From Tailored Chocolate Structuring with Additive Manufacturing to Sensory Perception, Neuroimaging and Pupillometry

Abstract

Additive manufacturing (AM) is transforming industries, but its potential in food production remains underexplored. We investigated the ability of AM to design novel 3D food structures with tailored sensory perceptions using fused deposition modeling technology. Initial sensory perceptions shaped the overall experience, though the profiles merged during later stages of oral processing. Enhanced sweetness perception was due to accelerated release of tastants (i.e., sucrose) from the first layer or reduced melting effort, which proved more critical than structural complexity beyond the first layer. Through the use of 3D inkjet printing technology, improved spatial surface resolution and tailored patterns increased sweetness perception by up to 300% over a commercial reference. To better understand mechanistically how structure influences taste, pupillometry was used to detect taste-evoked responses in real time, demonstrating that pupil size is a versatile biomarker of taste stimulus intensity, cognitive effort, and motor preparation. Electroencephalographic analyses examined taste-evoked neural patterns and revealed a sequential taste processing cascade. The gamma frequency range (38 Hz) was identified as central to sensory perception. Comparison of simulated taste bud concentrations with neural patterns confirmed the sensitivity of the gamma band to both perceptual and physicochemical information. In conclusion, our research has demonstrated the potential of AM to tailor food structures to enhance sensory perception, particularly sweetness. By integrating findings from pupillometry, neural imaging, and in silico tongue parameterization, we propose a multidimensional approach to understanding and predicting sensory perception, paving the way for future innovations in food design and sensory evaluation.