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Checking quality of sensory data via an agreement-based approach

Author

Listed:
  • Amalia Vanacore

    (University of Naples “Federico II”)

  • Maria Sole Pellegrino

    (University of Naples “Federico II”)

Abstract

Sensory evaluations are adopted in many fields for measuring and comparing sensory properties of products and improving their quality. The selection of panelists able to provide precise evaluations is a crucial issue to perform reliable sensory analysis. An agreement-based approach is here suggested in order to assess the quality of sensory data in terms of both panelist repeatability and panel reproducibility. The approach has been applied to two case studies involving untrained sensory panelists and trained teaching quality assessors, respectively. The results of the case studies show that although reproducibility can be assumed moderate for both groups of raters, repeatability is generally higher for the group of trained raters.

Suggested Citation

  • Amalia Vanacore & Maria Sole Pellegrino, 2019. "Checking quality of sensory data via an agreement-based approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2545-2556, September.
    • Handle: RePEc:spr:qualqt:v:53:y:2019:i:5:d:10.1007_s11135-018-0807-5
    DOI: 10.1007/s11135-018-0807-5
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    References listed on IDEAS

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    1. Tamar Gadrich & Emil Bashkansky & Ričardas Zitikis, 2015. "Assessing variation: a unifying approach for all scales of measurement," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 1145-1167, May.
    2. Michel Tenenhaus & L. Ambroisine & C. Guinot & J. Latreille & E. Mauger & M. Vincent & S. Navarro, 2006. "Measurement of the reliability of sensory panel performances," Post-Print halshs-00119591, HAL.
    3. Maria Iannario & Marica Manisera & Domenico Piccolo & Paola Zuccolotto, 2012. "Sensory analysis in the food industry as a tool for marketing decisions," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 6(4), pages 303-321, December.
    4. de Mast, Jeroen, 2007. "Agreement and Kappa-Type Indices," The American Statistician, American Statistical Association, vol. 61, pages 148-153, May.
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