classification of iranian honey according to their geographical origin based on the chemical composition and pattern recognition methods

Honey is the natural sweet substance produced by honey bees which is composed mainly of sugars and a complex mixture of minor components such as amino and organic acids, minerals, flavonoids, and other phytochemicals [1]. the composition and sensory attributes of honey vary considerably depending on its botanical and geographical origin [2, 3]. therefore, it is studied in different countries and zones because of the interest of consumers in origin and quality of food. iran produces and exports honey from different zones; therefore, the main aim of this work was to study the chemical parameters of honeys (from ghalikouh, jasb and north west of iran) using pattern recognition methods in order to classify honeys according to their geographical origin. because honey samples contain a number of fluorophores, it is not enough to measure only a single variable spectrum to collect sufficient data. therefore, multivariate measurements are required. amino acid contents were obtained using hplc with fluorescence detection after derivatization and spectrophotometric data (uv-vis spectra) were obtained after liquid-liquid extraction. then, the results were analyzed by principal component analysis (pca) and linear discriminant analysis (lda) for classification purposes. the results showed that the chemometric analysis allowed classification of samples according to their geographical origin by using spectrophotometric data. a high percentage of correct classifications for the training data demonstrated the strong relationship between the spectral data and the geographical origin, while a high percentage for the prediction set showed the ability to indicate the origin of an unknown honey sample based on its chemical composition spectrophotometric data.