Multivariate analysis and multiple factorial modeling i n the classification of peruvia n honeys from bajo mayo, san martin, peru.

Honey is a natural product made mainly from the nectar of flowers; its final quality depends on its botanical and geographical origin. The variability is wide even for honey from the same region. The botanical and geographical origin of honey is still difficult to determine, so it is increasingly necessary to standardize analysis protocols that contribute to the verification of the quality of this important product of the beehive. The physicochemical and sensory properties of fifteen samples of honey from the Mayo River basin, Department of San Martin (Peru) have been evaluated, taking as reference the physicochemical parameters of color, the chromaticity of the CIELab system, pH, free acidity, total sugars, humidity, ash, electrical conductivity, density, and water activity. Additionally, the sensory attributes and intrinsic properties of the honey samples have been related to their classification through a Neuronal Probabilistic Network system, cluster analysis, discriminant, multiple factorial, and PLS-PATH, which have allowed the differentiation and classification of the honey, according to their geographical origin under three categories associated to the Pfund scale in amber, light amber, and extra light amber.