A New Unbalanced Linguistic Scale for the Classification of Olive Oil Based on the Fuzzy Linguistic Approach

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 213)

Abstract

A key factor that determines the price of olive oil is its sensory profile. The International Olive Council (IOC) establishes four quality categories and a method to classify a sample of olive oil into one category, depending on its sensory characteristics. To do so, a taster panel is rigorously trained to provide the intensity perceived on a 10-cm scale for each organoleptic characteristic. These intensities are aggregated and analyzed statistically to obtain the classification among one of four quality categories established. The modeling and management of perceptions in sensory evaluation processes is an important problem because the information acquired by human senses always involves imprecision and uncertainty that has a non-probabilistic nature. The application of the fuzzy linguistic approach to sensory evaluation processes can model and manage the uncertainty and vagueness of this kind of processes. The main challenge in this approach is to establish a linguistic scale to measure tasters’ perceptions, since the success or failure of the sensory evaluation process will depend on the definition of a proper scale. In this contribution is analyzed and proposed an unbalanced linguistic scale to carry out the classification of olive oil samples, such a scale is validated, conducting a sensory evaluation case study for olive oil.

Keywords

Sensory evaluation Fuzzy linguistic approach Unbalanced linguistic scale Olive oil Linguistic 2-tuple. 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Department of Computer SciencesUniversity of JaenJaénSpain

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