Background: The organoleptic profile of an olive oil is a fundamental quality parameter obtained by human sensory panels. In this work, a portable electronic nose was employed to predict the fruity aroma intensity of 199 olive oil samples from different Spanish regions and cultivar varieties (Picual, Arbequina and Cornicabra), with special emphasis in testing the robustness of the predictions versus cultivar variety variability. The primary data given by the electronic-nose was used to obtain two different feature vectors that were employed to fit ridge and lasso regressions models to two datasets: one consisting of all the samples and another just the cv. Picual samples. Results: The results obtained showed Mean Average Error (MAE) values below 0.88 in all the cases, with a MAE of 0.67 for the Picual model. These MAE values and the similarities in the model parameters fitted for the different data folds are in agreement with the results obtained in previous works. Conclusion: The large number of samples analyzed and the results obtained show the robustness of the approach and the applicability of the methods. Also, the results suggest that better performance can be obtained when specific models are fitted for particular cultivar varieties. Overall, the proposed methods are capable of providing useful information for a fast screening of the fruity aroma intensity of olive oils. This article is protected by copyright. All rights reserved.
Assessment of Fruity Aroma Intensity in Olive Oils from Different Spanish Regions Using a Portable Electronic Nose
Bianchi, Alessandro;Mencarelli, FabioPenultimo
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2023-01-01
Abstract
Background: The organoleptic profile of an olive oil is a fundamental quality parameter obtained by human sensory panels. In this work, a portable electronic nose was employed to predict the fruity aroma intensity of 199 olive oil samples from different Spanish regions and cultivar varieties (Picual, Arbequina and Cornicabra), with special emphasis in testing the robustness of the predictions versus cultivar variety variability. The primary data given by the electronic-nose was used to obtain two different feature vectors that were employed to fit ridge and lasso regressions models to two datasets: one consisting of all the samples and another just the cv. Picual samples. Results: The results obtained showed Mean Average Error (MAE) values below 0.88 in all the cases, with a MAE of 0.67 for the Picual model. These MAE values and the similarities in the model parameters fitted for the different data folds are in agreement with the results obtained in previous works. Conclusion: The large number of samples analyzed and the results obtained show the robustness of the approach and the applicability of the methods. Also, the results suggest that better performance can be obtained when specific models are fitted for particular cultivar varieties. Overall, the proposed methods are capable of providing useful information for a fast screening of the fruity aroma intensity of olive oils. This article is protected by copyright. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.