{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T10:47:38Z","timestamp":1785754058275,"version":"3.56.0"},"reference-count":105,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2022,1,7]],"date-time":"2022-01-07T00:00:00Z","timestamp":1641513600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100013003","name":"University of Cagliari","doi-asserted-by":"publisher","award":["Fondi 5 per mille (Anno 2017) and Fondo Integrativo per la Ricerca (FIR 2019)"],"award-info":[{"award-number":["Fondi 5 per mille (Anno 2017) and Fondo Integrativo per la Ricerca (FIR 2019)"]}],"id":[{"id":"10.13039\/100013003","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Nutrients"],"abstract":"<jats:p>Several studies have used taste sensitivity to 6-n-propylthiouracil (PROP) to evaluate interindividual taste variability and its impact on food preferences, nutrition, and health. We used a supervised learning (SL) approach for the automatic identification of the PROP taster categories (super taster (ST); medium taster (MT); and non-taster (NT)) of 84 subjects (aged 18\u201340 years). Biological features determined from subjects were included for the training system. Results showed that SL enables the automatic identification of objective PROP taster status, with high precision (97%). The biological features were classified in order of importance in facilitating learning and as prediction factors. The ratings of perceived taste intensity for PROP paper disks (50 mM) and PROP solution (3.2 mM), along with fungiform papilla density, were the most important features, and high estimated values pushed toward ST prediction, while low values leaned toward NT prediction. Furthermore, TAS2R38 genotypes were significant features (AVI\/AVI, PAV\/PAV, and PAV\/AVI to classify NTs, STs, and MTs, respectively). These results, in showing that the SL approach enables an automatic, immediate, scalable, and high-precision classification of PROP taster status, suggest that it may represent an objective and reliable tool in taste physiology studies, with applications ranging from basic science and medicine to food sciences.<\/jats:p>","DOI":"10.3390\/nu14020252","type":"journal-article","created":{"date-parts":[[2022,1,9]],"date-time":"2022-01-09T23:06:15Z","timestamp":1641769575000},"page":"252","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Automated Classification of 6-n-Propylthiouracil Taster Status with Machine Learning"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1721-6815","authenticated-orcid":false,"given":"Lala","family":"Naciri","sequence":"first","affiliation":[{"name":"Department of Biomedical Sciences, University of Cagliari, Monserrato, 09042 Cagliari, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3833-9707","authenticated-orcid":false,"given":"Mariano","family":"Mastinu","sequence":"additional","affiliation":[{"name":"Department of Biomedical Sciences, University of Cagliari, Monserrato, 09042 Cagliari, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roberto","family":"Crnjar","sequence":"additional","affiliation":[{"name":"Department of Biomedical Sciences, University of Cagliari, Monserrato, 09042 Cagliari, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2849-4052","authenticated-orcid":false,"given":"Iole","family":"Tomassini Barbarossa","sequence":"additional","affiliation":[{"name":"Department of Biomedical Sciences, University of Cagliari, Monserrato, 09042 Cagliari, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3410-3158","authenticated-orcid":false,"given":"Melania","family":"Melis","sequence":"additional","affiliation":[{"name":"Department of Biomedical Sciences, University of Cagliari, Monserrato, 09042 Cagliari, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1016\/j.neuron.2005.10.015","article-title":"Taste recognition: Food for thought","volume":"48","author":"Scott","year":"2005","journal-title":"Neuron"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1083\/jcb.201003144","article-title":"The cell biology of taste","volume":"190","author":"Chaudhari","year":"2010","journal-title":"J. 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