Raman spectroscopy and discriminant analysis applied to the detection of frauds in bovine meat by the addition of salts and carrageenan

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dc.creatorKaren Monique Nunes
dc.creatorMarcus Vinicius de Oliveira Andrade
dc.creatorMariana Ramos de Almeida
dc.creatorCristiano Fantini Leite
dc.creatorMarcelo Martins de Sena
dc.date.accessioned2023-08-28T19:24:29Z
dc.date.accessioned2025-09-08T23:36:07Z
dc.date.available2023-08-28T19:24:29Z
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.format.mimetypepdf
dc.identifier.doihttps://doi.org/10.1016/j.microc.2019.03.076
dc.identifier.issn1095-9149
dc.identifier.urihttps://hdl.handle.net/1843/58305
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofMicrochemical Journal
dc.rightsAcesso Aberto
dc.subjectEspectroscopia de Raman
dc.subjectAnálise discriminante
dc.subjectQuimiometria
dc.subject.otherMeat adulteration
dc.subject.otherFood fraud
dc.subject.otherSupervised classification
dc.subject.otherVibrational spectroscopy
dc.subject.otherForensic analysis
dc.subject.otherChemometrics
dc.subject.otherRaman spectroscopy
dc.titleRaman spectroscopy and discriminant analysis applied to the detection of frauds in bovine meat by the addition of salts and carrageenan
dc.typeArtigo de periódico
local.citation.epage589
local.citation.spage582
local.citation.volume147
local.description.resumoIn the last years, there has been an important and growing concern about food authentication due to the increasing number of occurrences of new types of food frauds. Recently, some frauds have been reported describing the injection of non-meat ingredients, such as salts and polysaccharide compounds, into bovine meat in natura, aiming at increasing its water holding capacity (WHC) and obtaining economic fraudulent gains. Thus, this paper developed a simple and rapid analytical method based on a multivariate supervised classification model (partial least squares discriminant analysis, PLS-DA) and Raman spectroscopy for tackling this problem. Sixteen vacuum-packed pieces of the same cut, eye of the round (semitendinosus), of approximately 4 kg were obtained from different origins. According to an experimental design, each piece was divided into 11 parts, providing control and adulterated samples. Single, binary and ternary mixtures of adulterated samples were prepared by injecting NaCl, sodium tripolyphosphate and carrageenan in the meat pieces. A total of 165 samples were produced (54 controls and 111 adulterated) and their purges, the exudated liquid extracted from the meat after thawing, were obtained. Raman spectra of these purges were recorded between 1800 and 700 cm−1. The whole data set was split into 112 samples for the training set and 53 for the test set. The best PLS-DA model was built with 4 latent variables and successfully discriminated adulterated samples at relatively small rates of false negative and false positive results, which varied from 8.0 to 11.7%. As an additional validation step, confidence intervals were calculated by bootstrap algorithm.
local.identifier.orcidhttps://orcid.org/0000-0001-5823-0763
local.identifier.orcidhttps://orcid.org/0000-0002-2612-068X
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/S0026265X18315546

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