Karabagias Ioannis K, Louppis Artemis P, Kontakos Stavros, Drouza Chryssoula, Papastephanou Chara
Laboratory of Food Chemistry, Department of Chemistry, University of Ioannina, Ioannina 45110, Greece.
cp Foodlab Ltd., Polifonti 25, 2047 Strovolos, Nicosia, Cyprus.
J Anal Methods Chem. 2018 Jun 5;2018:7698251. doi: 10.1155/2018/7698251. eCollection 2018.
Thirty-four honey samples donated by beekeepers and purchased from supermarkets were collected during harvesting years 2010-2014 from Cyprus, Greece, and Egypt. The aims of this study were to characterize honey samples and, if possible, to differentiate honeys according to the honey type on the basis of physicochemical parameter values, mineral content, and their combination using supervised statistical techniques (linear discriminant analysis (LDA)). Physicochemical parameters (colour, pH, free acidity, total dissolved solids, salinity, electrical conductivity, and moisture content) were determined according to official methods, while minerals (Al, As, B, Ba, Be, Ca, Cd, Co, Cr, Cu, Fe, Hg, Mg, Mn, Mo, Ni, P, Pb, Sb, Si, Ti, Tl, V, and Zn) using inductively coupled plasma optical emission spectrometry. The majority of honey samples analyzed met the quality criteria set by the European directive and national decision related to honey. Implementation of multivariate analysis of variance (MANOVA) and LDA on specific physicochemical parameters, minerals, or their combination provided a satisfactory classification of honeys according to floral type. The overall correct classification rate (based on the cross-validation method) was 79.4% using 7 minerals and 91.2% using 8 physicochemical parameters. When the 15 parameters were combined, the classification rate of Egyptian honeys was improved by 25%.
2010 - 2014年收获季期间，从塞浦路斯、希腊和埃及收集了34份由养蜂人捐赠并从超市购买的蜂蜜样本。本研究的目的是对蜂蜜样本进行表征，并尽可能根据理化参数值、矿物质含量以及使用监督统计技术（线性判别分析（LDA））对它们的组合，按蜂蜜类型区分蜂蜜。理化参数（颜色、pH值、游离酸度、总溶解固体、盐度、电导率和水分含量）根据官方方法测定，而矿物质（铝、砷、硼、钡、铍、钙、镉、钴、铬、铜、铁、汞、镁、锰、钼、镍、磷、铅、锑、硅、钛、铊、钒和锌）则使用电感耦合等离子体发射光谱法测定。分析的大多数蜂蜜样本符合欧洲指令和国家有关蜂蜜的决定所设定的质量标准。对特定理化参数、矿物质或其组合进行多变量方差分析（MANOVA）和LDA，能根据花的类型对蜂蜜进行令人满意的分类。使用7种矿物质时，总体正确分类率（基于交叉验证法）为79.4%，使用8种理化参数时为91.2%。当将15个参数组合时，埃及蜂蜜的分类率提高了25%。
