Geographical discrimination of pine and fir honeys using multivariate analyses of major and minor honey components identified by 1H NMR and HPLC along with physicochemical data

Abstract

The objective of the present work was the geographical discrimination of the most common honeydew honeys produced in Greece, namely pine and fir, on the basis of sugar, free amino acid and organic acid content, determined by nuclear magnetic resonance spectroscopy (1H NMR) and high-performance liquid chromatography (HPLC), along with moisture content, sugar ratios, or sugars to moisture ratio, using chemometrics. For this purpose, 39 pine and 31 fir honey samples were collected from professional beekeepers from eight different regions in Greece. Data were subjected to multivariate analysis and modeled using supervised statistical methods. The combination of 1H NMR and HPLC based on metabolites along with the aforementioned physicochemical data resulted in the geographical discrimination of pine and fir honeys. Respective prediction rates were 76.9 and 80.6%, using a model validation technique: the cross-validation method. Present results support the combined use of instrumental and conventional methods for honey geographical origin differentiation.