Simultaneous Origin Discrimination and Sensory Prediction of Cocoa with UHPLC-HRMS

A joint study by the University of Parma (Italy) and the Ferrero Group (Alba, Italy) focused on identifying molecular markers capable of discriminating between different origins of cocoa, and, simultaneously, effectively modeling and predicting specific sensory attributes through a sensomics approach combining data from untargeted ultra-high performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) analysis and sensory data. A paper based on this research was recently published in Food Chemistry (1).

Derived from the seeds contained in the pods of the cocoa tree (Theobroma cacao), cocoa is a raw material of tropical origin. The most commercially important varieties are Forastero (representing around 80% of the cultivated varieties), Criollo (representing just under 5%) and Trinitario (a hybrid between Forastero and Criollo, representing around 15%) (2). In Europe, mono-origin chocolate products are gaining more market because these products are perceived by consumers as more valuable, high quality, and sustainable, characterized by “unique” sensory attributes. This trend is not destined to decrease soon, the “premium” segment is increasingly offered among retailers (3). In parallel with the interest in mono-origin chocolate, several analytical strategies have been adopted to recognize and discriminate the different origins of cocoa and ensure its authenticity, such as Raman and Fourier transform infrared spectroscopy (FT-IR), mineral element and isotope profiles, DNA barcoding and fingerprinting based approaches (4,5).

Cocoa beans for the study were selected from six different geographical origins, coming from two of the most productive areas in the world: Latin America and West Africa. For each origin, one batch was selected by the industrial partner, which includes a mix of cocoa beans from different farmers of the geographical area. For Nigeria and Ghana, two different batches (old and new) were selected each. Because it was crucial to be able to identify any origin and sensorial differentiations in the final edible consumer product, from each cocoa beans batch, dark chocolate bars were produced using uniform and standardized process conditions (1).

Results showed that 71 origin-discriminant markers from the HRMS dataset that were selected by orthogonal partial least squares discriminant analysis (OPLS-DA)

as the most influential in discriminating cocoa origins were globally strongly correlated to the sensory descriptors (sweet, flowers/honey, sour, bitter, astringent, roasted/coffee), allowing their prediction. The researchers believe that this explains how the discriminations observed for the origins can be attributed to differences in the sensory profile of the samples. For many of these compounds, such as flavonoids, alkaloids, coumarins, lignans, lactones, terpenoids and oligopeptides, the researchers state that a sensory effect has been reported in the literature, often attributable to bitter and astringent. Therefore, the use of UHPLC-HRMS allowed the modeling of sensory attributes such as astringent and bitter, which are typically linked to non-volatile molecules, thus providing an effective and complementary tool to the analyses of volatile molecules in sensomics (1).

Cocoa powder in a brown ceramic bowl, with raw cocoa beans. © iprachenko - stock.adobe.com

References

1. Spataro, F.; Rosso, F.; Peraino, A.; Arese, C.; Caligiani, A. Key Molecular Compounds for Simultaneous Origin Discrimination and Sensory Prediction of Cocoa: An UHPLC-HRMS Sensomics Approach. Food Chem. 2024, 12 (463 [Pt 2]), 141201. DOI: 10.1016/j.foodchem.2024.141201

2. Bermúdez, S.; Voora, V.; Larrea, C.; Luna, E. Global Market Report: Cocoa Prices and Sustainability. International Institute for Sustainable Development 2022.https://www.iisd.org/publications/report/2022-global-market-report-cocoa(accessed 2024-03-21).

3. Which Trends Offer Opportunities or Pose Threats in the European Cocoa Market? Centre for the Promotion of Imports from Developing Countries 2022. https://www.cbi.eu/market-information/cocoa/trends (accessed 2024-03-21).

4. Perez, M.; Lopez-Yerena, A. Vallverdú-Queralt. Traceability, Authenticity and Sustainability of Cocoa and Chocolate Products: A Challenge for the Chocolate Industry. Critical Reviews in Food Science and Nutrition2022, 62 (2), 475-489. DOI: 10.1080/10408398.2020.1819769

5. Sentellas, S.; Saurina, J. Authentication of Cocoa Products Based on Profiling and Fingerprinting Approaches: Assessment of Geographical, Varietal, Agricultural and Processing Features. Foods 2023,12 (16), 3120 DOI: 10.3390/foods12163120