Development of a system for classification of honey in floral and honeydew for physicochemicalDevelopment of a system for classification of honey in floral and honeydew for physicochemical

The honey classification depends on the raw material, this classification is important in the appreciatione identification of the product. The characterization can be given by the analysis of physic-chemicalparameters. In this paper, 25 samples of honey were classified into floral honey or honeydew through theKirkwood method. A neural model was developed with multilayer percentron networks, backpropagationlearning algorithm and an easy operation system for the use of beekeepers. Tested networks were able to classify the honey with 100% precision, using only the pH and reducing sugar parameters, which are determinedin an easy, cheap and quick way.