid matrix) and ice cream (solid matrix).
Pre-screened participants took part in a series of two-alternative forced-choice (2-AFC) tests using the Method of Constant Stimuli. For milkshakes (total n = 216), results indicate that manufacturers and nutritionists have room to adjust fat content by approximately 5.30% in Vanilla bean formulations before consumers perceive a difference. This threshold increases with the addition of a textural component (6.16% Milkfat) or a variation in thickness (6.11% Milkfat), suggesting that these factors might make it more difficult to perceive fat changes. Ice cream testing employed mixed qualitative and quantitative methods to investigate the difficulty of detecting fat differences in semi-solid dairy systems. Consumer-generated language provided descriptors for perceived fat differences, which were then utilized in blind taste tests to determine the JND for ice cream. Results across multiple ice cream tests (total n = 306) suggest that larger fat differences are required to determine a JND for fat in this system, in addition to further exploration of fat-related descriptors.
Join this virtual seminar on Zoom