000132289 001__ 132289
000132289 005__ 20241125101154.0
000132289 0247_ $$2doi$$a10.1016/j.foodchem.2023.137726
000132289 0248_ $$2sideral$$a137393
000132289 037__ $$aART-2023-137393
000132289 041__ $$aeng
000132289 100__ $$aFerrero-del-Teso, Sara
000132289 245__ $$aExploring UPLC-QTOF-MS-based targeted and untargeted approaches for understanding wine mouthfeel: A sensometabolomic approach
000132289 260__ $$c2023
000132289 5060_ $$aAccess copy available to the general public$$fUnrestricted
000132289 5203_ $$aThis study aimed to establish relationships between wine composition and in-mouth sensory properties using a sensometabolomic approach. Forty-two red wines were sensorially assessed and chemically characterised using UPLC‐QTOF-MS for targeted and untargeted analyses. Suitable partial least squares regression models were obtained for “dry”, “sour”, “oily”, “prickly”, and “unctuous”. “Dry” was positively contributed by flavan-3-ols, anthocyanin derivatives (AntD), valine, gallic acid and its ethyl ester, and peptides, and negatively by sulfonated flavan-3-ols, anthocyanin-ethyl-flavan-3-ols, tartaric acid, flavonols (FOL), hydroxycinnamic acids (HA), protocatechuic ethyl ester, and proline. The “sour” model included molecules involved in “dry” and “bitter”, ostensibly as a result of cognitive interactions. Derivatives of FOLs, epicatechin gallate, and N-acetyl-glucosamine phosphate contributed positively to “oily”, as did vanillic acid, HAs, pyranoanthocyanins, and malvidin-flavan-3-ol derivatives for “prickly”, and sugars, glutathione disulfide, AntD, FOL, and one HA for “unctuous”. The presented approach offers an interesting tool for deciphering the sensory-active compounds involved in mouthfeel perception.
000132289 536__ $$9info:eu-repo/grantAgreement/ES/MICINN/RYC2019-027995-I/AEI/10.13039/501100011033$$9info:eu-repo/grantAgreement/ES/AEI/PID2021-126031OB-C22$$9info:eu-repo/grantAgreement/ES/MINECO/AGL2017-87373-C3-3-R
000132289 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000132289 590__ $$a8.5$$b2023
000132289 592__ $$a1.745$$b2023
000132289 591__ $$aCHEMISTRY, APPLIED$$b5 / 74 = 0.068$$c2023$$dQ1$$eT1
000132289 593__ $$aAnalytical Chemistry$$c2023$$dQ1
000132289 591__ $$aNUTRITION & DIETETICS$$b4 / 114 = 0.035$$c2023$$dQ1$$eT1
000132289 593__ $$aMedicine (miscellaneous)$$c2023$$dQ1
000132289 591__ $$aFOOD SCIENCE & TECHNOLOGY$$b8 / 173 = 0.046$$c2023$$dQ1$$eT1
000132289 593__ $$aFood Science$$c2023$$dQ1
000132289 594__ $$a16.3$$b2023
000132289 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000132289 700__ $$aArapitsas, Panagiotis
000132289 700__ $$aJeffery, David W.
000132289 700__ $$0(orcid)0000-0002-3698-6719$$aFerreira, Chelo$$uUniversidad de Zaragoza
000132289 700__ $$aMattivi, Fulvio
000132289 700__ $$0(orcid)0000-0002-4516-9534$$aFernández-Zurbano, Purificación
000132289 700__ $$0(orcid)0000-0001-7225-2272$$aSáenz-Navajas, María-Pilar
000132289 7102_ $$12005$$2595$$aUniversidad de Zaragoza$$bDpto. Matemática Aplicada$$cÁrea Matemática Aplicada
000132289 773__ $$g437, Part 1 (2023), 137726 [11 pp.]$$pFood chem.$$tFood Chemistry$$x0308-8146
000132289 8564_ $$s4954975$$uhttps://zaguan.unizar.es/record/132289/files/texto_completo.pdf$$yVersión publicada
000132289 8564_ $$s2567018$$uhttps://zaguan.unizar.es/record/132289/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000132289 909CO $$ooai:zaguan.unizar.es:132289$$particulos$$pdriver
000132289 951__ $$a2024-11-22-12:08:28
000132289 980__ $$aARTICLE