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  • Open Access

    ARTICLE

    Evaluation of Resistance of Different Kiwifruit Varieties (Lines) to Canker Disease and Brown Spot Disease

    Wenwen Su1,#, Chongpei Zheng3,#, Zhencheng Han2, Chunguang Ren1, Di Wu1, Tao Li1, Yi Yang1, Weijie Li2,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.6, pp. 1249-1261, 2024, DOI:10.32604/phyton.2024.051935

    Abstract Kiwifruit canker and brown spot are significant diseases affecting kiwis, caused by Pseudomonas syringae pathogenic variations (Pseudomonas syringae pv. Actinidiae (Psa)) and Corynesporapolytica (Corynespora cassiicola). At present, the research on canker disease and brown spot disease mainly focuses on the isolation and identification of pathogenic bacteria, drug control, resistance gene mining and functional verification. Practice has proved that breeding disease resistant varieties are an effective method to control canker disease and brown spot disease. However, most existing cultivars lack genes for canker and brown spot resistance. Wild kiwifruit resources in nature exhibit extensive genetic diversity due to prolonged natural selection,… More >

  • Open Access

    ARTICLE

    Rice Leaves Disease Diagnose Empowered with Transfer Learning

    Nouh Sabri Elmitwally1,2, Maria Tariq3,4, Muhammad Adnan Khan5,*, Munir Ahmad3, Sagheer Abbas3, Fahad Mazaed Alotaibi6

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 1001-1014, 2022, DOI:10.32604/csse.2022.022017

    Abstract In the agricultural industry, rice infections have resulted in significant productivity and economic losses. The infections must be recognized early on to regulate and mitigate the effects of the attacks. Early diagnosis of disease severity effects or incidence can preserve production from quantitative and qualitative losses, reduce pesticide use, and boost ta country’s economy. Assessing the health of a rice plant through its leaves is usually done as a manual ocular exercise. In this manuscript, three rice plant diseases: Bacterial leaf blight, Brown spot, and Leaf smut, were identified using the Alexnet Model. Our research More >

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