Please use this identifier to cite or link to this item:
http://hdl.handle.net/2445/160897
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Campmajó Galván, Guillem | - |
dc.contributor.author | Saez-Vigo, Ruben | - |
dc.contributor.author | Saurina, Javier | - |
dc.contributor.author | Núñez Burcio, Oscar | - |
dc.date.accessioned | 2020-05-18T09:59:15Z | - |
dc.date.available | 2021-03-18T06:10:20Z | - |
dc.date.issued | 2020-03-18 | - |
dc.identifier.issn | 0956-7135 | - |
dc.identifier.uri | http://hdl.handle.net/2445/160897 | - |
dc.description.abstract | Economically motivated food fraud has increased in recent years, with adulterations and substitutions of high-quality products being common practice. Moreover, this issue can affect food safety and pose a risk to human health by causing allergies through nut product adulterations. Therefore, in this study, high-performance liquid chromatography with fluorescence detection (HPLC-FLD) fingerprints were used for classification of ten types of nuts, using partial least squares regression-discriminant analysis (PLS-DA), as well as for the detection and quantitation of almond-based product (almond flour and almond custard cream) adulterations with hazelnut and peanut, using partial least squares regression (PLS). A satisfactory global nut classification was achieved with PLS-DA. Paired PLS-DA models of almonds in front of their adulterants were also evaluated, producing a classification rate of 100%. Moreover, PLS regression produced low prediction errors (below 6.1%) for the studied adulterant levels, with no significant matrix effect observed. | - |
dc.format.extent | 28 p. | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | eng | - |
dc.publisher | Elsevier B.V. | - |
dc.relation.isformatof | Versió postprint del document publicat a: https://doi.org/10.1016/j.foodcont.2020.107265 | - |
dc.relation.ispartof | Food Control, 2020, vol. 114, p. 107265 | - |
dc.relation.uri | https://doi.org/10.1016/j.foodcont.2020.107265 | - |
dc.rights | cc-by-nc-nd (c) Elsevier B.V., 2020 | - |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es | - |
dc.source | Articles publicats en revistes (Enginyeria Química i Química Analítica) | - |
dc.subject.classification | Ametlles | - |
dc.subject.classification | Àcid oleic | - |
dc.subject.classification | Quimiometria | - |
dc.subject.classification | Inspecció dels aliments | - |
dc.subject.classification | Cromatografia de líquids d'alta resolució | - |
dc.subject.other | Almond | - |
dc.subject.other | Oleic acid | - |
dc.subject.other | Chemometrics | - |
dc.subject.other | Food inspection | - |
dc.subject.other | High performance liquid chromatography | - |
dc.title | High-performance liquid chromatography with fluorescence detection fingerprinting combined with chemometrics for nut classification and the detection and quantitation of almond-based product adulterations | - |
dc.type | info:eu-repo/semantics/article | - |
dc.type | info:eu-repo/semantics/acceptedVersion | - |
dc.identifier.idgrec | 699976 | - |
dc.date.updated | 2020-05-18T09:59:16Z | - |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | - |
Appears in Collections: | Articles publicats en revistes (Enginyeria Química i Química Analítica) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
699976.pdf | 1.53 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License