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Type:	Artigo de Periódico
Title:	Raman spectroscopy and discriminant analysis applied to the detection of frauds in bovine meat by the addition of salts and carrageenan
Authors:	Karen Monique Nunes Marcus Vinicius de Oliveira Andrade Mariana Ramos de Almeida Cristiano Fantini Leite Marcelo Martins de Sena
Abstract:	In 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.
Subject:	Espectroscopia de Raman Análise discriminante Quimiometria
language:	eng
metadata.dc.publisher.country:	Brasil
Publisher:	Universidade Federal de Minas Gerais
Publisher Initials:	UFMG
metadata.dc.publisher.department:	ICX - DEPARTAMENTO DE FÍSICA ICX - DEPARTAMENTO DE QUÍMICA
Rights:	Acesso Aberto
metadata.dc.identifier.doi:	https://doi.org/10.1016/j.microc.2019.03.076
URI:	http://hdl.handle.net/1843/58305
Issue Date:	2019
metadata.dc.url.externa:	https://www.sciencedirect.com/science/article/pii/S0026265X18315546
metadata.dc.relation.ispartof:	Microchemical Journal
Appears in Collections:	Artigo de Periódico

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