Lime Diseases Detection and Classification Using Spectroscopy and Computer Vision

In the agricultural industry, plant diseases and pests pose greatest risks. Lime is rich 10 source of vitamin C which works as an immunity booster in human body. Because late manually detection lime causes a vast loss crop production worldwide. The most common are found limes canker, lemon scab, brown rot, sooty mould Armillaria. this paper we used imaging non-imaging (spectral based sensing) methods with combination machine learning technique to detect canker diseases. Image acquirement, pre-processing, segmentation classification all steps methodology, then followed by feature extraction. methodology multispectral sensor (Spectrometer) 400 nm 1000 wavelength training set test ratio fixed for both techniques 75% 25% respectively. When it comes identifying classifying disease, spectroscopy has 99% efficiency rating compared methodology's 96%.