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Please use this identifier to cite or link to this item: http://hdl.handle.net/1843/58305
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dc.creatorKaren Monique Nunespt_BR
dc.creatorMarcus Vinicius de Oliveira Andradept_BR
dc.creatorMariana Ramos de Almeidapt_BR
dc.creatorCristiano Fantini Leitept_BR
dc.creatorMarcelo Martins de Senapt_BR
dc.date.accessioned2023-08-28T19:24:29Z-
dc.date.available2023-08-28T19:24:29Z-
dc.date.issued2019-
dc.citation.volume147pt_BR
dc.citation.spage582pt_BR
dc.citation.epage589pt_BR
dc.identifier.doihttps://doi.org/10.1016/j.microc.2019.03.076pt_BR
dc.identifier.issn1095-9149pt_BR
dc.identifier.urihttp://hdl.handle.net/1843/58305-
dc.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.pt_BR
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológicopt_BR
dc.description.sponsorshipFAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas Geraispt_BR
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superiorpt_BR
dc.format.mimetypepdfpt_BR
dc.languageengpt_BR
dc.publisherUniversidade Federal de Minas Geraispt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.departmentICX - DEPARTAMENTO DE FÍSICApt_BR
dc.publisher.departmentICX - DEPARTAMENTO DE QUÍMICApt_BR
dc.publisher.initialsUFMGpt_BR
dc.relation.ispartofMicrochemical Journal-
dc.rightsAcesso Abertopt_BR
dc.subjectMeat adulterationpt_BR
dc.subjectFood fraudpt_BR
dc.subjectSupervised classificationpt_BR
dc.subjectVibrational spectroscopypt_BR
dc.subjectForensic analysispt_BR
dc.subjectChemometricspt_BR
dc.subjectRaman spectroscopypt_BR
dc.subject.otherEspectroscopia de Ramanpt_BR
dc.subject.otherAnálise discriminantept_BR
dc.subject.otherQuimiometriapt_BR
dc.titleRaman spectroscopy and discriminant analysis applied to the detection of frauds in bovine meat by the addition of salts and carrageenanpt_BR
dc.typeArtigo de Periódicopt_BR
dc.url.externahttps://www.sciencedirect.com/science/article/pii/S0026265X18315546pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0001-5823-0763pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-2612-068Xpt_BR
dc.identifier.orcidhttps://orcid.org/0000-0003-0436-7857pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0001-5693-9015pt_BR
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