Agriculture
40 articles · search the full text for this term
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A SHAP - Enhanced Voice-Based Conversational Agent for Agriculture Using BERT
Abstract: The integration of advanced artificial intelligence technologies into modern agriculture has become increasingly important for narrowing the persistent knowledge gap faced by farmers, especially in regions with limited access to expert advisory services. While state-of-the-art language models such as BERT (Bidirectional Encoder Representations from Transformers) demonstrate exceptional performance in understanding and generating natural language, their opaque “black-box” nature often limits user confidence, trust, and widespread adoption. Farmers may hesitate to …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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Evaluation of Organic-Mineral Fertilizer Components: A Multi-Criteria Analysis Based on Various Factors
Abstract: This study explores the potential of organic-mineral fertilizers as sustainable alternatives to synthetic options, evaluating ten such fertilizers, including coffee grounds, poultry eggshells, bone meal, Fish Emulsion, compost, cow manure, wood ash, biochar, seaweed extract, and green manure. A multi-criteria analysis assessed factors like effectiveness, cost, environmental impact, availability, and waste potential. Coffee grounds and poultry eggshells performed best due to their high nutrient content and positive soil effects, with …
Published in International Journal of Trends in Horticulture · Vol. 2, Issue 2, 2025 · pp. 29–42 Read article
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Fertiledata: Advanced Strategies For Crop Optimization Through Machine Learning Processing
Abstract: The venture, titled "Fertile Data: Advanced Strategies for Crop Optimization Through Machine Learning processing" is created utilizing HTML, CSS, and JavaScript for the front conclusion, and Python for the back conclusion. In a nation like India, where a noteworthy parcel of the populace depends on agribusiness for their vocation, joining progressed advances such as Machine Learning and Profound Learning into cultivating hones can revolutionize the industry. This venture presents a …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 25–35 Read article
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Study of Agriculture Using Drones in India: Evaluation of Feasibility, Impact, and Adoption Challenges
Abstract: Studies in India show that drone technology is revolutionizing agriculture by enabling precision farming, increasing crop yields, reducing costs, and improving sustainability. Key applications include using drones for efficient spraying, crop monitoring via multispectral sensors, soil health analysis, and optimized water management. Government initiatives like the "Kisan Drones" program are promoting adoption, supported by research that demonstrates significant benefits like yield increases and resource savings[1-3]. Figure 1 shows the usage …
Published in International Journal on Drones · Vol. 1, Issue 2, 2025 · pp. 21–33 Read article
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A Thorough Examination of How Artificial Intelligence is Affecting the Transformation of Agriculture in India and Throughout the World
Abstract: By providing creative ways to increase crop yields, maximize resource usage, and advance sustainability, artificial intelligence (AI) is revolutionizing agriculture. AI technologies, such as machine learning, computer vision, and robotics, are being increasingly used in precision farming, crop monitoring, disease detection, and decision-making as the global agricultural sector faces pressing challenges like food security, population growth, and climate change. AI enables farmers to make data-driven decisions, optimize irrigation systems, monitor …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 39–45 Read article
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A Study on Unmanned Air Vehicles (UAV)
Abstract: Unmanned Air Vehicles (UAVs), commonly known as drones, represent one of the most transformative technologies of the 21st century, rapidly evolving from their initial military applications into a diverse array of civilian and commercial uses. This study explores the rapid proliferation of UAV technology, highlighting its profound impact across sectors such as logistics, agriculture, infrastructure inspection, communication, and public safety. We discuss the inherent advantages UAVs offer, including enhanced efficiency, …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 24–36 Read article
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Design and Implementation of Lightweight Polymer-Based Drone System for Targeted Agricultural Spraying
Abstract: Agriculture has entered a new era of innovation, with drone technology emerging as a key tool in pesticide and fertilizer application. Unlike conventional methods that expose farmers to hazardous chemicals resulting in health issues such as skin disorders, neurological impairments, and in extreme cases, fatal illnesses drone-based spraying offers a safer and more efficient alternative. In India, the adoption of this technology is accelerating due to its ability to reduce …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 476–486 Read article
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Store Management System
Abstract: E-commerce into agriculture has significantly changed the existing structures of the agricultural markets. For farmers, it provides a direct outlet to sell their farm products and for consumers, it offers the opportunity to buy fresh and organic farm products. Here we report the design and development of an e-commerce web application for agricultural trading that not only makes use of modern web technologies but also allows farmers to list their …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 01–9 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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E-Commerce Platform for Agricultural Products
Abstract: The e-commerce platform for agricultural products reported here is designed to solve the problems faced by shop owners, such as managing data, billing, and selling products. In many rural areas, awareness of technology is still low. By introducing this project, rural shopkeepers can learn to use new technologies, making their work easier, faster, and more efficient. Our platform specifically targets village shopkeepers, aiming to help them improve profits. It includes …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 2, 2025 · pp. 28–34 Read article
