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73 articles for “Crop Disease”
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Kisan Mantra: Enhancing Farmer Productivity, A Web-Based Approach for Efficient Crop Harvesting and Problem Diagnosis
Abstract: India's agricultural sector faces persistent challenges, including limited access to expert guidance, difficulties in managing diverse datasets, unreliable weather forecasting, and a lack of real-time monitoring for farm activities and crop quality. Additionally, farm lenders struggle to obtain accurate insights into farm productivity and risks, hindering their ability to provide tailored financial solutions. The sector also grapples with underemployment among educated professionals, limiting their contributions to agricultural advancement. To tackle …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 71–87 Read article
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Leveraging Artificial Intelligence for Precision Agriculture: Opportunities and Challenges
Abstract: AI in the agriculture sector is slowly changing the face of farming and the way it is practiced through enhanced precision, efficiency and sustainability. This study explores the role of AI in precision agriculture, focusing on its potential to revolutionize crop management, soil health monitoring, pest and disease control, and resource optimization. We examine the various AI technologies, including machine learning, computer vision, and robotics, that are being leveraged to …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 1, 2025 · pp. 28–40 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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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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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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Multivariant Disease Detection from Different Plant Leaves and Classification
Abstract: Agricultural growth is significant in Indian GDP which is based on yield of crops, quality of the plants and procedure of the plants taken. To maintain good quality of plant, the plant diseases should be identified and then given proper suggestions to farmers for specific fertilizers and pesticides to be used. The use of specific fertilizers or pesticides makes plant more health with good quality so that farmers can get …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 27–35 Read article
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Revolutionizing Agriculture with Advanced Computer Vision Technologies
Abstract: The integration of computer vision technology in smart agriculture has marked a significant advancement in the way farming operations are conducted, leading to enhanced productivity and efficiency. This paper explores the multifaceted applications of computer vision, which include crop monitoring, disease detection, automatic harvesting, and quality inspection. By utilizing high-resolution imaging and advanced algorithms, farmers can achieve real-time insights into crop health and growth stages, enabling them to make informed …
Published in Journal of Electronic Design Technology · Vol. 16, Issue 2, 2025 · pp. 24–30 Read article
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The Future is Bioengineered: Consequences, Directions, and Regulation
Abstract: Biotechnology is changing how people interact with health, life, and the environment very quickly. This article talks about how new tools in genetic engineering, synthetic biology, and bioinformatics are making it possible for scientists to build and change biological things with more accuracy than ever before. Biotechnology is changing several fields, from making personalised medical treatments and disease-resistant crops to making biofuels and materials that break down naturally. The talk …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 16, Issue 1, 2026 Read article
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A Review of Automated Pomegranate Disease Detection and Classification Using Machine Learning
Abstract: The abstract outlines a research study focused on developing an automated system for detecting and classifying diseases that affect pomegranate fruits. Pomegranates, like many other crops, are vulnerable to several types of diseases that appear as visible colored spots on the fruit’s surface. These visible symptoms, such as lesions or discoloration, can significantly impact the fruit’s quality, market value, and yield. Therefore, timely and accurate identification of such diseases is …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 01–13 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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Integrating Biotechnology, Physiology, and Agroecological Practices for Sustainable Crop Production and Protection
Abstract: Global agriculture is currently confronting a wide range of complex challenges, including a rapidly growing population, climate change, increasing pest and disease pressures, soil degradation, water scarcity, and the urgent need for sustainable intensification of crop production. Addressing these issues requires integrated strategies that combine crop improvement (through modern breeding and biotechnology), precision agronomic practices related to soil, irrigation, and nutrition, as well as advancements in plant physiology, molecular biology, …
Published in International Journal of Trends in Horticulture · Vol. 2, Issue 2, 2025 · pp. 1–6 Read article
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A review on polyhouse monitoring system
Abstract: The integration of Internet of Things (IoT) technology in agriculture has revolutionized traditional farming practices, offering innovative solutions to enhance productivity, sustainability, and resource efficiency. This study explores the role of loT-based systems in smart agriculture, focusing on applications such as environmental monitoring, automated irrigation, crop health prediction, and precision farming. The reviewed systems utilize advanced sensors to monitor parameters like temperature, humidity, soil moisture, and light intensity, transmitting real-time …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 2, 2025 · pp. 1–9 Read article
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Fields of Data: Exploring AI’s Impact on Modern Farming
Abstract: The Food and Agriculture Organization (FAO) of the United Nations projects that by 2050, there will be a further 2 billion people on the planet, but just 4% of that additional land will be used for agriculture. Under such circumstances, the most recent technical developments and solutions to the farming industry’s obstacles can be used to achieve more effective farming methods. The direct implementation of machine intelligence or artificial intelligence …
Published in International Journal of Solid State Innovations & Research · Vol. 1, Issue 2, 2023 · pp. 14–20 Read article
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Recent Advances in Smart Polymer Composites for Plant Health Monitoring: A Strategic Integration of Sensing Mechanisms and Computational Intelligence
Abstract: Plant health assessment is crucial for agricultural production and food security, as plant diseases significantly affect crop yields and quality. This paper reviews the applications of polymers and composite materials in the evaluation of plant health, focusing on both natural and artificial polymers, carbon materials, and polymeric–nanoparticle composite materials. Various types of sensing principles, such as colorimetry, fluorimetry, surface plasmon resonance (SPR), surface enhanced Raman scattering (SERS), and interferometry, are …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Assessing the Effectiveness of New Fungicides Against Potato Late Blight Disease (Phytophthora Infestans)
Abstract: An experiment was conducted in the field of the Plant Pathology Division, Regional Agricultural Research Station (RARS), Bangladesh Agricultural Research Institute (BARI), Jamalpur, Bangladesh during the rabi season of 2024–2025 to determine the appropriate chemical fungicide for controlling late blight disease of potato. The evaluation included twenty-five new fungicides approved by the Pesticide Technical Advisory Committee (PTAC), Bangladesh, along with a standard control (Ridomil Gold MZ 68 WG) and an …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 28–38 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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Applications of Nanotechnology in Crop Improvement: New Era of Agriculture
Abstract: It represents a transformative force in agriculture, promising to improve the productivity, yield, sustainability, and food security. This review paper focused on the certain advantages of nanoscience and nanotechnology in enhancing the agricultural productivity, disease management, and food safety. By manipulating different materials and objects at the nanoscale, researchers can develop advanced tools such as smart sensors and targeted delivery systems that improve nutrient absorption and combat plant pathogens. By …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 3, 2025 · pp. 46–54 Read article
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Organic Farming
Abstract: Organic farming is an agricultural production management system that excludes all synthetic off-farm inputs and instead relies on on-farm agronomic, biological, and mechanical practices. This sustainable approach focuses on methods such as crop rotations, the use of crop residues, animal manures, off-farm organic waste, and mineral-grade rock additives to maintain soil fertility and health. Organic farming also employs biological systems for nutrient mobilization and plant protection, reducing or eliminating the …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 1, 2025 · pp. 1–8 Read article
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Intelligent Farming: Integrating AI and IoT for Sustainable Agriculture
Abstract: Artificial Intelligence (AI) and the Internet of Things (IoT) are transforming modern agriculture by enabling data-driven, resource-efficient, and climate-resilient farming practices. This review critically examines recent advances in AI-IoT integration across crop production, irrigation management, pest and disease surveillance, and supply chain optimization through an analysis of published literature and documented case studies. The review indicates that AI-assisted predictive analytics combined with IoT-based real-time sensing significantly improves decision-making in precision …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 2, 2026 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