CESAM/Chemistry Department, University of Aveiro, 3810-193 Aveiro, Portugal.
Anal Bioanal Chem. 2010 Aug;397(7):3051-60. doi: 10.1007/s00216-010-3885-3. Epub 2010 Jun 15.
An electronic tongue (ET) based on potentiometric chemical sensors was assessed as a rapid tool for the quantification of bitterness in red wines. A set of 39 single cultivar Pinotage wines comprising 13 samples with medium to high bitterness was obtained from the producers in West Cape, South Africa. Samples were analysed with respect to a set of routine wine parameters and major phenolic compounds using Fourier transform infrared-multiple internal reflection spectroscopy (WineScan) and high-performance liquid chromatography, respectively. A trained sensory panel assessed the bitterness intensity of 15 wines, 13 of which had a bitter taste of medium to high intensity. Thirty-one wine samples including seven bitter-tasting ones were measured by the ET. Influence of the chemical composition of wine on the occurrence of the bitter taste was evaluated using one-way analysis of variance. It was found that bitter-tasting wines had higher concentrations of phenolic compounds (catechin, epicatechin, gallic and caffeic acids and quercetin) than non-bitter wines. Sensitivity of the sensors of the array to the phenolic compounds related to the bitterness was studied at different pH levels. Sensors displayed sensitivity to all studied compounds at pH 7, but only to quercetin at pH 3.5. Based on these findings, the pH of wine was adjusted to 7 prior to measurements. Calibration models for classification of wine samples according to the presence of the bitter taste and quantification of the bitterness intensity were calculated by partial least squares-discriminant analysis (PLS-DA) regression. Statistical significance of the classification results was confirmed by the permutation test. Both ET and chemical analysis data could discriminate between bitter and control wines with the correct classification rates of 94% and 91%, respectively. Prediction of the bitterness intensity with good accuracy (root mean square error of 2 and mean relative error of 6% in validation) was possible only using ET data.
一种基于电位化学传感器的电子舌被评估为快速定量测定红葡萄酒苦味的工具。从南非西开普省的生产商那里获得了一组 39 种单一栽培品乐塔吉葡萄酒，其中包括 13 种具有中等到高度苦味的样品。使用傅里叶变换红外-多次内部反射光谱（WineScan）和高效液相色谱法分别对样品进行了一系列常规葡萄酒参数和主要酚类化合物的分析。一个经过培训的感官小组评估了 15 种葡萄酒的苦味强度，其中 13 种具有中等到高度强度的苦味。用 ET 测量了 31 种葡萄酒样品，其中包括 7 种苦味样品。使用单向方差分析评估了葡萄酒化学成分对苦味发生的影响。结果发现，苦味葡萄酒中酚类化合物（儿茶素、表儿茶素、没食子酸、咖啡酸和槲皮素）的浓度高于非苦味葡萄酒。研究了阵列传感器对与苦味相关的酚类化合物的敏感性在不同 pH 值下的变化。传感器在 pH 7 时对所有研究的化合物都敏感，但在 pH 3.5 时仅对槲皮素敏感。基于这些发现，在测量前将葡萄酒的 pH 值调整到 7。通过偏最小二乘判别分析（PLS-DA）回归计算了根据苦味存在和苦味强度定量分类葡萄酒样品的校准模型。通过置换检验确认了分类结果的统计学意义。电子舌和化学分析数据都可以区分苦味和对照葡萄酒，正确分类率分别为 94%和 91%。仅使用 ET 数据即可实现对苦味强度的准确预测（验证中的均方根误差为 2，平均相对误差为 6%）。
