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Discrimination of Cocoa Liquors Based on Their Odor Fingerprint: a Fast GC Electronic Nose Suitability Study

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Abstract

With the rising interest by consumers for high-quality cocoa products from a clear geographical origin, a rapid analytical method for quality control, authenticity and traceability assessment is of paramount importance. However, the complex mixture of volatiles present in cocoa liquor, the main ingredient for the chocolate production, complicates reaching this purpose. Hence, an analytical fingerprint approach using advanced electronic nose (E-nose) technology may offer a suitable technique. This study aimed to verify the suitability of an E-nose based on ultra-fast gas chromatography (GC) for the rapid discrimination between cocoa liquors from different origins. Fourteen cocoa liquors, produced of cocoa beans from ten different geographical origins, were analyzed. The obtained odor fingerprints were investigated using principal component analysis (PCA) which successfully discriminated most cocoa liquors, within one continent, according to their geographical origin. Besides, discriminant factor analysis (DFA) showed the possibility to differentiate between bulk and fine cocoa. Further tentative identification of predominant volatile compounds allowed the detection of compounds within a wide range of chemical classes occurring in cocoa products, such as acids, alcohols, aldehydes, ketones, esters, pyrazines, pyrones, and pyrroles. Most odorant compounds were previously described in literature as key volatiles in cocoa flavor, notable examples are acetic acid, 2-heptanol, 2/3-methylbutanal, acetophenone, isoamyl acetate, tetramethylpyrazine, maltol, and 2-acetyl-1-pyrroline. This study proves for the first time the usefulness of the GC E-nose for effective and rapid aroma profiling and discrimination between single origin cocoa liquors, which can be easily applied in the cocoa industry.

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Acknowledgments

The authors would like to thank CacaoLab (Ghent Belgium), Cimarron Cocoa Estates (Ecuador), Candy Ruiz (Peru), Fondo Nacional del cacao (FEDECACAO, Colombia), Luciana Monteiro and Marcello Ortolano (Brazil), Esco Kivu Sprl (Congo), Dr. Phuoc Hong Duc Pham and Dr. Tăng Kim Hồng from Center for Forestry Research and Technology Transfer (CEFFORT), Nong Lam University (NLU) (Vietnam), Consolidated Agriventures Corp. (AGCOR) and Joel Juvinal (Philippines) for providing the cocoa bean samples. Further, we are grateful to Katharina Riehn, Christina Krabbe, and Stephanie Nottelmann from Group Hamburg University of Applied Sciences, Hamburg, Germany for technical assistance during cocoa liquor production.

Funding

Financial support for this research was obtained from BOF (Special Research Fund) of Ghent University (PhD grant). BOF is further recognized for its financial support in the acquisition of the Heracles II GC E-nose (grant nr. BOF 01B05915).

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Authors and Affiliations

  1. Department of Food Technology, Safety and Health, Laboratory of Food Technology and Engineering, Ghent University, Coupure links 653, 9000, Ghent, Belgium

    Hayley Rottiers, Daylan Amelia Tzompa Sosa, Liesbet Van de Vyver, Michael Hinneh, Helena Everaert & Koen Dewettinck

  2. Department of Biotechnology, Laboratory AgriFing, Faculty of Bioscience Engineering, Ghent University, Valentin Vaerwyckweg 1, 9000, Ghent, Belgium

    Hayley Rottiers, Helena Everaert, Jocelyn De Wever & Kathy Messens

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  1. Hayley Rottiers
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Correspondence to Hayley Rottiers.

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Hayley Rottiers declares that she has no conflict of interest. Daylan Amelia Tzompa Sosa declares that she has no conflict of interest. Liesbet Van de Vyver declares that she has no conflict of interest. Michael Hinneh declares that he has no conflict of interest. Helena Everaert declares that she has no conflict of interest. Jocelyn De Wever declares that she has no conflict of interest. Kathy Messens declares that she has no conflict of interest. Koen Dewettinck declares that he has no conflict of interest.

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Rottiers, H., Tzompa Sosa, D.A., Van de Vyver, L. et al. Discrimination of Cocoa Liquors Based on Their Odor Fingerprint: a Fast GC Electronic Nose Suitability Study. Food Anal. Methods 12, 475–488 (2019). https://doi.org/10.1007/s12161-018-1379-7

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