Sensory optimization of Peruvian lucuma fruit ice cream using I-optimal mixture design

• The consumer-data-driven approach, utilizing I-Optimal mixture design and sensory data, enabled the development of a commercially viable Lucuma ice cream for the U.S. market • The optimized lucuma ice cream formulation, balancing the key ingredients, achieved maximum consumer liking for texture, mouthfeel, and overall liking. • Correspondence analysis of CATA data revealed distinct flavor profiles across the lucuma ice cream prototypes. • A practical framework is presented for food manufacturers to leverage consumer insights and statistical techniques to develop innovative and appealing food products. Optimizing food products to maximize consumer liking is challenging due to the inherent variability in sensory perception. This study addressed this challenge by developing a novel lucuma ice cream formulation using an I-optimal mixture design. Eleven ice cream prototypes, varying in concentrations of Lucuma Fruit Powder (LFP), milk fat, and sucrose, with additional ingredients serving as the filler were evaluated by 104 consumers using a complete balanced randomized design. Consumer acceptance scores for overall liking, texture liking, and mouthfeel liking were modeled using Scheffé’s linear mixture model. Desirability function analysis was applied to identify the optimal formulation that maximized the combined consumer acceptance scores. Correspondence analysis of CATA data revealed distinct flavor profiles across the prototypes. Higher LFP concentrations were associated with stronger, potentially less desirable flavors, highlighting the importance of careful balancing LFP levels to achieve optimal consumer acceptance. The optimal formulation with maximized consumer acceptance, contained 1.5% LFP, 13% sucrose, and 6% milk fat, achieving high scores for overall liking (7.3), texture liking (7.9), and mouthfeel liking (7.8) with a desirability score of 1. Results indicate that reducing sucrose and increasing LFP in the ice cream formulation led to a drop in consumer acceptance. The variations in fat levels did not significantly impact consumer liking, suggesting the potential of LFP as a fat replacer in ice cream formulations without compromising consumer acceptance. Incorporating LFP at optimal levels could enhance the textural qualities by improving the mouthfeel of lower-fat ice creams. This study suggests a framework that could be used by food producers to maximize consumer acceptance of novel ingredients in complex food systems.

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Publication Details

Journal
Applied Food Research
Published
2025-03-04
DOI
https://doi.org/10.1016/j.afres.2025.100807
Citations
2
Primary Topic
Postharvest Quality and Shelf Life Management
Type
article
Field-Weighted Citation Impact
3.50
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article

Sensory optimization of Peruvian lucuma fruit ice cream using I-optimal mixture design

Rajesh Kumar, Martin Talavera, Sidharth Babu, Jeff Garza
2 citations
Applied Food Research
Postharvest Quality and Shelf Life Management
3.50
article

Sensory optimization of Peruvian lucuma fruit ice cream using I-optimal mixture design

Rajesh Kumar, Martin Talavera, Sidharth Babu, Jeff Garza
article en
2 citations

Abstract

• The consumer-data-driven approach, utilizing I-Optimal mixture design and sensory data, enabled the development of a commercially viable Lucuma ice cream for the U.S. market • The optimized lucuma ice cream formulation, balancing the key ingredients, achieved maximum consumer liking for texture, mouthfeel, and overall liking. • Correspondence analysis of CATA data revealed distinct flavor profiles across the lucuma ice cream prototypes. • A practical framework is presented for food manufacturers to leverage consumer insights and statistical techniques to develop innovative and appealing food products. Optimizing food products to maximize consumer liking is challenging due to the inherent variability in sensory perception. This study addressed this challenge by developing a novel lucuma ice cream formulation using an I-optimal mixture design. Eleven ice cream prototypes, varying in concentrations of Lucuma Fruit Powder (LFP), milk fat, and sucrose, with additional ingredients serving as the filler were evaluated by 104 consumers using a complete balanced randomized design. Consumer acceptance scores for overall liking, texture liking, and mouthfeel liking were modeled using Scheffé’s linear mixture model. Desirability function analysis was applied to identify the optimal formulation that maximized the combined consumer acceptance scores. Correspondence analysis of CATA data revealed distinct flavor profiles across the prototypes. Higher LFP concentrations were associated with stronger, potentially less desirable flavors, highlighting the importance of careful balancing LFP levels to achieve optimal consumer acceptance. The optimal formulation with maximized consumer acceptance, contained 1.5% LFP, 13% sucrose, and 6% milk fat, achieving high scores for overall liking (7.3), texture liking (7.9), and mouthfeel liking (7.8) with a desirability score of 1. Results indicate that reducing sucrose and increasing LFP in the ice cream formulation led to a drop in consumer acceptance. The variations in fat levels did not significantly impact consumer liking, suggesting the potential of LFP as a fat replacer in ice cream formulations without compromising consumer acceptance. Incorporating LFP at optimal levels could enhance the textural qualities by improving the mouthfeel of lower-fat ice creams. This study suggests a framework that could be used by food producers to maximize consumer acceptance of novel ingredients in complex food systems.

Applied Food ResearchVol. 5(1)
Academy of Nutrition and Dietetics (US), Lakeland Library Cooperative (US)
Zero hunger
Openalex Percentile: Top 9%
Postharvest Quality and Shelf Life Management
3.50
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