Analysis and feasibility study of plant disease using e-nose

Abstract

Agriculture is one of the main sources that contribute to the economic development in the country. However, diseases that attack the crops have given a little impact to the agricultural production. Generally, plant pathologist has the difficulties to detect the symptoms that relate to the plant disease. The plant usually gets infected that are caused by different plant pathogens such as bacteria, fungus and virus that attack the plant. Therefore, some method of solution needs to be uncounted in order to provide faster solution in detecting this disease. In order to overcome this problem, the current study proposes detection of plant disease using an electronic nose (e-nose) called PEN3 e-nose. This type of e-nose will detect the volatile organic compounds that are produced by two types of plants which are chilies and papaya. The data that have been collected from PEN3 e-nose are processed using principal component analysis (PCA) and linear discriminant analysis (LDA) methods. In order to validate the detection result, the bacteria sample will be stained based on Gram staining procedure in order to observe the structure and colony of the bacteria cells using a digital microscope. Thus, this study shows that the PEN3 e-nose is able to detect the presence of plant pathogenic bacteria on both chilli and papaya plants.