Abstract
This study examined strawberry white spot disease severity using different hyperspectral imaging analyzing methods. The plant leaf images were classified by spectral angle mapper (SAM), by vegetation indices (RENDVI, GNDVI, MCARI) thresholds and by principal component analysis (PCA) method. The SAM method showed the overall accuracy 84% when classifying three types of visual symptoms of the disease.
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