Comparison of quality characteristics in honey using grey relational analysis and principal component analysis methods

Abstract

Composition characteristics are taken into account to determine authenticity and quality of honey. This study used grey relational analysis and principal component analysis methods to identify the most important variables affecting quality of honey.Honey specimens from 20 different producers were obtained to determine quality characteristics. C4 % (0.787), glucose (0.753), moisture (0.731), F+G (0.712), fructose (0.685), acidity (0.605), brix (0.581), conductivity (0.580), δ13C honey (0.576), proline (0.571), pH (0.530), δ13Cprotein -honey (0.527), δ13C protein (0.516), Fructose -glucose ratio (0.507) and diastase number (0.490) were found to be the most important variables on quality of honey based on the mean values of grey relational coefficients of quality characteristics. Grey relational grade (GRG) calculated by using eight values obtained from principal component analysis of quality parameters showed that S6 (0.690) was the honey with the highest quality, while S16 (0.501) was the honey with the lowest quality.