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

通过 3D 打印进行食品生物聚合物的纹理设计，以调节气味/风味感知

• 批准号: 405072578
• 负责人: Professor Dr.-Ing. Thomas Becker
• 金额: --
• 依托单位: Hochschulpräsidium
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/405072578?language=en
• 关键词: Texture; design; food; biopolymers; 3D

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.

根据最新发现，几乎无限种类的食品香气只由230种关键气味物质组成，其中3到40种不同浓度的化合物组合构成了产品的化学气味代码。不是单独的化合物，但它们的组合确保了对食物系统的真实嗅觉和味道感知。除了气味和味道的浓度外，食物消费过程中感官感受器的活动模式主要取决于质地(凝胶、泡沫)。缺乏对质地诱导的气味/味道组合编码的移动的了解限制了对化学感觉的有针对性的分析和控制的可能性。特别是，如果气味/风味活性化合物的分布不均匀(会引起强烈的感官感受)，则很难用单个化合物的整体质量浓度来预测感官活性。以前的研究没有针对单个食品的关键气味和风味进行，只能对定义较少的食品质地进行经验研究。复杂系统的织构因制造工艺的不同而有很大差异(例如，孔径分布)。因此，目前几乎不可能给出可重复的机械解释。简而言之，这个主题是通过设计高度明确的食品质地和可重复生产的关键气味和风味的局部可分辨浓度梯度来探索的。其目的是系统地研究质构及其在标准化矩阵中的分布对食品化学感官编码的量化位移的影响。与传统工艺不同，目标是通过一种专门开发的3D打印技术，逐层建立食品生物聚合物的特定纹理。与感官相关的关键化合物的浓度场被认为是作为纹理中的分子探针掺杂的。在这个项目中，重点放在以谷物为基础的食物纹理上。质地将从无空气的单组分基质逐渐形成类似于多组分基质的明确的泡沫。因此，确定的气味和风味的浓度梯度可以第一次在质地中具体地并入和局部分解。此外，泡沫质地对人类感官知觉的影响也可以阐明。