Dymerski Tomasz, Gębicki Jacek, Wardencki Waldemar, Namieśnik Jacek
Department of Analytical Chemistry, Chemical Faculty, Gdansk University of Technology, 11/12 G. Narutowicza Str., 80-233 Gdańsk, Poland.
Department of Chemical and Process Engineering, Chemical Faculty, Gdansk University of Technology, 11/12 G. Narutowicza Str., 80-233 Gdańsk, Poland.
Sensors (Basel). 2014 Jun 18;14(6):10709-24. doi: 10.3390/s140610709.
The paper presents practical utilization of an electronic nose prototype, based on the FIGARO semiconductor sensors, in fast classification of Polish honey types-acacia flower, linden flower, rape, buckwheat and honeydew ones. A set of thermostating modules of the prototype provided gradient temperature characteristics of barbotage-prepared gas mixtures and stable measurement conditions. Three chemometric data analysis methods were employed for the honey samples classification: principal component analysis (PCA), linear discriminant analysis (LDA) and cluster analysis (CA) with the furthest neighbour method. The investigation confirmed usefulness of this type of instrument in correct classification of all aforementioned honey types. In order to provide optimum measurement conditions during honey samples classification the following parameters were selected: volumetric flow rate of carrier gas-15 L/h, barbotage temperature-35 °C, time of sensor signal acquisition since barbotage process onset-60 s. Chemometric analysis allowed discrimination of three honey types using PCA and CA and all five honey types with LDA. The reproducibility of 96% of the results was within the range 4.9%-8.6% CV.
本文介绍了一种基于费加罗半导体传感器的电子鼻原型在波兰蜂蜜类型（刺槐蜜、椴树蜜、油菜花蜜、荞麦蜜和甘露蜜）快速分类中的实际应用。该原型的一组恒温模块提供了鼓泡法制备的气体混合物的梯度温度特性以及稳定的测量条件。采用了三种化学计量学数据分析方法对蜂蜜样本进行分类：主成分分析（PCA）、线性判别分析（LDA）和最远邻域法聚类分析（CA）。研究证实了这类仪器在正确分类上述所有蜂蜜类型方面的有用性。为了在蜂蜜样本分类过程中提供最佳测量条件，选择了以下参数：载气的体积流量为15 L/h、鼓泡温度为35℃、自鼓泡过程开始起传感器信号采集时间为60 s。化学计量学分析通过PCA和CA能够区分三种蜂蜜类型，通过LDA能够区分所有五种蜂蜜类型。96%的结果的重现性在4.9%-8.6%变异系数范围内。
