The identification of the relationship between chemical and electrical parameters of honeys using artificial neural networks

Abstract

A number of significant scientific studies have confirmed the health benefits of honey. Due to the high price of natural honey, it is a common target for adulteration which reduces its medicinal value. Adulteration detection methods require specific laboratory equipment and are very expensive. The development of measurement techniques enables the measurement of electrical characteristics of strained honey. Honey electrical parameters can possibly be used for its quality assessment. The identification of the relationship between chemical and electrical parameters of honeys and analysis to determine if there are frequency-dependent changes, can help in developing of that group of methods. The aim of this research was to determine how the chemical parameters of certain honeys influence the dielectric loss factor and the permittivity of strained honey measured in various frequencies. Another aim was to determine whether the percentage influence of certain chemical parameters of honeys on electrical characteristics significantly depends on frequency value. The research was based on neural network models and sensitivity analysis. The percentage influence of certain chemical parameters on electrical characteristics significantly depends on frequency value.