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Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue

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Abstract

Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactory–gustatory sensations). However, it is not guaranteed that trained panelist can correctly classify monovarietal extra-virgin olive oils according to olive cultivar. In this work, the potential application of human (sensory panelists) and artificial (electronic tongue) sensory evaluation of olive oils was studied aiming to discriminate eight single-cultivar extra-virgin olive oils. Linear discriminant, partial least square discriminant, and sparse partial least square discriminant analyses were evaluated. The best predictive classification was obtained using linear discriminant analysis with simulated annealing selection algorithm. A low-level data fusion approach (18 electronic tongue signals and nine sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination.

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Acknowledgments

This work was co-financed by FCT/MEC and FEDER under Program PT2020 (Project UID/EQU/50020/2013); by Fundação para a Ciência e Tecnologia under the strategic funding of UID/BIO/04469/2013 unit; and by Project POCTEP through Project RED/AGROTEC—Experimentation network and transfer for development of agricultural and agro industrial sectors between Spain and Portugal.

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Authors and Affiliations

  1. Escola Superior Agrária, Instituto Politécnico de Bragança, Campus Santa Apolónia, Apartado 1172, 5301-855, Bragança, Portugal

    Luís G. Dias

  2. CQ-VR, Centro de Química – Vila Real, University of Trás-os-Montes e Alto Douro, Apartado 1013, 5001-801, Vila Real, Portugal

    Luís G. Dias

  3. CIMO - Mountain Research Centre, Escola Superior Agrária, Instituto Politécnico de Bragança, Campus Santa Apolónia, Apartado 1172, 5301-855, Bragança, Portugal

    Nuno Rodrigues & José A. Pereira

  4. Instituto Politécnico de Coimbra, ISEC, DEQB, Rua Pedro Nunes, Quinta da Nora, 3030-199, Coimbra, Portugal

    Ana C. A. Veloso

  5. CEB - Centre of Biological Engineering, University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal

    Ana C. A. Veloso

  6. LSRE - Laboratory of Separation and Reaction Engineering - Associate Laboratory LSRE/LCM, Escola Superior Agrária, Instituto Politécnico de Bragança, Campus Santa Apolónia, Apartado 1172, 5301-855, Bragança, Portugal

    António M. Peres

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  1. Luís G. Dias
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  2. Nuno Rodrigues
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  3. Ana C. A. Veloso
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  4. José A. Pereira
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  5. António M. Peres
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Correspondence to António M. Peres.

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Dias, L.G., Rodrigues, N., Veloso, A.C.A. et al. Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue. Eur Food Res Technol 242, 259–270 (2016). https://doi.org/10.1007/s00217-015-2537-4

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  • DOI: https://doi.org/10.1007/s00217-015-2537-4

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