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

根据最新的研究结果，几乎无限种类的食物香味仅由~230种关键气味剂组成，其中3至~40种不同浓度的化合物组合形成产品的化学气味代码。不是单个化合物，而是它们的组合确保了食物系统的真实嗅觉和味觉感知。除了气味和风味的浓度外，食物消费期间的感觉受体活动模式主要取决于质地（凝胶，泡沫）。缺乏知识的纹理诱导的变化的组合气味/风味代码限制了有针对性的分析和控制的化学感觉知觉的可能性。特别是，感官活动很难预测的积分质量浓度的个别化合物，如果气味/风味活性化合物分布不均匀（会引起强烈的感官知觉）。以前的研究没有进行的关键气味和风味的个别食品，只能在经验的方法上进行稀疏定义的食品质地。复杂系统的纹理根据制造工艺（例如孔径分布）而有很大差异。因此，目前几乎不可能给出可重复的机理解释。正是通过设计高度定义的食品质地和可重复生产关键气味和风味的局部分辨浓度梯度，以开创性的方法探索了这一主题。目的是研究质地的影响，以及它们在一个标准化的矩阵中的分布上的定量变化的化学感觉代码的食物在一个系统的方式。与传统工艺相比，其目标是通过特定的3D打印技术逐层构建食品生物聚合物的定义纹理。作为分子探针掺杂的感觉相关关键化合物在纹理中的浓度场。在这个项目中，重点是基于谷物的食品质地。质地将从无气的单组分基质逐渐形成为限定的泡沫状多组分基质。因此，气味剂和香料的限定浓度梯度可以第一次在纹理中被具体地结合和局部解析。此外，可以阐明泡沫质地对人类感官知觉的影响。

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.