Electronic Honey Quality Analyser

The detection of adulterated honey is a considerable challenge in the Sri Lankan context. The usual practice is to independently check the different parameters in order to determine the quality of a given honey sample. However, measuring and employing a single parameter for the classification reduces the accuracy of the classification. Thus, in this paper a multi-parameter based honey quality classification is proposed to ensure a better accuracy. The design of a parameter detector and a classifier which can automatically complete the classification of a given sample is also presented. This classifier operating on support vector machines is first trained using an array of honey samples obtained in Sri Lanka. The resultant classifier shows a high level of accuracy of 97.5% for the randomly selected test sample set. The proposed system is a handy tool for accurate, quick, low cost and simple honey quality checking.