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26 articles for “Plant Disease Detection”
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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 abstractDeep Learning-Based Approach for Identification of Potato Leaf Diseases Using Wrapper Feature Selection and Feature ConcatenationMuhammad Ahtsam Naeem, Muhammad Asim Saleem, Jarrar Amjad et al.The potato is a widely grown crop in many regions of the world. In recent decades, potato farming has gained incredible traction in the world. Potatoes are susceptible to several illnesses that stunt their development. This plant seems to have significant leaf disease. Early Blight and Late Blight are two prevalent leaf diseases that affect potato plants. The early detection … …Journal of Computer Science, Vol. 21, Issue 5 · 12 May 2025 · 5,171 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
Research ArticleOpen accessIn the abstractCrop Disease Detection Using Deep Learning Techniques on ImagesKinjal Vijaybhai Deputy, Kalpdrum Passi, Chakresh Kumar JainAgriculture plays a crucial role in the economic development of many countries and sustains the global population despite facing various challenges like climate change, pollinator decline, and plant diseases. These threats to food security highlight the need for innovative solutions to prevent crop loss. Leveraging smartphone technology for automated image recognition-based disease diagnosis has emerged as a promising approach, thanks … …Journal of Computer Science, Vol. 19, Issue 12 · 25 Oct 2023 · 7,497 accessesView PDFCite
Research ArticleOpen accessIn the abstractIdentification of the Presence of the "Swollen Shoot" Disease in Endemic Areas in Côte d'Ivoire Via Convolutional Neural NetworksCoulibaly Mamadou, Silue Kolo, Konan Hyacinthe Kouassi et al.The detection of Swollen Shoot disease and its control is one of the major objectives of research related to sustainable cocoa farming in Côte d'Ivoire. To contain the epidemic, the Cocoa Coffee Council (CCC) in collaboration with the National Agency for Support to Rural Development (ANADER) is responsible for prospecting and delimiting the infected areas as well as for uprooting … …American Journal of Engineering and Applied Sciences, Vol. 16, Issue 3 · 1 Oct 2023 · 6,064 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetection of Rust Emergence in Coffee Plantations using Data Mining: A Systematic ReviewLenin Quiñones Huatangari, Candy Lisbeth Ocaña Zúñiga, Annick Estefany Huaccha Castillo et al.Hemileia vastatrix is a fungus that causes coffee rust disease and, depending on the level of severity, reduces the photosynthetic capacity of the plant and of new shoots, leading to low coffee yields and even death; its symptoms are visible on the leaf. Systems based on computer algorithms have been developed to predict diseases and pests in coffee. The objective … …OnLine Journal of Biological Sciences, Vol. 22, Issue 2 · 31 Mar 2022 · 8,022 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Weighted Voting Deep Learning Approach for Plant Disease ClassificationAssia Ennouni, Noura Ouled Sihamman, My Abdelouahed Sabri, Abdellah AarabPlant destruction is usually caused by plant diseases. Without early and reliable detection, it can affect the plants and may eventually cause permanent losses, especially for inexperienced farmers. Therefore, intelligence in agriculture is becoming more and more required. Thereafter early diagnosis and classification are crucial and a very challenging research field in the agriculture sector for its treatment. In this … …Journal of Computer Science, Vol. 17, Issue 12 · 16 Dec 2021 · 6,557 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetection of Plant Leaf Diseases Using K‒mean++ Intermeans Thresholding AlgorithmKittipol Wisaeng, Worawat Sa–NgiamviboolIn the field of agricultural information, the plant leaf disease detection is highly important for both farmer life and environment. To improve the accuracy of plant leaf disease detection and reduce the image processing time, the improved K‒mean++ clustering and intermeans thresholding method are proposed in this study. The proposed algorithms are used for training and testing diseases in plant … …Journal of Computer Science, Vol. 16, Issue 9 · 21 Sep 2020 · 6,750 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproving a PCR-Based Method for Identification of Ralstonia solanacearum in Natural Sources of West MalaysiaReza Khakvar, Kamaruzaman Sijam, Wong Mui Yun et al.Ralstonia solanacearum, a soil-borne plant pathogen, causes lethal wilting disease of more than 200 plants worldwide. This very wide host range covers both monocots and dicots, extending from annual plants to trees and shrubs. Although generally it’s considered as a plant pathogen, R. solanacearum behaves primarily as a saprophytic bacterium able to survive for long periods of time in various … …American Journal of Agricultural and Biological Sciences, Vol. 3, Issue 2 · 30 Jun 2008 · 9,469 accessesView PDFCite