Paper Title
Classification of Honey Samples of Isfahan Province With Different Floral Origin By Chemometric Methods

The analytical data of 30 Isfahanian honey samples from five varieties, lotus (7 samples), milk vetch (6 samples), Thyme (6 samples), coriander (6 samples) and citrus (5 samples) collected and physiochemical characteristics according to Codex Alimentarius such as sugar before hydrolysis, sucrose, f/g, pH, acidity, moisture, ash, hydroxyl methyl furfural, electrical conductivity, diastaze activity, solid matter and prolin tested 3 times and average of data calculated. With this data, cannot opine about floral origin of honey, so we use cluster analysis, principal component analysis, linear discriminant analysis, and artificial neural network to classification against honey floral origin by minitab and matlab softwares. Keywords- Honey, Classification, Artificial neural network, Linear Discriminant Analysis, Principle Component Analysis.