Department of Materials Science, Universidad de Valladolid, 47011 Valladolid, Spain.
Centro de Investigação de Montanha (CIMO), ESA, Instituto Politécnico de Bragança, 5301 Bragança, Portugal.
Sensors (Basel). 2020 Jul 27;20(15):4176. doi: 10.3390/s20154176.
A bio-electronic tongue has been developed to evaluate the phenolic content of grape residues (seeds and skins) in a fast and easy way with industrial use in mind. A voltammetric electronic tongue has been designed based on carbon resin electrodes modified with tyrosinase combined with electron mediators. The presence of the phenoloxydase promotes the selectivity and specificity towards phenols. The results of multivariate analysis allowed discriminating seeds and skins according to their polyphenolic content. Partial least squares (PLS) has been used to establish regression models with parameters related to phenolic content measured by spectroscopic methods i.e., total poliphenol content (TPC) and Folin-Ciocalteu (FC) indexes. It has been shown that electronic tongue can be successfully used to predict parameters of interest with high correlation coefficients (higher than 0.99 in both calibration and prediction) and low residual errors. These values can even be improved using genetic algorithms for multivalent analysis. In this way, a fast and simple tool is available for the evaluation of these values. This advantage may be due to the fact that the electrochemical signals are directly related to the phenolic content.
已经开发出一种生物电子舌，以便快速、轻松地评估葡萄残渣（种子和果皮）中的酚类含量，并着眼于工业用途。基于与电子介体结合的酪氨酸酶修饰的碳树脂电极设计了一种伏安电子舌。酚氧化酶的存在促进了对酚类物质的选择性和特异性。多元分析的结果允许根据其多酚含量对种子和果皮进行区分。偏最小二乘（PLS）已用于建立与通过光谱方法测量的酚类含量相关的参数的回归模型，即总多酚含量（TPC）和福林-希奥考尔特（FC）指数。结果表明，电子舌可以成功地用于预测具有高相关系数（在校准和预测中均高于 0.99）和低残差误差的相关参数。使用遗传算法进行多变量分析甚至可以提高这些值。通过这种方式，提供了一种快速简单的工具来评估这些值。这种优势可能是由于电化学信号与酚类含量直接相关。
