ABSTRACT
The trace and rare earth elements content of 93 honeys of different botanical type and origin have been studied through ICP-MS. Discriminant Analysis (DA) was successful for botanical type and geographical origin classification while Cluster Analysis (CA) was successful only for botanical type. Through Probabilistic Neural Network (PNN) analysis, 85.3% were correctly classified by the network according to their geographical origin and 73.3% according to their organic characterization. A Partial Least Squares (PLS) model was constructed, giving a prediction accuracy of more than 95%. Information obtained using Rare Earths (Y, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu) and trace elements (Li, Mg, Mn, Ni, Co, Cu, Sr, Ba, Pb) via chemometric evaluation facilitated classification of honey samples.
Subject(s)
Cheminformatics , Geography , Honey/analysis , Metabolomics , Cluster Analysis , Discriminant Analysis , Fraud/prevention & control , Least-Squares Analysis , Metals, Rare Earth/analysis , Neural Networks, Computer , Spectrum Analysis , Trace Elements/analysisABSTRACT
Honey is a natural food product hypothesized to have significant health-beneficial value. The results of recent studies indicate that the biological activity of honey can also be ascribed to phenolic compounds and their antioxidant activity. The aims of this study were: To determine the phenolic profiles of several varieties of Polish honey and their correlation with various factors influencing the quality of honey, plus to verify the impact of production method (organic/conventional) and the pollen content on these profiles. In total, 11 organic and 11 conventional honey samples from Poland were investigated. The botanical origin of the samples was identified through melissopalynological analysis, whereas individual phenolic compounds were determined by the LC/MS analysis. The Folin-Ciocalteau assay was used for the determination of the total phenolic content (TPC). Moreover, the CIE L*a*b* color values were measured and matched with the above-mentioned parameters. The results of the study contribute to the discussion on the health benefits of organic farming. It was found that chrysin may act as a potential indicator compound. The study confirms the existence of the link between TPC and color, and it shows that there is a correlation between pinocembrin and galangin, two compounds that are reported to ameliorate insulin resistance.
ABSTRACT
We developed a new, indirect method for the determination of mineral substances, expressed as total ash content in bee honey varieities, based on a multiple regression model. This time-saving and effective method could serve as a new procedure in routine quality control plans of bee honey varieties.
Subject(s)
Honey/analysis , Minerals/analysis , Electric Conductivity , Honey/classification , Hydrogen-Ion Concentration , Regression Analysis , ViscosityABSTRACT
In order to develop a procedure to identify a type and variety of honeys, basing on the physicochemical parameters of honey quality, two-phase calculations were conducted. A method of discrimination analysis was used. Moreover, a model to use while identifying honeys was proposed.