Sensory optimization of Peruvian Lucuma fruit ice cream using I-Optimal Mixture Design - Babu, Sidharth (Kansas State University, 2024)
Consumers are increasingly interested in healthier, more diverse, and culturally inspired ice cream options. Lucuma, a subtropical fruit from the Andes, is gaining popularity in desserts like ice cream due to its natural sweetness and flavor-enhancing properties. Previous research shows that higher levels of Lucuma fruit powder in ice cream affected consumer acceptance. Understanding consumer behavior is crucial in the food industry, with psychographic segmentation providing insights into values and preferences. The objectives of this study were 1) to use i-optimal mixture design for formulating various ice creams with different levels of fat, sugar, and lucuma fruit powder. It also involves evaluating the sensory properties and consumer liking of the prototypes, 2) Optimize consumer liking scores to develop a predictive model that determines maximum ice cream likeability and ideal ingredient levels in the formulation, and 3) To segment consumers based on psychographic data into health-conscious and indulgent groups, to identify sensory response differences in Lucuma ice cream prototypes, and to optimize product formulation for targeted market segments. A total of 11 Lucuma ice creams were produced at the K-State Innovation Kitchen, Olathe. A consumer study (n=104) revealed statistically significant differences in liking between the lucuma ice cream prototypes for all attributes except aroma liking. The flavor profiles varied widely based on product composition, with different levels of lucuma resulting in distinct sensory variations among the prototypes. The study found that optimizing the levels of lucuma fruit powder, sucrose, and milk fat at 1.5%, 13%, and 6.0% respectively led to an overall likeability score of 7.3 among consumers. However, reducing sucrose and increasing lucuma fruit powder resulted in decreased consumer acceptance. Incorporating lucuma fruit powder at optimal levels can enhance the texture of reduced-fat ice cream products. Based on psychographic data, K-means clustering segmented the consumers into health-conscious (n=53) and indulgent (n=51) groups. The consumer acceptance scores of each segment were used to predict the optimal levels of ingredients for the lucuma ice cream formulations specific to each segment. The overall likeability of the health-conscious group had an optimized score of 7.6 on a 9-point hedonic scale, while the indulgent group scored 7.1 for the same formulation containing 1.5% lucuma fruit powder, 13% sucrose, and 6% fat, indicating a difference in their liking pattern.
Keywords: Lucuma ice cream development; I-optimal mixture design; Pyschographic consumer segmentation; Sensory analysis; Sensory optimization; Check all that apply (CATA); Consumer research