Texture Independently Drives Liking in AI-Generated Alternative Protein Burgers
Vahidullah Tac, Aeneas O. Koosis, Ellen Kuhl

TL;DR
This study links mechanical texture measurements with sensory perception and liking of AI-generated alternative protein burgers, highlighting resilience as a key factor influencing consumer preference.
Contribution
It identifies specific textural features that drive perception and liking, emphasizing resilience as a target for texture engineering in alternative proteins.
Findings
Animal-based burgers have distinct firm, fatty, and cohesive textures.
Mushroom- and plant-based burgers deviate in springy, gummy, dry, and brittle textures.
Resilience is the strongest mechanical predictor of perceived meatiness and liking.
Abstract
Texture shapes how we perceive and like food, yet clear links between mechanical measurements and sensory perception of texture remain elusive. Here we combine sensory data from a blind tasting with 101 participants with mechanical texture profile analysis across six burgers to identify the textural features that drive consumer perception and liking. We compare five burgers -- generated with artificial intelligence -- with animal-based, plant-based, mushroom-based, and hybrid animal-mushroom patties, and the classical Big\,Mac. Three main findings emerge: First, animal-based burgers occupy a distinctive and coherent sensory-mechanical region associated with attributes such as firm, fatty, and holds together. Second, mushroom- and plant-based burgers deviate from this region in protein-dependent ways: mushroom-based burgers associate with springy and gummy textures, while plant-based…
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