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Comprehensive Chemical Fingerprinting of High-Quality Cocoa at Early Stages of Processing: Effectiveness of Combined Untargeted and Targeted Approaches for Classification and Discrimination.
Magagna, Federico; Guglielmetti, Alessandro; Liberto, Erica; Reichenbach, Stephen E; Allegrucci, Elena; Gobino, Guido; Bicchi, Carlo; Cordero, Chiara.
Afiliação
  • Magagna F; Dipartimento di Scienza e Tecnologia del Farmaco, Università di Torino , I-10125 Turin, Italy.
  • Guglielmetti A; Dipartimento di Scienza e Tecnologia del Farmaco, Università di Torino , I-10125 Turin, Italy.
  • Liberto E; Dipartimento di Scienza e Tecnologia del Farmaco, Università di Torino , I-10125 Turin, Italy.
  • Reichenbach SE; Department of Computer Science and Engineering, University of Nebraska-Lincoln , Lincoln, Nebraska 68588-0115, United States.
  • Allegrucci E; Guido Gobino Srl , 10153 Turin, Italy.
  • Gobino G; Guido Gobino Srl , 10153 Turin, Italy.
  • Bicchi C; Dipartimento di Scienza e Tecnologia del Farmaco, Università di Torino , I-10125 Turin, Italy.
  • Cordero C; Dipartimento di Scienza e Tecnologia del Farmaco, Università di Torino , I-10125 Turin, Italy.
J Agric Food Chem ; 65(30): 6329-6341, 2017 Aug 02.
Article em En | MEDLINE | ID: mdl-28682071
ABSTRACT
This study investigates chemical information of volatile fractions of high-quality cocoa (Theobroma cacao L. Malvaceae) from different origins (Mexico, Ecuador, Venezuela, Columbia, Java, Trinidad, and Sao Tomè) produced for fine chocolate. This study explores the evolution of the entire pattern of volatiles in relation to cocoa processing (raw, roasted, steamed, and ground beans). Advanced chemical fingerprinting (e.g., combined untargeted and targeted fingerprinting) with comprehensive two-dimensional gas chromatography coupled with mass spectrometry allows advanced pattern recognition for classification, discrimination, and sensory-quality characterization. The entire data set is analyzed for 595 reliable two-dimensional peak regions, including 130 known analytes and 13 potent odorants. Multivariate analysis with unsupervised exploration (principal component analysis) and simple supervised discrimination methods (Fisher ratios and linear regression trees) reveal informative patterns of similarities and differences and identify characteristic compounds related to sample origin and manufacturing step.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Sementes / Cacau / Compostos Orgânicos Voláteis / Cromatografia Gasosa-Espectrometria de Massas Tipo de estudo: Evaluation_studies / Prognostic_studies País como assunto: America do sul Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Sementes / Cacau / Compostos Orgânicos Voláteis / Cromatografia Gasosa-Espectrometria de Massas Tipo de estudo: Evaluation_studies / Prognostic_studies País como assunto: America do sul Idioma: En Ano de publicação: 2017 Tipo de documento: Article