Nowadays, the check of the organoleptic characteristics for the evaluation of extra virgin olive oil (EVOO) quality is regulated by the European Union (EU) authorities, which indicate the use of the panel test (PT). It is composed by a team of specialists that give a numerical value to many characteristics about flavours, synthesising a sensory analysis. Each expert answers questions about the aroma by assigning the adequate scores to each oil. The evaluation becomes objective by applying the statistical analysis of all the scores given by the participants: This is the definition of “measure” of Russell. The PT can be considered a true standard “metrological system” (considering the number of questions in the questionnaire), while the perceptions of the testers are the solicitations of it. To allow access to an expensive evaluation process by small companies, this work proposes to “disseminate” the properties of the metrology represented by PT. The results of the PT are arranged in an unsupervised artificial neural network (ANN), the Kohonen map, which represents the synthesis of self-organised output that has only the goal, in this paper, to make readable PT results. The dissemination process is obtained by the gas chromatographic (GC) analysis of each oil sample and through the identification of peaks corresponding to the perceptions. These signals are used for the training of the supervised Multi Layer Perceptron (MLP) ANN, with the back propagation algorithm, whose outputs are represented by the results of the PT. This procedure is exact a “metrological dissemination of a standard” and also the aim of the work: to classify EVOO without always resorting to PT.
