Texture design of food biopolymers by 3D printing for modulation of odour/flavour perception

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According to latest findings, the almost unlimited variety of food aromas are composed of only ~230 key odorants of which a combination of 3 to ~40 compounds in distinct concentrations form the chemical odour code of a product. Not individual compounds, but their combinatorics ensure the authentic olfactory and taste perception of food systems. In addition to the concentration of odorants and flavours, the sensorial receptor activity pattern during food consumption mainly depends on the texture (gels, foams). The lack of knowledge of the texture-induced shifts of the combinatorial odour/flavour codes limit the possibility of targeted analysis and control of chemosensory perception. Particularly, the sensory activity can hardly be predicted by the integral mass concentration of individual compounds if odour/flavour-active compounds are distributed inhomogeneously (would induce intense sensory perceptions).Previous studies were not carried out on key odorants and flavours of individual foods and could only be performed in empirical approaches on sparsely defined food textures. Textures of complex systems differ strongly depending on manufacturing processes (e.g. pore size distribution). Therefore, it is almost impossible to give reproducible mechanistic explanations, currently.Precisely this topic is explored in a pioneering approach by designing of highly defined food textures and a reproducible production of locally resolved concentration gradients of key odorants and flavours. The aim is to study the influence of the texture as well as their distribution in a standardized matrix on quantitative shifts in the chemosensory code of food in a systematic manner. In contrast to conventional processes, the target is to build up defined textures of food biopolymers layer by layer by means of a specific developed 3D-printing technology. Concentration fields of sensory relevant key compounds supposed to be doped as molecular probes in textures. In this project, the focus is on cereal-based food textures. The texture will be gradually build up from an airless single-component matrix to a defined foam like multi-component matrix. Thus, defined concentration gradients of odorants and flavours can be specifically incorporated and locally resolved in textures for the first time. Additionally, the influence of foam textures on the human sensory perception can be elucidated.