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Reliable discriminant analysis tool for controlling the roast degree of coffee samples through chemical markers approach

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Abstract

Roasting is one of the most influencing stages of coffee processing. Accordingly, a discriminant analysis (DA) was carried out with the objective of identifying key compounds (chemical markers) that enable a differentiation of coffee samples according to their roasting degree. For this, chromatographic data of the volatile fraction of 21 coffee samples submitted to distinct roasting treatments (Light, Medium, Dark, and French Roasts) were employed. Using three discriminant functions that rely on only ten chemical markers, it was possible to explain 100 % of the variance of the data points. If two functions are used, the surprisingly high value of 99.4 % is achieved. The model was cross-validated, and the main function successfully passed a permutation test using two statistical indicators. It was found that half of the markers belong to the pyrazines family, known to grant sensorial notes related to roasted hazelnut and peanuts. In the whole, this essay demonstrates the usefulness of DA as a tool to control the quality of roasting treatment of coffee and can be further extended with advantage to the eight roasting degrees of the AGTRON Roasting Classification as soon as larger databases become available.

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Acknowledgments

The authors thank the Brazilian National Research Council (CNPq) and the Coordination for the Improvement of Higher Level Personnel (CAPES) for financial support. This work was developed within the scope of the project CICECO-Aveiro Institute of Materials, POCI-01-0145-FEDER-007679 (FCT Ref. UID/CTM/50011/2013), financed by national funds through the FCT/MEC and when appropriate co-financed by FEDER under the PT2020 Partnership Agreement.

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Authors and Affiliations

  1. Institute of Chemistry, State University of São Paulo – UNESP, Araraquara, SP, 14800-060, Brazil

    Paulo R. A. B. de Toledo, Helena R. Pezza & Leonardo Pezza

  2. CICECO – Aveiro Institute of Materials, Department of Chemistry, University of Aveiro, Aveiro, 3810-193, Portugal

    Marcelo M. R. de Melo & Carlos M. Silva

  3. Latin American Institute of Science of Life and Nature, Federal University of Latin American Integration – UNILA, Foz do Iguaçú, PR, 85867-970, Brazil

    Aline T. Toci

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  1. Paulo R. A. B. de Toledo
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  2. Marcelo M. R. de Melo
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  3. Helena R. Pezza
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  5. Aline T. Toci
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Correspondence to Carlos M. Silva.

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de Toledo, P.R.A.B., de Melo, M.M.R., Pezza, H.R. et al. Reliable discriminant analysis tool for controlling the roast degree of coffee samples through chemical markers approach. Eur Food Res Technol 243, 761–768 (2017). https://doi.org/10.1007/s00217-016-2790-1

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