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

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.

[1]  Yejun Xu,et al.  Approaches based on 2-tuple linguistic power aggregation operators for multiple attribute group decision making under linguistic environment , 2011, Appl. Soft Comput..

[2]  Hari Niwas Mishra,et al.  SENSORY EVALUATION OF DIFFERENT DRINKS FORMULATED FROM DAHI (INDIAN YOGURT) POWDER USING FUZZY LOGIC , 2012 .

[3]  Francisco Herrera,et al.  Computing with Words in Decision support Systems: An overview on Models and Applications , 2010, Int. J. Comput. Intell. Syst..

[4]  Yan Chen,et al.  Optimisation of garment design using fuzzy logic and sensory evaluation techniques , 2009, Eng. Appl. Artif. Intell..

[5]  Garmt Dijksterhuis Multivariate data analysis in sensory and consumer science , 1997 .

[6]  Francisco Herrera,et al.  A Fuzzy Linguistic Methodology to Deal With Unbalanced Linguistic Term Sets , 2008, IEEE Transactions on Fuzzy Systems.

[7]  G. W. Wei,et al.  Some harmonic Aggregation Operators with 2-Tuple Linguistic Assessment Information and their Application to Multiple Attribute Group Decision Making , 2011, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[8]  Macarena Espinilla,et al.  An Evaluation Model with Unbalanced Linguistic Information Applied to Olive Oil Sensory Evaluation , 2009, J. Multiple Valued Log. Soft Comput..

[9]  Wei Yang,et al.  New aggregation operators based on the Choquet integral and 2-tuple linguistic information , 2012, Expert Syst. Appl..

[10]  S. Jaya,et al.  SENSORY EVALUATION OF MANGO DRINKS USING FUZZY LOGIC , 2003 .

[11]  Lotfi A. Zadeh,et al.  The Concepts of a Linguistic Variable and its Application to Approximate Reasoning , 1975 .

[12]  H. Mishra,et al.  Fuzzy Analysis of Sensory Data for Quality Evaluation and Ranking of Instant Green Tea Powder and Granules , 2011 .

[13]  N. Perrota,et al.  Fuzzy concepts applied to food product quality control : A review , 2015 .

[14]  Lucia Russo,et al.  A neuro‐fuzzy computational approach for multicriteria optimisation of the quality of espresso coffee by pod based on the extraction time, temperature and blend , 2012 .

[15]  L. A. ZADEH,et al.  The concept of a linguistic variable and its application to approximate reasoning - I , 1975, Inf. Sci..

[16]  Xianyi Zeng,et al.  Intelligent Sensory Evaluation , 2004 .

[17]  Luis Martínez,et al.  Sensory evaluation based on linguistic decision analysis , 2007 .

[18]  Francisco Herrera,et al.  A 2-tuple fuzzy linguistic representation model for computing with words , 2000, IEEE Trans. Fuzzy Syst..

[19]  Seung Ju Lee,et al.  Study on fuzzy reasoning application for sensory evaluation of sausages , 2007 .

[20]  Luuk Fleskens,et al.  Olive production systems on sloping land: prospects and scenarios. , 2008, Journal of environmental management.

[21]  E. Blery,et al.  Marketing olive oil in Greece , 2008 .

[22]  Francisco Herrera,et al.  A model based on linguistic 2-tuples for dealing with multigranular hierarchical linguistic contexts in multi-expert decision-making , 2001, IEEE Trans. Syst. Man Cybern. Part B.

[23]  Xianyi Zeng,et al.  Intelligent Sensory Evaluation: Methodologies and Applications , 2004 .

[24]  Francisco Herrera,et al.  An overview on the 2-tuple linguistic model for computing with words in decision making: Extensions, applications and challenges , 2012, Inf. Sci..