classification of different floral origin honey samples using a machine olfaction system

honey is a sweet and viscous liquid made by bees from nectar of flowers. the emitted smell by honey depending on flower variety can be different. these factors led to use of machine olfactory system based on metal oxide sensors(mos) in order to classify different floral origin honeys. seven samples of different floral origins of honey with a total of 70 samples from each of 10 samples were tested. principal component analyze (pca), linear discriminant analyze (lda) and artificial neural network (ann) were methods to classify and analyze the extracted features from the machine olfactory system signal that were used. to classify floral origin honey using the machine olfaction, the results was included a 97% variance by pca, 87.3% and 88.5% accuracy classification, respectively of lda and ann. as a conclusion, it was found that the electronic nose could provide good classification among of honeys.