Identification of Various Genus Mentha L. with Electronic Nose Using Fuzzy Logic Algorithm

Genus Mentha commonly known as mint plants belonging to the Lamiaceae family are the most sought plants due to their health benefits. This paper describes a study that uses an electronic nose system and a fuzzy logic algorithm to identify various types of genus Mentha. The gases emitted by the mint plants will be measured using MQ sensors. The measured data will be utilized by applying a fuzzy logic approach to figure out the identity of different mint plant species. The prototype system performance evaluation is done by the researchers using three types of Genus Mentha plants namely, Applemint, Lemonmint, and Peppermint. A total of 37/45 plant samples were used. Based on the test, the system has acquired 80.00% for identifying Applemint, 86.66% for Lemonmint, and lastly an 80.00% accuracy in identifying Peppermint. The overall performance accuracy of 82.22% for identifying the three plant types.