This research proposes a method for the automatic diagnosis and classification of leaf diseases in Kenyan Arabica coffee leaves. We trained Deep Convolution Neural Learning models on JMuBEN2 obtained from Mendeley data public access to determine whether particular image contains Phoma, Cercospora, or Rust. The proposed this work were ResNet50, Densenet-121, VGG19 architectures, all are well-kno...

Abstract The article presents the research data on effect of Fusarium blight, Phoma rot, and Sclerotinia blight plant productivity winter spring rapeseed, brown mustard, white mustard. As a result studies, we found that (the pathogens are fungi genus Link) was most harmful for mustard – affection by it significantly decreased productivity. At 4 points degree plants, harmfulness disease reached ...