An iterative selection algorithm: A decision aid to select the best extra virgin olive oils competing in an international contest

Fabien Girard (1, 2) , Jacques Artaud (2) , Christian Pinatel (3) , Magalie Claeys-Bruno (2) , Catherine Rébufa (2)

1 AMU - Aix Marseille Université
2 IMBE - Institut méditerranéen de biodiversité et d'écologie marine et continentale
3 Maison des Agriculteurs

Extra virgin olive oils (EVOO) are typically categorized in accordance with the nature of their fruitiness (green or ripe) and the intensity of their fruitiness (delicate, medium, or robust) in accordance with the proposal of the competitor (producers) or a chemical analysis certificate established by an official panel. Depending on the category in which EVOO participates, its categorization may either disadvantage or benefit its rating. To eliminate this ambiguity and maximize an EVOO's probability of winning, the jury of the International "Word Edible Oils" competition use an innovative method to assess the EVOOs using a restricted amount of sensory descriptors (aromatic maturity, structure and fruitiness). Independent of category, the best EVOOs with comparable organoleptic properties have been identified using a statistical processing of the scores of the three descriptors. This is an iterative version of the technique developed by Wootton, Sergent, and Phan-Tan-Luu (iWSP), which generates subspaces that enable a local selection of the best EVOOs in a 2D aromatic maturity vs structure plan. In each subspace, their ranking is determined by their fruitiness score. An iterative approach that takes into consideration the changing sequence of subspace formation and the varying size of the subspace enables the selection of the best EVOOs. The development of the iWSP algorithm enabled the elimination of category constraints, (ii) the selection of the best EVOOs among those with comparable organoleptic features based on a large number of simulations, and (iii) the creation of a ranking to aid the jury's final judgment.

Mots clés: Selection algorithm; Extra virgin olive oil; Descriptors; International competition

Domaines: Chimie; Statistiques [stat]

Fabien Girard, Jacques Artaud, Christian Pinatel, Magalie Claeys-Bruno, Catherine Rébufa. An iterative selection algorithm: A decision aid to select the best extra virgin olive oils competing in an international contest. Food Control, 2023, 151, pp.109776. ⟨10.1016/j.foodcont.2023.109776⟩. ⟨hal-04074757⟩