Abstract:
The potential of a voltametric E-tongue coupled with a custom data pre-processing stage to improve the performance of machine learning techniques for rapid discrimination of tomato purées between cultivars of different economic value has been investigated. To this aim, a sensor array with screen-printed carbon electrodes modified with gold nanoparticles (GNP), copper nanoparticles (CNP) and bulk gold subsequently modified with poly(3,4-ethylenedioxythiophene) (PEDOT), was developed to acquire data to be transformed by a custom pre-processing pipeline and then processed by a set of commonly used classifiers. The GNP and CNP-modified electrodes, selected based on their sensitivity to soluble monosaccharides, demonstrated good ability in discriminating samples of different cultivars. Among the different data analysis methods tested, Linear Discriminant Analysis (LDA) proved to be particularly suitable, obtaining an average F1 score of 99.26%. The pre-processing stage was beneficial in reducing the number of input features, decreasing the computational cost, i.e., the number of computing operations to be performed, of the entire method and aiding future cost-efficient hardware implementation. These findings proved that coupling the multi-sensing platform featuring properly modified sensors with the custom pre-processing method developed and LDA provided an optimal tradeoff between analytical problem solving and reliable chemical information, as well as accuracy and computational complexity. These results can be preliminary to the design of hardware solutions that could be embedded into low-cost portable devices.
摘要:
已经研究了伏安电子舌与自定义数据预处理阶段相结合的潜力,以提高机器学习技术在不同经济价值的品种之间快速区分番茄泥的性能。为了这个目标,具有用金纳米颗粒(GNP)修饰的丝网印刷碳电极的传感器阵列,铜纳米颗粒(CNP)和本体金随后用聚(3,4-亚乙基二氧噻吩)(PEDOT)改性,是为了获取要由自定义预处理管道转换的数据,然后由一组常用分类器进行处理。GNP和CNP修饰的电极,根据它们对可溶性单糖的敏感性进行选择,在区分不同品种的样品方面表现出良好的能力。在测试的不同数据分析方法中,线性判别分析(LDA)被证明是特别合适的,获得99.26%的平均F1分数。预处理阶段有利于减少输入特征的数量,降低计算成本,即,要执行的计算操作的数量,整个方法,并有助于未来成本效益高的硬件实现。这些发现证明,将具有适当修改的传感器的多传感平台与开发的自定义预处理方法和LDA相结合,可以在分析问题解决和可靠的化学信息之间进行最佳权衡。以及准确性和计算复杂性。这些结果可以初步设计可以嵌入到低成本便携式设备中的硬件解决方案。