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Fungus Detection System
Abstract: This project identifies fungal pathogens in wet soil with sensors and gives an instant result through an Android app. It helps farmers avoid crop loss, increase yield, and encourage eco-friendly farming practices by enabling early detection and evidence-based decision-making for soil health management. Soil condition is most important to agriculture and environmental health. Having fungus in pre-maturity soil analysis can prevent crop damage and increase the yield. This project seeks …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 30–34 Read article
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Fertile Data: Advanced Strategies for Crop Optimization Through Machine Learning Processing
Abstract: The venture, titled "FertileData: Advanced Strategies for Crop Optimization Through Machine Learning processing" is created utilizing HTML, CSS, and JavaScript for the front conclusion, and Python for the back conclusion. In a nation like India, where a noteworthy parcel of the populace depends on agribusiness for their vocation, joining progressed advances such as Machine Learning and Profound Learning into cultivating hones can revolutionize the industry. This venture presents a user-friendly …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 2, 2025 · pp. 25–35 Read article
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Leveraging Deep Learning and Cloud Computing for Water Usage Optimization in Agriculture: A Study
Abstract: Water scarcity and inefficient irrigation practices are significant challenges in modern agriculture. This research investigates how deep learning and cloud computing can be combined to enhance water efficiency in agricultural practices. Leveraging advancements in deep learning and cloud computing, researchers have developed innovative solutions for optimizing water usage. This review examines the state-of-the-art methodologies, technologies, and applications in smart irrigation systems. It explores how deep learning models and cloud platforms …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 83–91 Read article
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A Multi-Criteria Analysis Based on Various Factors for Evaluation of Organic-Mineral Fertilizer Components
Abstract: This study explores the potential of organic-mineral fertilizers as sustainable alternatives to synthetic options, evaluating ten such fertilizers, including coffee grounds, poultry eggshells, bone meal, Fish Emulsion, compost, cow manure, wood ash, biochar, seaweed extract, and green manure. A multi-criteria analysis assessed factors like effectiveness, cost, environmental impact, availability, and waste potential. Coffee grounds and poultry eggshells performed best due to their high nutrient content and positive soil effects, with …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 32–44 Read article
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Smart Soil Health Monitoring: Leveraging Sensors and Big Data to Optimize Crop Growth
Abstract: The increasing demand for sustainable farming practices has necessitated the development of innovative technologies that improve crop productivity while reducing environmental harm. This study investigates the combination of internet of things (IoT) sensors and big data analytics for real-time soil health monitoring, with the aim of maximizing crop yield and efficient resource management. This allows for informed decision-making in key agricultural practices, such as fertilization, irrigation, and crop rotation, based …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 2, 2025 · pp. 36–43 Read article
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Strategies of Biopesticide Development and Application: The Hype and Hope
Abstract: This review presents a comprehensive analysis of biopesticides, examining their types, mechanisms of action, and role as eco-friendly alternatives to conventional chemical pesticides. It provides insights into the development strategies of biopesticides and explores their effectiveness in managing agricultural pests. The review also discusses market trends, identifying challenges and strategies faced by manufacturers and stakeholders in promoting biopesticides. It addresses the increasing interest in these sustainable solutions, distinguishing between the …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 15, Issue 2, 2025 · pp. 34–50 Read article
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Unmanned Aerial Vehicle Using AI-ML
Abstract: Remotely piloted aircraft systems (RPAS), commonly known as drones, have evolved significantly in recent years, revolutionizing various industries and domains. This article provides an overview of the key aspects of RPAS technology, their applications, and the impact they have had on society. RPAS are autonomous or semi-autonomous aerial vehicles that can be controlled remotely, offering diverse capabilities, from data collection and surveillance to cargo delivery and recreational activities. This abstract …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 1, 2025 · pp. 11–19 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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The Impact of Climate Change on Jute Production in Gaibandha District, Bangladesh
Abstract: Jute plays a crucial role in Bangladesh’s agricultural economy, especially in Gaibandha District, where it is a key crop for rural livelihoods. However, climate change, characterized by rising temperatures and unpredictable rainfall, poses significant threats to jute production. While numerous studies have explored the broader impact of climate change on agriculture, there is a gap in understanding how localized climate conditions specifically affect jute farming in Gaibandha, with many existing …
Published in International Journal of Climate Conditions · Vol. 2, Issue 1, 2025 · pp. 1–17 Read article
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Havoc of Papaya Mealybug (Paracoccus marginatus) and Its Management Strategies
Abstract: The papaya mealybug (Paracoccus marginatus) is a serious problem that affects mulberries, citrus, and papaya among other agricultural and horticultural crops. Originating in Central America, it has spread around the world and caused extensive harm because of its capacity to consume plant sap, which results in reduced crop yields, fruit drop, and chlorosis. In addition, the insect releases honeydew, which encourages the development of sooty mold, further impeding photosynthesis and …
Published in International Journal of Insects · Vol. 2, Issue 1, 2025 · pp. 12–16 Read article