dc.contributor.author | Malavolta, Marta | |
dc.contributor.author | Martos Núñez, María Vanesa | |
dc.date.accessioned | 2022-06-24T11:31:31Z | |
dc.date.available | 2022-06-24T11:31:31Z | |
dc.date.issued | 2022-05-26 | |
dc.identifier.citation | Malavolta, M... [et al.]. A survey on computational taste predictors. Eur Food Res Technol (2022). [https://doi.org/10.1007/s00217-022-04044-5] | es_ES |
dc.identifier.uri | http://hdl.handle.net/10481/75649 | |
dc.description.abstract | 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. | es_ES |
dc.description.sponsorship | Politecnico di Torino within the CRUI-CARE Agreement | es_ES |
dc.description.sponsorship | European Union's Horizon 2020 research and innovation program 872181 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Springer | es_ES |
dc.rights | Atribución 3.0 España | * |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | Machine learning | es_ES |
dc.subject | Taste prediction | es_ES |
dc.subject | Molecular descriptors | es_ES |
dc.subject | Small compounds | es_ES |
dc.subject | Tastants | es_ES |
dc.subject | Food | es_ES |
dc.title | A survey on computational taste predictors | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/872181 | es_ES |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es_ES |
dc.identifier.doi | 10.1007/s00217-022-04044-5 | |
dc.type.hasVersion | info:eu-repo/semantics/publishedVersion | es_ES |