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A non-targeted metabolomic approach based on reversed-phase liquid chromatography-mass spectrometry to evaluate coffee roasting process.
Pérez-Míguez, Raquel; Sánchez-López, Elena; Plaza, Merichel; Castro-Puyana, María; Marina, María Luisa.
Afiliação
  • Pérez-Míguez R; Departamento de Química Analítica, Química Física e Ingeniería Química, Universidad de Alcalá, Ctra. Madrid-Barcelona Km. 33.600, 28871 Alcalá de Henares, Madrid, Spain.
  • Sánchez-López E; Departamento de Química Analítica, Química Física e Ingeniería Química, Universidad de Alcalá, Ctra. Madrid-Barcelona Km. 33.600, 28871 Alcalá de Henares, Madrid, Spain.
  • Plaza M; Instituto de Investigación Química "Andrés M. del Río" (IQAR), Universidad de Alcalá, Ctra. Madrid-Barcelona Km. 33.600, 28871 Alcalá de Henares, Madrid, Spain.
  • Castro-Puyana M; Departamento de Química Analítica, Química Física e Ingeniería Química, Universidad de Alcalá, Ctra. Madrid-Barcelona Km. 33.600, 28871 Alcalá de Henares, Madrid, Spain.
  • Marina ML; Instituto de Investigación Química "Andrés M. del Río" (IQAR), Universidad de Alcalá, Ctra. Madrid-Barcelona Km. 33.600, 28871 Alcalá de Henares, Madrid, Spain.
Anal Bioanal Chem ; 410(30): 7859-7870, 2018 Dec.
Article em En | MEDLINE | ID: mdl-30345455
ABSTRACT
In this work, a non-targeted metabolomics approach based on the use of reversed-phase liquid chromatography coupled to a high-resolution mass spectrometer has been developed to provide the characterization of coffee beans roasted at three different levels (light, medium, and dark). In this way, it was possible to investigate how metabolites change during the roasting process in order to identify those than can be considered as relevant markers. Twenty-five percent methanol was selected as extracting solvent since it provided the highest number of molecular features. In addition, the effect of chromatographic and MS parameters was evaluated in order to obtain the most adequate separation and detection conditions. Data were analyzed using both non-supervised and supervised multivariate statistical methods to point out the most significant markers that allow group discrimination. A total of 24 and 33 compounds in positive and negative ionization modes, respectively, demonstrated to be relevant markers; most of them were from the hydroxycinnamic acids family. Graphical abstract ᅟ.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Controle de Qualidade / Café Tipo de estudo: Evaluation_studies / Prognostic_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Controle de Qualidade / Café Tipo de estudo: Evaluation_studies / Prognostic_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article