味觉是一种对营养和生存至关重要的感官形态,因为它允许区分健康食品和有毒物质,这要归功于五种口味,即,甜,苦涩,umami,咸,酸,与不同的营养或生理需求有关。今天,味觉预测在几个领域起着关键作用,例如,medical,工业,或药物,但是味觉感知过程的复杂性,它的多学科性质,和大量的潜在相关的参与者和特征的基础上的味觉感觉使味觉预测是一个非常复杂的任务。在这种情况下,机器学习的新兴能力为这一研究领域提供了卓有成效的见解,允许考虑和整合大量变量,并识别特定口味感知背后的隐藏相关性。这篇综述旨在总结口味预测的最新进展,分析近年来开发的食品相关数据库和口味预测工具。
■在线版本包含补充材料,可在10.1007/s00217-022-04044-5获得。
Taste is a sensory modality crucial for nutrition and survival, since it allows the discrimination between healthy foods and toxic substances thanks to five tastes, i.e., sweet, bitter, umami, salty, and sour, associated with distinct nutritional or physiological needs. Today, taste prediction plays a key role in several fields, e.g., medical, industrial, or pharmaceutical, but the complexity of the taste perception process, its multidisciplinary nature, and the high number of potentially relevant players and features at the basis of the taste sensation make taste prediction a very complex task. In this context, the emerging capabilities of machine learning have provided fruitful insights in this field of research, allowing to consider and integrate a very large number of variables and identifying hidden correlations underlying the perception of a particular taste. This review aims at summarizing the latest advances in taste prediction, analyzing available food-related databases and taste prediction tools developed in recent years.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s00217-022-04044-5.