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Determination of Bitterness of Extra Virgin Olive Oils by Amperometric Detection

机译：电流检测测定特级初榨橄榄油的苦味

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摘要

A flow injection system with amperometric detection at potentials poised at + 0.4 and + 0.9V was used to evaluate intensity of the bitter taste in monovarietal Extra Virgin Olive Oils (EVOO). Results from the proposed method were based on the extraction of the bitter constituents of the virgin olive oil samples in methanolwater, followed by the direct amperometric measurement. These potentials were selected according to the hydrodynamic voltammogram of oleuropein, one of the most prominent and bitter phenolic compound found in EVOO. The amperometric detection was applied on 32 monovariatal EVOO samples. Results were correlated with the phenolic profile measured by high performance liquid chromatography (HPLC). The amperometric signal at + 0.9V mainly correlated with the total phenols of the samples (R-2 = 0.81), whereas the signal at + 0.4V mainly correlated with oleuropein aglycone (3,4 DHPEA-EDA, R-2 = 0.79). Bitterness intensity of the samples was evaluated by a trained sensory panel of experts and the results compared to those obtained by the amperometric flow system. The best correlation with the bitter taste was achieved by the sensor at + 0.4V (R-2 = 0.72). A calibration model based on partial least squares was built with three variables, namely the sensors set at + 0.4 and + 0.9 V and the total phenol content of the EVOO extracts. The model showed a moderate capacity to predict the bitterness of the EVOO samples using leave one out method, (R-2 = 0.75) and in prediction of a test set of samples (R-2 = 0.7). Such approach is very promising for future studies.
机译：在+ 0.4和+ 0.9V下的电位下具有安培检测的流动喷射系统用于评估单体植物橄榄油（EVOO）中苦味的强度。所提出的方法的结果是基于甲醇水中初榨橄榄油样品的苦味成分的提取，其次是直接排水测量。根据Oleuropein的流体动力学伏安图选择这些电位，在Evoo中发现的最突出和苦酚类化合物之一。在32个单亚聚物evoo样品上施加安培测量检测。结果与通过高效液相色谱（HPLC）测量的酚醛曲线相关。在+ 0.9V的顺化信号主要与样品的总酚（R-2 = 0.81）相关，而AT + 0.4V的信号主要与油孔蛋白糖苷酮（3,4 dhpea-EDA，R-2 = 0.79）相关。与由电流流动系统获得的那些相比，通过训练有素的专家的感官板和结果评估样品的苦味强度。通过+ 0.4V（R-2 = 0.72）的传感器实现与苦味的最佳相关性。基于部分最小二乘的校准模型用三个变量构建，即设定为+ 0.4和+ 0.9 V的传感器以及Evoo提取物的总酚含量。该模型显示使用留出一个OUT方法来预测EVOO样品的苦涩的中等能力，（R-2 = 0.75）并预测样品的测试组（R-2 = 0.7）。这种方法对于未来的研究非常有前途。

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