Bianchi Alessandro, Cano Marchal Pablo, Martínez Gila Diego M, Mencarelli Fabio, Gámez García Javier
Department of Agriculture, Food and Environment, University of Pisa, Pisa, Italy.
University Institute of Research on Olive and Olive Oils (INUO), Electronics and Systems Engineering Department, University of Jaén, Jaén, Spain.
J Sci Food Agric. 2025 Feb;105(3):1448-1455. doi: 10.1002/jsfa.13179. Epub 2023 Dec 10.
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 were 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.
The results obtained showed mean average error (MAE) values below 0.88 in all cases, with an 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 studies.
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 cultivars. Overall, the proposed methods are capable of providing useful information for a fast screening of the fruity aroma intensity of olive oils. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
橄榄油的感官特征是通过人工感官小组获得的一个基本质量参数。在这项工作中，使用了一种便携式电子鼻来预测来自西班牙不同地区和品种（“皮夸尔”、“阿贝基纳”和“科尔尼卡布拉”）的199个橄榄油样品的果香强度，特别强调测试预测结果相对于品种变异性的稳健性。电子鼻给出的原始数据被用于获得两个不同的特征向量，这两个特征向量被用于将岭回归和套索回归模型拟合到两个数据集：一个由所有样品组成，另一个仅由皮夸尔品种的样品组成。
所获得的结果表明，在所有情况下平均绝对误差（MAE）值均低于0.88，“皮夸尔”模型的MAE为0.67。这些MAE值以及为不同数据折叠拟合的模型参数的相似性与先前研究中获得的结果一致。
分析的大量样品和获得的结果表明了该方法的稳健性和这些方法的适用性。此外，结果表明，为特定品种拟合特定模型时可以获得更好的性能。总体而言，所提出的方法能够为快速筛选橄榄油的果香强度提供有用信息。© 2023作者。《食品与农业科学杂志》由约翰·威利父子有限公司代表化学工业协会出版。
