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 twodimensional 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.

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;BICCHI, Carlo;CORDERO, Chiara Emilia Irma
Last
2017-01-01

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 twodimensional 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.
2017
6329
6341
Theobroma cacao L., combined untargeted and targeted fingerprinting, comprehensive two-dimensional gas chromatography-mass spectrometry, classification and discrimination models, key-aroma compounds
Magagna, Federico; Guglielmetti, Alessandro; Liberto, Erica; Reichenbach, Stephen E.; Allegrucci, Elena; Gobino, Guido; Bicchi, Carlo; Cordero, Chiara...espandi
File in questo prodotto:
File Dimensione Formato  
acs.jafc.7b02167.pdf

Accesso riservato

Descrizione: full text
Tipo di file: PDF EDITORIALE
Dimensione 3.6 MB
Formato Adobe PDF
3.6 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Post-print Manuscript_OA.pdf

Open Access dal 19/07/2018

Descrizione: Post-print Manuscript_OA
Tipo di file: POSTPRINT (VERSIONE FINALE DELL’AUTORE)
Dimensione 1.68 MB
Formato Adobe PDF
1.68 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1645266
Citazioni
  • ???jsp.display-item.citation.pmc??? 10
  • Scopus 59
  • ???jsp.display-item.citation.isi??? 54
social impact