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A survey on computational taste predictors

2022; Springer Science+Business Media; Volume: 248; Issue: 9 Linguagem: Inglês

10.1007/s00217-022-04044-5

1438-2385

Marta Malavolta, Lorenzo Pallante, Bojan Mavkov, Filip Stojceski, Gianvito Grasso, Aigli Korfiati, Seferina Mavroudi, Αθανάσιος Καλογεράς, Christos Alexakos, Vanessa Martos, Daria Amoroso, Giacomo Di Benedetto, Dario Piga, Konstantinos Theofilatos, Marco A. Deriu,

Olfactory and Sensory Function Studies

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.The online version contains supplementary material available at 10.1007/s00217-022-04044-5.