Labiatae herbs extracts are used directly or indirectly for the treatment of different diseases as medicinal plants. The safety, quality and effectiveness of medicinal plants and herbal drugs are very important for consumers. So authentication and quality of medicinal plants are very important parameters. This idea became highlight when it is revealing the adulteration of food, spice and herbs. The adultery, forgery (falsification), substitution, and deliberate labeling of incorrect products are performing for reducing production costs, using cheaper and older or banned chemicals in food or herbal product. Also, the influences of herbs on food quality and human health depend on their composition, nutritional properties and geographical origin. For these purposes authentication and quality of 47 dried and fresh labiatae samples contain Mint, Thyme, Oregano, Satureja, Basil, Sage, Lemmon balm, Lavender and Hyssop with different botanical origins was investigated. The acidic extracts of samples from twelve genus different geographical origins and nine genus samples were assessed using individually UV-Vis and IR fingerprints coupled by principal component analysis (PCA) and partial least square -linear discriminant analysis (PLS-DA). PLS-DA classification model with classification accuracy of %67, %11 and %90 was obtained for FT-IR, UV-Vis and Cyclic voltametry data, respectively. The accuracy of PLS-DA was not well. So, classification was tested using data fusion approach. This means that the dimension of data sets was reduced and the optimum latent vectors (LVs) of individually models was extracted and combined with each other. The constructed data matrix was subjected to PCA and PLS-DA model and classification based on originality and sample type was performed. It can be concluded that, the discrimination of geographical origins and chemical content of samples using single spectroscopic technique may be insufficient due to similarity and complexity of UV-Vis, CV and
