Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/216087
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dc.contributor.authorLozano-Castellón, Julián-
dc.contributor.authorLaveriano-Santos, Emily P.-
dc.contributor.authorAbuhabib, Mohamed M.-
dc.contributor.authorPozzoli, Carola-
dc.contributor.authorPérez Bosch, Maria-
dc.contributor.authorVallverdú i Queralt, Anna-
dc.contributor.authorLamuela Raventós, Rosa Ma.-
dc.date.accessioned2024-10-28T13:24:39Z-
dc.date.available2024-10-28T13:24:39Z-
dc.date.issued2024-03-17-
dc.identifier.issn0924-2244-
dc.identifier.urihttps://hdl.handle.net/2445/216087-
dc.description.abstractBackground: risk of fraudulent mislabeling of organic food, driven by higher prices and a more favorable consumer perception, underscores the necessity for accurate authentication of organic products. Different analytical approaches and statistical analysis have been developed to classify between organic and conventional food. Scope and approach: In this review the current analytical approaches to detect organic food mislabeling are described. Potential and validated markers of organic traceability are explained, together with the techniques and statistical analysis employed. In this article, all the different foods have been reviewed and are presented by type of food. Key findings and conclusions: Variations in the elemental and stable isotopic ratios of fertilizers lead to differences in plant food ratios. In the case of animal food products, the distinct ratio in organic results in a final product with a unique elemental and stable isotopic composition. Those could be used for authenticating organic food. In addition, the different fertilization promotes different metabolic pathways leaving a distinct metabolic signature, hence targeted and untargeted metabolomic analysis permits the traceability of organic food. Finally, the use of soft classification models such as SIMCA, PLS-DA or OPLS-DA permits the classification of organic food and enables prediction of whether a new sample is conventional or organic. -
dc.format.extent15 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisherElsevier B.V.-
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.1016/j.tifs.2024.104430-
dc.relation.ispartofTrends in Food Science & Technology, 2024, vol. 147, p. 1-15-
dc.relation.urihttps://doi.org/10.1016/j.tifs.2024.104430-
dc.rightscc-by-nc-nd (c) Julián Lozano-Castellón, et al., 2024-
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/-
dc.sourceArticles publicats en revistes (Nutrició, Ciències de l'Alimentació i Gastronomia)-
dc.subject.classificationAgricultura biològica-
dc.subject.classificationQualitat dels aliments-
dc.subject.classificationEspectrometria de masses-
dc.subject.otherOrganic farming-
dc.subject.otherFood quality-
dc.subject.otherMass spectrometry-
dc.titleProven traceability strategies using chemometrics for organic food authenticity -
dc.typeinfo:eu-repo/semantics/article-
dc.typeinfo:eu-repo/semantics/publishedVersion-
dc.identifier.idgrec747764-
dc.date.updated2024-10-28T13:24:40Z-
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess-
Appears in Collections:Articles publicats en revistes (Nutrició, Ciències de l'Alimentació i Gastronomia)

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