Development of electronic nose for classification of medicinal aromatic herbs using artificial intelligent techniques

Herbs is useful in various applications especially in nutraceutical products and botanical medicine. In normal practice, the herbs identification is done mainly by botanists. However, it is difficult for botanist to recognize herbs based on aroma measurement for the species under the same family which is the physical appearance may look almost the same characteristic and also may be having the almost same aromas. Electronic nose instruments, derived from numerous types of aroma sensor technologies have been developed for a diverse of applications in a broad field of agriculture including for herbs. The emphasizes on the ability of an electronic nose in this project was to distinctify odor pattern of the herbs leaves from twelve species among lauraceae, myrtaceae and zingiberaceae family. The output captured by electronic nose gas sensors was classified by using Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS). From the result, ANFIS gives as higher as 94.8% percentage of accuracy to classify the herbs compare than ANN for 91.7% of accuracy