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38 results for “Leaf Diseases”
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Research ArticleOpen accessIn the abstractAutomating Paddy Crop Disease Classification With Deep Learning ModelsShiva Shankar J, S. Palanivel, S. China VenkateswarluRice is a staple food crop for more than 10 countries. High consumption of rice demands better yield of crop. Timely disease diagnosis in paddy is fundamental to preventing yield losses and ensuring an adequate supply of rice for a rapidly rising worldwide population. Agriculture and modern farming is one of the fields where IoT and automation can have a … …Journal of Computer Science, Vol. 21, Issue 8 · 1 Sep 2025 · 5,696 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Plant Disease Identification Through Hyperspectral Imaging and AC-FNet FrameworkDhason Lita Pansy, Malaichamy MuraliThe precise identification of plant diseases is essential for optimizing agricultural practices. The impact of these diseases on food production often leads to significant revenue loss. Detecting diseases that primarily manifest symptoms in plant leaves has conventionally depended on visual inspection by plant pathologists. However, modern methodologies use machine learning and computer vision techniques to facilitate disease identification, thus addressing … …Journal of Computer Science, Vol. 21, Issue 5 · 21 May 2025 · 8,568 accessesView PDFCite
Research ArticleOpen accessIn the abstractAgricultural Crop Disease Detection Using Convolutional Neural NetworksAtsu Alagah Komlavi, Harouna Naroua, Chaibou KadriMitigating food insecurity in Niger is of paramount importance. According to some researchers, agricultural yield is declining. The permanent annual food shortage was estimated to be between 25 and 50%. Loss of cereal agricultural production is caused by pests and plant diseases. Knowing that ordinary techniques became inefficient. Automatic detection of plant diseases using artificial intelligence becomes the best solution. … …Journal of Computer Science, Vol. 21, Issue 3 · 24 Jan 2025 · 7,547 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Multi-Scale Feature Extraction and Fusion Deep Learning Method for Classification of Wheat DiseasesSajjad Saleem, Adil Hussain, Nabila Majeed et al.Wheat is an important source of dietary fiber and protein that is negatively impacted by a number of risks to its growth. The difficulty of identifying and classifying wheat diseases is discussed with an emphasis on wheat loose smut, leaf rust, and crown and root rot. Addressing conditions like crown and root rot, this study introduces an innovative approach that … …Journal of Computer Science, Vol. 21, Issue 1 · 2 Jan 2025 · 6,344 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Accurate Mango Pest Identification Employing the Gaussian Mixture Model and Expectation-Maximization (EM) AlgorithmD. Lita Pansy, M. MuraliMangoes are fruits that originated in South and Southeast Asia. Mango fruits are consumed in high volume worldwide. However, fruit, stem, root, and mango leaves are damaged by pests, and it has a significant negative impact on mango production. Many works were developed for the pest detection of mango; but, none of the works concentrated on the practical applicability and … …Journal of Computer Science, Vol. 21, Issue 1 · 3 Dec 2024 · 5,063 accessesView PDFCite
Review ArticleOpen accessIn the abstractThe Impact of Di-2-Ethylhexyl Phthalate (DEHP) in Focus on the Reproductive System and Toxicity in Rat or Mammalian ModelVenkataramanaiah Poli, Srinivasulu Reddy MotireddyAbsalan, F., Saremy, S., Mansouri, E., Moghadam, M. T., Moghadam, A. R. E., & Razie, G. (2016). Effects of Mono-(2-Ethylhexyl) Phthalate and Di-(2-Ethylhexyl) Phthalate Administrations on Oocyte Meiotic Maturation, Apoptosis and Gene Quantification in Mouse Model. Cell Journal, 18(4), 503–513. https://doi.org/10.22074/cellj.2016.4717 Acevedo‐Rodriguez, A., Kauffman, A. S., Cherrington, B. D., Borges, C. S., Roepke, T. A., & Laconi, M. (2018). Emerging … …American Journal of Pharmacology and Toxicology, Vol. 19, Issue 1 · 6 Jun 2024 · 12,990 accessesView PDFCite
Research ArticleOpen accessIn the abstractGrowth Characters, Physiology and Leaf Fall Disease Resistance in Immature Plants of Rubber (Hevea brasiliensis) IRR 400 Series ClonesRahayu Novrina Rosa, Mohammad Basyuni et al.Superior rubber clones have been used in Indonesia, but productivity achievements are low. The area and rubber production in 2020 was 3,316,047 ha with a productivity of 1,022 kg/ha. The low productivity is caused use of seedling materials. Adaptation testing is one of the stages for selecting superior rubber clones in various environmental conditions, the influencing factors are clone or … …OnLine Journal of Biological Sciences, Vol. 24, Issue 3 · 22 Mar 2024 · 5,300 accessesView PDFCite
Research ArticleOpen accessIn the abstractResistance to Brown and Stem Rust in Spring Soft Wheat Varieties in the Arid Climate of Northern KazakhstanAdylkhan Babkenov, Sandukash Babkenova, Svetlana Dashkevich et al.To create competitive wheat varieties, it is essential to make active use of the world's diversity of genetic resources. The study aims to test the genetic resources of spring soft wheat for resistance to rust diseases. A spring soft wheat collection consisting of 206 samples, was studied in 2020-2022 for resistance to leaf and stem rust, as well as for … …OnLine Journal of Biological Sciences, Vol. 23, Issue 4 · 28 Aug 2023 · 5,023 accessesView PDFCite
Research ArticleOpen accessIn the abstractApoptosis in Yeast is Modulated by Clove Leaf Extract and Eugenol Potentially by Interfering Caspase YCA1Septyani Amini, Rika Indri Astuti, Irmanida BatubaraApoptosis is a process of cell death important for preventing the development of diseases such as cancer, neurodegenerative disorders, autoimmune, and cardiovascular disease. Apoptosis is reported to be potentially induced by antioxidant compounds, including phytoextract. Thus in this study, we determined the potential of apoptotic modulation in yeast cells by clove extract, which was rich in eugenol. Apoptotic in yeast … …OnLine Journal of Biological Sciences, Vol. 22, Issue 3 · 15 Sep 2022 · 5,497 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Backward Regressed Capsule Neural Network for Plant Leaf Disease DetectionJennifer Jepkoech, Benson Kipkemboi Kenduiywo, David Muchangi Mugo, Edna Chebet ToolThis study investigated the introduction ofbackward regression coupled with DenseNet features in a Capsule Neural Network(CapsNet) for plant leaf disease classification. Plant diseases are consideredone of the main factors influencing food production and therefore fast cropdisease detection and recognition are important in enhancing food securityinterventions. CapsNets have successfully been adopted for plant leaf diseaseclassification however, backpropagation of signals to preceding … …Journal of Computer Science, Vol. 18, Issue 9 · 8 Sep 2022 · 5,718 accessesView PDFCite