PROTSENS Rethinking Alternative PROTein Extraction: Decoding SENsory-Protein Extraction Relationships

全球食品系统排放约18%的温室气体(GHGs)，因为它依赖于动物来源的成分，如蛋白质。因此，为了减少食品系统对环境的影响，提高可持续性，人们正在研究以植物、昆虫和微藻为基础的蛋白质来源。然而，这些蛋白质对苦味和苦涩的感官知觉较差，导致社会对它们的接受程度较低。以前的研究项目未能提供机械性的洞察力和策略，在成分水平上最大限度地减少这些负面感官感觉。因此，问题仍然存在，这些蛋白质是天生苦涩的，还是蛋白质提取过程会导致蛋白质修饰，从而导致这些感官感觉。PROTSENS旨在了解并最大限度地减少这些负面感觉，使用保留蛋白质结构的绿色提取方法。这些新工艺产生的蛋白质提取物将得到彻底的表征。苦涩的机制将用物理方法从宏观到纳米进行研究，而苦味将通过模拟口腔环境中的感官细胞体外研究。体外、体外和物理工具将成为研究涩和苦感觉的新工具箱。蛋白质的性质、提取方法和它们的感官感知之间的联系将在机器学习(ML)模型中捕捉到。该模型将为基于蛋白质来源的蛋白质提取路线提供指导，以保存蛋白质结构并改善感官感受。总体而言，PROTSENS通过其新颖的实验工具包和ML模型，改善了对新蛋白质的感官感知和采用。PROTSENS将开辟欧洲食品蛋白质学术研究的新天地。PROTSENS的成功将有助于推动新蛋白质的采用，减少食品系统中的温室气体，并有助于缓解气候变化。

The global food system emits about 18% Green House Gas (GHGs), due to its reliance on animal-sourced ingredients such as proteins.Therefore, to reduce the environmental impact of the food system and improve sustainability, plant, insect, and microalgae-basedprotein sources are being investigated. However, these proteins suffer from poor sensory perception of bitterness and astringency,leading to poor adoption by society. Previous research projects have failed to provide mechanistic insight and strategies to minimizethese negative sensory perceptions at an ingredient level. Therefore, the question remains, whether these proteins are inherentlybitter and astringent or does the protein extraction process leads to protein modifications that cause these sensory perceptions.PROTSENS aims to understand and minimize these negative perceptions using green extraction methods that preserve proteinstructure. Protein extracts resulting from these novel processes will be thoroughly characterized. The mechanism of astringency andbitterness will be studied from macro to nanoscale using physical methods, while bitterness will be investigated using sensory cells invitro in a simulated oral environment. The in vitro, ex vivo and physical tools will serve as a novel toolbox to investigate astringencyand bitterness perception. The link between protein properties, extraction methods, and their sensory perception will be captured ina Machine Learning (ML) model. The model will provide a guide on protein extraction routes, based on protein source to preserveprotein structure and improve sensory perception. Overall, PROTSENS, through its novel experimental toolkit and ML model,improves the sensory perception of novel proteins and adoption. PROTSENS will open new horizons in European academic researchon food proteins. The success of PROTSENS will help drive the adoption of novel proteins, decrease GHGs in the food system, and helpmitigate climate change.