Discrimination between conventional and omega-3 fatty acids enriched eggs by FT-Raman spectroscopy and chemometric tools

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dc.creatorThiago de Oliveira Mendes
dc.creatorBrenda Lee Simas Porto
dc.creatorCristiano Fantini Leite
dc.creatorMariana Ramos de Almeida
dc.creatorMarcelo Martins de Sena
dc.date.accessioned2023-08-08T19:45:30Z
dc.date.accessioned2025-09-09T00:13:09Z
dc.date.available2023-08-08T19:45:30Z
dc.date.issued2019
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico
dc.description.sponsorshipFAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas Gerais
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
dc.identifier.doihttps://doi.org/10.1016/j.foodchem.2017.12.084
dc.identifier.issn1873-7072
dc.identifier.urihttps://hdl.handle.net/1843/57619
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofFood Chemistry
dc.rightsAcesso Restrito
dc.subjectEspectroscopia de Raman
dc.subjectQuimiometria
dc.subject.otherFood quality control
dc.subject.otherEgg
dc.subject.otherRaman spectra
dc.subject.otherLipids
dc.subject.otherSupervised classification
dc.subject.otherChemometrics
dc.titleDiscrimination between conventional and omega-3 fatty acids enriched eggs by FT-Raman spectroscopy and chemometric tools
dc.typeArtigo de periódico
local.citation.epage150
local.citation.spage144
local.citation.volume273
local.description.resumoThis work developed an analytical method to differentiate conventional and omega-3 fat acids enriched eggs by Raman spectroscopy and multivariate supervised classification with Partial Least Squares Discriminant Analysis (PLS-DA). Forty samples of enriched eggs and forty samples of different types of common eggs from different batches were used to build the model. Firstly, gas chromatography was employed to analyze fatty acid profiles in egg samples. Raman spectra of the yolk extracts were recorded in the range from 3100 to 990 cm−1 . PLS-DA model was able to correctly classify samples with nearly 100% success rate. This model was validated estimating appropriate figures of merit. Predictions uncertainties were also estimated by bootstrap resampling. The most discriminant Raman modes were identified based on VIP (variables importance in projection) scores. This method has potential to assist food industries and regulatory agencies for food quality control, allowing detecting frauds and enabling faster and reliable analyzes.
local.identifier.orcidhttps://orcid.org/0000-0002-8346-1552
local.identifier.orcidhttps://orcid.org/0000-0003-3469-0284
local.identifier.orcidhttps://orcid.org/0000-0003-0436-7857
local.identifier.orcidhttps://orcid.org/0000-0001-5693-9015
local.publisher.countryBrasil
local.publisher.departmentICX - DEPARTAMENTO DE FÍSICA
local.publisher.departmentICX - DEPARTAMENTO DE QUÍMICA
local.publisher.initialsUFMG
local.url.externahttps://www.sciencedirect.com/science/article/pii/S0308814617320551?via%3Dihub

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