Gok Seher, Severcan Mete, Goormaghtigh Erik, Kandemir Irfan, Severcan Feride
Department of Biological Sciences, Middle East Technical University, 06531 Ankara, Turkey.
Department of Electrical and Electronic Engineering, Middle East Technical University, 06531 Ankara, Turkey.
Food Chem. 2015 Mar 1;170:234-40. doi: 10.1016/j.foodchem.2014.08.040. Epub 2014 Aug 20.
Botanical origin of the nectar predominantly affects the chemical composition of honey. Analytical techniques used for reliable honey authentication are mostly time consuming and expensive. Additionally, they cannot provide 100% efficiency in accurate authentication. Therefore, alternatives for the determination of floral origin of honey need to be developed. This study aims to discriminate characteristic Anatolian honey samples from different botanical origins based on the differences in their molecular content, rather than giving numerical information about the constituents of samples. Another scope of the study is to differentiate inauthentic honey samples from the natural ones precisely. All samples were tested via unsupervised pattern recognition procedures like hierarchical clustering and Principal Component Analysis (PCA). Discrimination of sample groups was achieved successfully with hierarchical clustering over the spectral range of 1800-750 cm(-1) which suggests a good predictive capability of Fourier Transform Infrared (FTIR) spectroscopy and chemometry for the determination of honey floral source.
花蜜的植物来源主要影响蜂蜜的化学成分。用于可靠蜂蜜鉴定的分析技术大多耗时且昂贵。此外，它们在准确鉴定方面无法提供100%的效率。因此，需要开发用于确定蜂蜜花源的替代方法。本研究旨在根据不同植物来源的安纳托利亚蜂蜜样本的分子含量差异来区分它们，而不是给出样本成分的数值信息。该研究的另一个范围是精确区分天然蜂蜜样本和掺假蜂蜜样本。所有样本均通过无监督模式识别程序进行测试，如层次聚类和主成分分析（PCA）。通过在1800 - 750 cm(-1)光谱范围内的层次聚类成功实现了样本组的区分，这表明傅里叶变换红外（FTIR）光谱和化学计量学在确定蜂蜜花源方面具有良好的预测能力。
