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31 articles for “leaf disease”
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Enhancing Crop Health: A Review of Image Processing Methods for Leaf Disease Identification
Abstract: This research presents an overview of different image processing techniques for the identification of leaf disease. Many algorithms can be used to identify and categorize leaf diseases in plants, and digital image processing provides a quick, dependable, and accurate method of disease detection. This paper presents various techniques used on multiple crops and the achieved accuracy for each model. Leaf disease detection is a critical task in agriculture to ensure …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 10–14 Read article
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An Empirical Study of Hyperparameter Impact on Deep Learning Models for Cardamom Leaf Disease Classification
Abstract: Recent advancements in deep learning models like convolutional neural networks and self- attention mechanisms have achieved great success in the field of plant disease classification. This study investigates the efficacy of two pre-trained models, ConvNeXT-Tiny and Swin Transformer-Tiny, for leaf disease classification in cardamom using a publicly available dataset constituting three categories of leaves, namely Healthy, Colletotrichum Blight and Phyllosticta Leaf Spot. The effectiveness of the models highly depends on …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 48–60 Read article
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Hybrid Techniques in Mango Leaf Disease Identification: Evaluating Neural Networks and Support Vector Machines
Abstract: Mango leaf diseases pose a significant threat to mango production, impacting both yield and fruit quality. Early and accurate detection of these diseases is crucial for effective management. This paper evaluates the use of hybrid techniques, specifically the integration of neural networks (NNs) and support vector machines (SVM), in the identification and classification of mango leaf diseases. NN excel in extracting complex features from images, while SVMs are robust classifiers, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 19–27 Read article
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Nanotechnology: Effective Pesticide Solutions for Jawar Leaf Diseases
Abstract: Jawar (Sorghum), a staple food crop in many parts of the world, faces significant challenges from various leaf diseases that can drastically reduce yields and impact food security. Traditional pesticide application, while offering some protection, often suffers from limitations such as low efficiency, environmental concerns, and the development of pesticide resistance in pathogens. The application of nanotechnology is a viable option, presenting novel strategies to solve these challenges and revolutionising …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 2, 2025 Read article
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Classification of Plant Leaf Diseases Using Deep Learning Concepts
Abstract: Agriculture is vital to the economy of a country like India, where 70% of the workforce is employed in this sector. Plants suffering from illnesses experience a significant reduction in output. Delays in the identification of plant diseases lead to decreased yield and plant mortality. The cost of manufacturing is increased since it takes a big number of experts to manually detect plant diseases over several acres of land. The …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 46–55 Read article
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Methods Based on Machine Learning for Large-scale Classification of Crop Leaf Diseases
Abstract: Worldwide productivity of crops is seriously threatened by crop leaf diseases, which can result in large crop losses and negative economic effects. Effective disease management and crop protection depend on the early and precise detection and classification of these illnesses. Machine learning approaches have gained popularity recently due to their ability to automate procedures related to illness diagnosis and classification. An overview of the several machine learning–based methods used for …
Published in International Journal of Computer Science Languages · Vol. 2, Issue 1, 2024 · pp. 11–23 Read article
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Deep Learning based Solution for Leaf disease Detection in Crops and Fertilizer Recommendation
Abstract: The field of agriculture faces significant threats, including diseases that attack plant leaves. To address this issue, our system assists farmers in promptly detecting plant diseases using advanced technology. The user, typically a farmer, only needs to capture an image of the affected leaf and input it into our system. Our system then analyzes the uploaded image to accurately identify the specific disease afflicting the leaf. This analytical process is …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 31–40 Read article
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Crop Disease Prediction by Machine Learning
Abstract: The classification of Crop can be classified into several methods. The data set of crop leaf illnesses, notably Bacterial Leaf Blight disease (BLB), a crop leaf disease with significant outbreaks throughout Thailand, and Brown Spot Crop disease (BSR), is classified employing image classification in this study. Additionally, image processing technology is used for identifying different types of crop leaf disease. These algorithms include the Random Forest, Decision Tree, Gradient Boost, …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 21–25 Read article
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Screening of Mustard Varieties and Lines against Clubroot and Alternaria Leaf Spot Diseases
Abstract: The experiment was conducted to find out the resistant varieties/lines against clubroot and Alternaria leaf spot diseases of mustard at the Plant Pathology Division, RARS Jamalpur, Bangladesh during the Rabi season of 2024-2025 with sixty-two (62) varieties and lines of Mustard collected from Oilseed Research Centre (ORC) and Plant Genetic Resources Centre (PGRC), Joydebpur, Gazipur-1701, Bangladesh. To screen for clubroot and Alternaria leaf spot diseases and to evaluate yield and …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 97–106 Read article
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GreenDiagnosis: Intelligent Crop Disease Detection Using Deep Learning Algorithm
Abstract: Agriculture in parts of India relies on labour-intensive traditions, maintaining disease-free crops is crucial. Manual methods can be inaccurate, driving farmers towards AI-based solutions. AI offers a proactive approach to address real-time farming challenges. Among these is the invasion of pests, which diminishes crop quality. Combating pest-related diseases poses a challenge, prompting innovation. Effective surveillance and early detection of crop diseases play a pivotal role in ensuring global food security …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 8–18 Read article
