Department of Food Quality Control and Nutrition, Faculty of Food Technology and Biotechnology, University of Zagreb, Pierottijeva 6, 10000 Zagreb, Croatia.
Talanta. 2010 Sep 15;82(4):1292-7. doi: 10.1016/j.talanta.2010.06.048. Epub 2010 Jul 6.
The paper reports on the application of an electronic tongue for simultaneous determination of ethanol, acetaldehyde, diacetyl, lactic acid, acetic acid and citric acid content in probiotic fermented milk. The alphaAstree electronic tongue by Alpha M.O.S. was employed. The sensor array comprised of seven non-specific, cross-sensitive sensors developed especially for food analysis coupled with a reference Ag/AgCl electrode. Samples of plain, strawberry, apple-pear and forest-fruit flavored probiotic fermented milk were analyzed both by standard methods and by the potentiometric sensor array. The results obtained by these methods were used for the development of neural network models for rapid estimation of aroma compounds content in probiotic fermented milk. The highest correlation (0.967) and lowest standard deviation of error for the training (0.585), selection (0.503) and testing (0.571) subset was obtained for the estimation of ethanol content. The lowest correlation (0.669) was obtained for the estimation of acetaldehyde content. The model exhibited poor performance in average error and standard deviations of errors in all subsets which could be explained by low sensitivity of the sensor array to the compound. The obtained results indicate that the potentiometric electronic tongue coupled with artificial neural networks can be applied as a rapid method for the determination of aroma compounds in probiotic fermented milk.
本文报告了一种电子舌在益生菌发酵乳中同时测定乙醇、乙醛、双乙酰、乳酸、乙酸和柠檬酸含量的应用。使用了 Alpha M.O.S. 的 alphaAstree 电子舌。传感器阵列由 7 个专为食品分析而开发的非特异性、交叉敏感传感器组成,与参考 Ag/AgCl 电极相结合。对原味、草莓味、苹果梨味和森林果味益生菌发酵乳样品进行了标准方法和电位传感器阵列分析。这些方法得到的结果被用于开发神经网络模型,以快速估计益生菌发酵乳中香气化合物的含量。对于乙醇含量的估计,获得了最高的相关性(0.967)和最小的训练(0.585)、选择(0.503)和测试(0.571)子集的误差标准偏差。对于乙醛含量的估计,相关性最低(0.669)。该模型在所有子集的平均误差和误差标准偏差方面表现不佳,这可以用传感器阵列对该化合物的低灵敏度来解释。所得结果表明,与人工神经网络耦合的电位电子舌可作为一种快速测定益生菌发酵乳中香气化合物的方法。