Biancolillo Alessandra, Preys Sébastien, Gaci Belal, Le Quéré Jean-Luc, Labouré Hélène, Deuscher Zoé, Cheynier Véronique, Sommerer Nicolas, Fayeulle Noémie, Costet Pierre, Hue Clotilde, Boulanger Renaud, Alary Karine, Lebrun Marc, Lahon Marie-Christine, Morel Gilles, Maraval Isabelle, Davrieux Fabrice, Roger Jean-Michel. 2021. Multi-block classification of chocolate and cocoa samples into sensory poles. Food Chemistry, 340:127904, 9 p.
Version publiée
- Anglais
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Quartile : Q1, Sujet : CHEMISTRY, APPLIED / Quartile : Q1, Sujet : FOOD SCIENCE & TECHNOLOGY / Quartile : Q1, Sujet : NUTRITION & DIETETICS
Résumé : The present study aims at developing an analytical methodology which allows correlating sensory poles of chocolate to their chemical characteristics and, eventually, to those of the cocoa beans used for its preparation. Trained panelists investigated several samples of chocolate, and they divided them into four sensorial poles (characterized by 36 different descriptors) attributable to chocolate flavor. The same samples were analyzed by six different techniques: Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS), Solid Phase Micro Extraction-Gas Chromatography-Mass Spectroscopy (SPME-GC-MS), High-Performance Liquid Chromatography (HPLC) (for the quantification of eight organic acids), Ultra High Performance Liquid Chromatography coupled to triple-quadrupole Mass Spectrometry (UHPLC-QqQ-MS) for polyphenol quantification, 3D front face fluorescence Spectroscopy and Near Infrared Spectroscopy (NIRS). A multi-block classification approach (Sequential and Orthogonalized-Partial Least Squares – SO-PLS) has been used, in order to exploit the chemical information to predict the sensorial poles of samples. Among thirty-one test samples, only two were misclassified.
Mots-clés Agrovoc : propriété organoleptique, analyse organoleptique, fève de cacao, chocolat, composition chimique, chromatographie, spectroscopie
Mots-clés libres : Chocolate, Cocoa beans, Multi-block, Spectroscopy, Chromatography, Classification, Sensory analysis
Classification Agris : Q04 - Composition des produits alimentaires
Q01 - Sciences et technologies alimentaires - Considérations générales
U30 - Méthodes de recherche
Champ stratégique Cirad : CTS 3 (2019-) - Systèmes alimentaires
Auteurs et affiliations
- Biancolillo Alessandra, Université de l'Aquila (ITA) - auteur correspondant
- Preys Sébastien, ONDALYS (FRA)
- Gaci Belal, INRAE (FRA)
- Le Quéré Jean-Luc, CNRS (FRA)
- Labouré Hélène, CNRS (FRA)
- Deuscher Zoé, CIRAD-PERSYST-UMR Qualisud (FRA) ORCID: 0000-0003-0660-676X
- Cheynier Véronique, INRAE (FRA)
- Sommerer Nicolas, INRAE (FRA)
- Fayeulle Noémie, INRAE (FRA)
- Costet Pierre, Chocolaterie Valrhona (FRA)
- Hue Clotilde, Chocolaterie Valrhona (FRA)
- Boulanger Renaud, CIRAD-PERSYST-UMR Qualisud (FRA) ORCID: 0000-0001-9396-5634
- Alary Karine, CIRAD-PERSYST-UMR Qualisud (FRA)
- Lebrun Marc, CIRAD-PERSYST-UMR Qualisud (FRA)
- Lahon Marie-Christine, CIRAD-PERSYST-UMR Qualisud (FRA)
- Morel Gilles, CIRAD-PERSYST-UMR Qualisud (FRA)
- Maraval Isabelle, CIRAD-PERSYST-UMR Qualisud (FRA)
- Davrieux Fabrice, CIRAD-PERSYST-UMR Qualisud (REU)
- Roger Jean-Michel, INRAE (FRA)
Source : Cirad-Agritrop (https://agritrop.cirad.fr/598703/)
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