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An Efficient CNN Model for Automated Cotton Leaf
Abstract: Timely and accurate identification of cotton leaf diseases are essential for maintaining healthy crop production and minimizing agricultural losses. Early detection allows farmers to take preventive or corrective measures, reducing the risk of disease spread and improving overall yield. In this study, we propose a Convolutional Neural Network (CNN) based model for the automated classification of cotton leaf diseases using image-based detection techniques. The model is trained on a diverse …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 3, 2025 · pp. 01–10 Read article
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Transformative Breakthroughs: Revolutionizing Potato Disease Detection Through Machine Learning
Abstract: Advancements in agricultural technology and the integration of artificial intelligence for diagnosing plant and leaf diseases are crucial for sustainable agricultural development. Conditions like early blight and late blight exert a notable influence on both the quality and quantity of potato harvests. Identifying these leaf diseases manually demands significant labor and a considerable level of expertise. Therefore, efficient, and automated methods for disease detection are essential to improve potato production. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 54–62 Read article
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Automated Plant Disease Detection and Treatment Advisor Using Artificial Intelligence
Abstract: Automated plant disease detection and treatment advisors using artificial intelligence represent a significant advancement in modern agriculture. The identification of plant leaf diseases is essential to maintaining food security and agricultural output. Machine learning models, particularly deep learning algorithms like convolutional neural networks (CNNs), are trained on labeled datasets containing images of healthy and diseased plants. These models learn to classify images into different disease categories with high accuracy. Convolutional …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 1–7 Read article
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Status Of Sucking Insect Pests And Yellow Mosaic Disease Incidence In Major Greengram, (Vigna Radiata) Growing Districts Of Karnataka
Abstract: Yellow Mosaic Disease (YMD) and sucking insect pests are the serious problem to greengram growing farmers in Karnataka. Information on the regional distribution of vectors involved and the disease transmitted is essential to manage the pests. In the present study, roving survey was undertaken during Kharif season of 2018 and 2019 in eight major greengram growing districts of Karnataka. The species of sucking pests observed on green gram are whitefly, …
Published in International Journal of Insects · Vol. 1, Issue 1, 2024 · pp. 1–6 Read article
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Agrobot: IoT Enabled Crop-care
Abstract: Agriculture serves as the foundation of global civilization, particularly in nations like India, where it accounts for roughly 70% of the GDP, underscoring its pivotal role in economic stability. Despite its significance, traditional agricultural practices have often overlooked critical elements such as disease identification and precise pesticide application, focusing primarily on conventional methods like harvesting and seedling techniques. To address these gaps and usher in a new era of efficiency …
Published in Journal of Experimental & Applied Mechanics · Vol. 15, Issue 1, 2024 · pp. 38–45 Read article
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Leafguard: Smart Plant Health Detection
Abstract: Machine learning techniques, including traditional (shallow) ML, deep learning (DL), and augmented learning (AL), are being increasingly utilized for leaf disease classification. These methods involve feature extraction, data augmentation, and transfer learning to enhance model effectiveness and reduce the need for labeled data. The success of machine learning approaches in this domain hinges on the quality and quantity of data available. LeafGuard is a cutting-edge device with intelligent sensing systems …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 32–39 Read article
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Curry Leaf Extracts as a Natural Antimicrobial Agent for Eco-Friendly Tomato Disease Control
Abstract: Tomatoes (Solanum lycopersicum) are a vital horticultural crop worldwide, valued for their nutritional and economic importance. However, bacterial diseases significantly threaten yield and quality. This study investigates the antimicrobial potential of Murraya koenigii (curry leaf) extracts as a sustainable alternative to synthetic pesticides. Ethyl acetate, methanol, and aqueous extracts were prepared and tested at 50 and 200 µg/mL against Xanthomonas campestris and Pseudomonas syringae. Ethyl acetate extracts exhibited superior antimicrobial …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 54–58 Read article
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Plant Disease Detection Using Machine Learning
Abstract: Plant diseases significantly threaten global crop yields and affect both nutritional safety and farmer income. Accurate and early detection of plant diseases is essential for effective intervention and treatment. In this study, we used the CNN model (convolutional neural network) to explore a deep learning-based approach for plant disease classification. The model was trained and evaluated on a large dataset encompassing 38 different classes of plant disease, including healthy leaves. …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 2, 2025 · pp. 07–19 Read article
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Plants Disease Detection Using TensorFlow and OpenCV
Abstract: Growing healthy and productive crops is crucial in the global battle for food security. To minimize crop losses and apply timely control measures, early and precise diagnosis of plant diseases is essential. Conventional illness detection techniques are subjective, labor-intensive, and complicated; they frequently rely on eye inspection. The TensorFlow and OpenCV libraries are used in this study to explore the use of Convolutional Neural Networks (CNNs) for plant disease discovery. …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 1, 2024 · pp. 31–38 Read article
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A Review: Carissa Carendas Leaves: Phytochemical Constituents, Traditional Use, and Pharmacological Properties
Abstract: Carissa carendas called Karanda are used in many traditional systems Unani, Ayurveda, homeopathic systems. Traditionally various herbal drugs used in curing many diseases are used singly or in a combination of another herbal drugs. Carissa carendas is all part of plant-like fruit, root, leaves all parts is used to treat many diseases traditionally. Various herbal drugs individually or in combination have been recommended for the treatment of different diseases. The …
Published in Research & Reviews : Journal of Botany Read article