Sensory Laboratory, Corvinus University of Budapest, Faculty of Food Science, Villányi út 29-35, Budapest H-1118, Hungary.
Food Chem. 2012 Dec 15;135(4):2947-53. doi: 10.1016/j.foodchem.2012.06.021. Epub 2012 Jul 7.
Mineral, spring and tap water samples of different geographical origins (7 classes) were distinguished by various methods, such as sensory evaluation, electronic tongue measurement, inductively coupled plasma atomic emission spectroscopy and ion chromatography. Samples from the same geographical origin were correctly classified by chemical analysis and electronic tongue (100%), but it was found that only 80% classification rate can be achieved by sensory evaluation. Different water brands (different brand names) from the same geographical origin did not show definite differences, as expected. Forward stepwise algorithm selected three chemical parameters namely, chloride (Cl(-)), sulphate (SO(4)(2-)) and magnesium (Mg) content and two electronic tongue sensor signals (ZZ and HA) to discriminate according to the geographical origins.
不同地理来源(7 类)的矿物、泉水和自来水样品通过各种方法进行区分,例如感官评估、电子舌测量、电感耦合等离子体原子发射光谱和离子色谱。通过化学分析和电子舌(100%)对来自同一地理来源的样品进行正确分类,但发现感官评估的分类率仅为 80%。正如预期的那样,来自同一地理来源的不同水品牌(不同品牌名称)没有显示出明确的差异。向前逐步算法选择了三个化学参数,即氯(Cl(-))、硫酸盐(SO(4)(2-))和镁(Mg)含量以及两个电子舌传感器信号(ZZ 和 HA),根据地理来源进行区分。