Marone Elettra, Masi Elisa, Taiti Cosimo, Pandolfi Camilla, Bazihizina Nadia, Azzarello Elisa, Fiorino Piero, Mancuso Stefano
Faculty of Biosciences and Technologies for Agriculture Food and Environment, University of Teramo, Via R. Balzarini, 1, 64100 Teramo, Italy.
Department of Agrifood Production and Environmental Science, University of Florence, Viale delle Idee, 30, 50019 Sesto Fiorentino, Florence Italy.
J Food Sci Technol. 2017 May;54(6):1368-1376. doi: 10.1007/s13197-017-2541-8. Epub 2017 Apr 1.
Olive oil samples were obtained from six cultivars grown in different environments, and graded by chemical analyses as extra virgin (EVOOs). These were evaluated for flavors and off-flavors, and relative VOCs spectrum as determined by PTR-ToF-MS. A hierarchical clustering of Panel test data separated olive oil in three groups, one including the samples with perceived off-flavor (VOOs), regardless of cultivar and environment. The Pearson's correlation coefficients between the mass data from PTR-ToF-MS and the sensory characteristics perceived by the Panel test were determined. A mass-to-sensory attributes correlation index was calculated. A color-coded card was built up based on the intensities (ncps) of five selected protonated mass data that was able to distinguish EVOOs from VOOs olive oil samples.
橄榄油样本取自生长于不同环境的六个品种，并通过化学分析评定为特级初榨橄榄油（EVOOs）。对这些样本进行风味和异味评估，并通过质子转移反应-飞行时间质谱（PTR-ToF-MS）测定其相对挥发性有机化合物（VOCs）光谱。感官测试数据的层次聚类将橄榄油分为三组，其中一组包括有异味的样本（VOOs），无论品种和生长环境如何。测定了PTR-ToF-MS的质量数据与感官测试所感知的感官特征之间的皮尔逊相关系数。计算了质量与感官属性的相关指数。基于五个选定的质子化质量数据的强度（ncps）构建了一张颜色编码卡片，该卡片能够区分特级初榨橄榄油和有异味的橄榄油样本。
