kinetic model simulation of thin-layer drying of peppermint (mentha piperita l.) using adaptive neuro-fuzzy inference system (anfis)

rating medicinal plants based on the total number of drug shows that the mint plant species, withgeneral name mentha, among the most consumption herbs that are used in various industries such aspharmaceutical, food, cosmetics and health. drying process, in order to maintain the quality andquantity of essential oil extraction have a great role in the processing medicinal plants. importantaspects of drying technology with the aim of selecting the most appropriate drying method, ismodeling of the drying process. therefore in this study, thin layer drying behavior of peppermint(mentha piperita l.) was experimentally investigated in a convective type dryer by using adaptiveneuro-fuzzy inference system (anfis). drying experiments were conducted at inlet drying airtemperatures of the 40, 50 and 60°c, at three drying air velocity of 1, 1.5 and 2 m/s. for kineticmodel simulation of thin-layer drying of peppermint, four anfis models was used and for generatethe fuzzy inference system model, the two partitioning techniques, grid partitioning and subtractiveclustering, was used. results indicated that, anfis model could satisfactorily describe the dryingcurve of peppermint, also comparison of two partitioning techniques results showed that subtractiveclustering technique was found to be the most suitable for fuzzy inference system generation forpredicting moisture ratio of the thin layer drying of peppermint.