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Link between Flavor Perception and Volatile Compound Composition of Dark Chocolates Derived from Trinitario Cocoa Beans from Dominican Republic
Santiago Guzmán Penella, Renaud Boulanger, Isabelle Maraval, Gabi Kopp, Marcello Corno, Bénédicte Fontez, Angélique Fontana

Link between Flavor Perception and Volatile Compound Composition of Dark Chocolates Derived from Trinitario Cocoa Beans from Dominican Republic

Science & Mathematics Published 2023 Verification Pending

Overview & Synopsis

The chemical composition of dark chocolate has a significant impact on its complex flavor profile. This study aims to investigate the relationship between the volatile chemical composition and perceived flavor of 54 dark chocolate samples made from Trinitario cocoa beans from the Dominican Republic. The samples were evaluated by a trained panel and analyzed using gas chromatography-mass spectrometry (GC-MS) to identify and quantify the volatile compounds. Predictive models based on a partial least squares regression (PLS) allowed the identification of key compounds for predicting individual sensory attributes. The models were most successful in classifying samples based on the intensity of bitterness and astringency, even though these attributes are mostly linked to non-volatile compounds. Acetaldehyde, dimethyl sulfide, and 2,3-butanediol were found to be key predictors for various sensory attributes, while propylene glycol diacetate was identified as a possible marker for red fruit aroma. The study highlights the potential of using volatile compounds to accurately predict chocolate flavor potential.

Indexed from repository: HAL Open Science (hal.science)
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Document Information

Document Title Link between Flavor Perception and Volatile Compound Composition of Dark Chocolates Derived from Trinitario Cocoa Beans from Dominican Republic
Author / Organization Santiago Guzmán Penella, Renaud Boulanger, Isabelle Maraval, Gabi Kopp, Marcello Corno, Bénédicte Fontez, Angélique Fontana
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2023
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-156621
Original Source Link Visit Source Page on hal.science »