A one-class classification approach for authentication of specialty coffees by inductively coupled plasma mass spectroscopy (ICP-MS).

Autor: de Oliveira Costa T; Laboratório de Analítica, Metabolômica e Quimiometria (LAMeQui), Instituto Federal de Educação, Ciência e Tecnologia do Espírito Santo, Campus Alegre (IFES), Brazil; Programa de Pós-Graduação em Ciências Naturais (PPGCN), Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF), Brazil., Rangel Botelho J; Instituto Federal de Educação, Ciência e Tecnologia Fluminense (IFF), Brazil., Helena Cassago Nascimento M; Departamento de Química, Universidade Federal do Espírito Santo (UFES), Brazil., Krause M; Departamento de Química, Universidade Federal do Espírito Santo (UFES), Brazil., Tereza Weitzel Dias Carneiro M; Departamento de Química, Universidade Federal do Espírito Santo (UFES), Brazil., Coelho Ferreira D; Instituto Federal de Educação, Ciência e Tecnologia Fluminense (IFF), Brazil., Roberto Filgueiras P; Departamento de Química, Universidade Federal do Espírito Santo (UFES), Brazil., de Oliveira Souza M; Laboratório de Analítica, Metabolômica e Quimiometria (LAMeQui), Instituto Federal de Educação, Ciência e Tecnologia do Espírito Santo, Campus Alegre (IFES), Brazil; Programa de Pós-Graduação em Ciências Naturais (PPGCN), Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF), Brazil. Electronic address: murilo.souza@ifes.edu.br.
Jazyk: angličtina
Zdroj: Food chemistry [Food Chem] 2024 Jun 01; Vol. 442, pp. 138268. Date of Electronic Publication: 2023 Dec 24.
DOI: 10.1016/j.foodchem.2023.138268
Abstrakt: Due to the lucrative nature of specialty coffees, there have been instances of adulteration where low-cost materials are mixed in to increase the overall volume, resulting in illegal profit. A widely used and recommended approach to detect possible adulteration is the application of one-class classifiers (OCC), which only require information about the target class to build the models. Thus, this work aimed to identify adulterations in specialty coffees with low-quality coffee using multielement analysis determined by ICP-MS and to evaluate the performance of one-class classifiers (dd-SIMCA, OCRF, and OCPLS). Therefore, authentic specialty coffee samples were adulterated with low-quality coffee in 25 % to 75 % (w/w) proportions. Samples were subjected to acid decomposition for analysis by ICP-MS. OCPLS method presented the best performance to detect adulterations with low-quality coffee in specialty coffees, showing higher specificity (SPE = 100 %) and reliability rate (RLR = 94.3 %).
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2023 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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