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78 articles for “crop analysis”
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Smart Agriculture in India: Advancements in Image Processing for Automated Plant Disease Detection and Crop Analysis
Abstract: The adoption of image processing technologies in agriculture is emerging as a revolutionary method for tackling persistent challenges in the farming industry. These techniques are increasingly used for different tasks such as detecting plant diseases, assessing crop health, and predicting yields, especially in the framework of smart agriculture systems. This study paints a detailed picture of the latest progress in image processing techniques applied to automated disease detection and detailed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 13–19 Read article
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A Polymer-Based Recommender System for Precision Agriculture: Enhancing Crop Yield Analysis Using IoT Technology
Abstract: This study introduces an innovative recommender system that employs polymer-based sensors combined with advanced data analytics to deliver personalized recommendations for crop management optimization. The use of polymer-based materials in sensor design allows for the creation of durable, cost-effective, and efficient sensors, well-suited for the challenging conditions typical in agricultural environments. These sensors are designed to withstand variations in numerous factors like temperature of the surrounding, humidity level, and at …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 86–95 Read article
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Jowar Millet Crop Monitoring and Analysis Robot (JMAR): A Smart Solution for Plant and Soil Health in Jowar Millet Farming
Abstract: Farmers cultivating jowar millet (Sorghum) face significant challenges in maintaining crop health and optimizing yield due to the limitations of traditional plant disease detection and soil health assessment methods. Visual inspection and indigenous knowledge are labour-intensive, time-consuming, and often inaccurate, while soil monitoring requires specialized equipment that is not always affordable or accessible. These issues hinder timely intervention and can lead to crop losses and soil degradation. To address these …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 2, 2025 · pp. 8–18 Read article
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A Data-Driven Analysis of Machine Learning Classification Models for Reliable Crop Yield Prediction
Abstract: The adoption of ML technologies in agriculture is reshaping farming practices, empowering producers to make informed, data-oriented decisions that improve yields, sustainability, and long-term resilience. In mango cultivation, ML analyzes data from weather, soil, and pests to optimize irrigation, fertilization, and pest control. Predictive analytics help forecast ideal farming practices, minimizing resource wastage and improving yield. Real-time monitoring and image-based disease detection allow timely interventions to maintain plant health and …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 1, 2026 · pp. 12–17 Read article
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A Multivariate Adaptive Regression Splines Based Study of Soil Parameters and Their Impact on Onion Yield in Bhavnagar District
Abstract: Bhavnagar district is one of the prominent onion-growing areas in the Saurashtra region of Gujarat, encompassing key talukas such as Mahuva, Talaja, Ghogha, Jesar, and Palitana. Onion cultivation in the district is carried out across three distinct seasons: rabi, kharif, and late kharif with harvesting periods extending from April to May for the rabi crop and from October to March for the kharif and late kharif crops. The productivity of …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 53–64 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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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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A Detailed Survey of Machine Learning Applications, Methods, and Future Prospects in Agriculture
Abstract: Agriculture is undergoing a digital transformation driven by machine learning (ML) and artificial intelligence. The integration of ML techniques with data from sensors, drones, satellites, and IoT devices has enabled precision agriculture, early disease detection, optimized resource use, and improved yield prediction. This paper presents a comprehensive review of machine learning applications in modern agriculture, covering key areas such as crop monitoring, soil analysis, irrigation scheduling, pest, and disease detection, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 39–45 Read article
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Integrated Water Balance and Water Stress Index–Based Sustainability Assessment of a Semi-Arid Island Ecosystem
Abstract: Freshwater scarcity is an increasingly critical challenge in semi-arid island environments due to limited natural water availability, high dependence on seasonal rainfall, growing population pressure, and expanding agricultural activities. Island ecosystems are particularly vulnerable to water stress because they often lack perennial surface water sources and rely heavily on groundwater recharge during short and highly variable monsoon periods. This study presents a comprehensive assessment of water demand, post-monsoon water availability, …
Published in Journal of Water Pollution & Purification Research · Vol. 13, Issue 1, 2026 · pp. 26–41 Read article
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Smart Gardening: Simplified Seed Sowing Techniques
Abstract: The primary objective of the exhibiting operation is to plant seed and fertilizer in rows at the proper depth and seed-to-seed spacing, cover the seeds with soil, and make sure there is enough compaction over the seed. To get the maximum yields, different recommended row-to-row spacing, seed rate, seed-to-seed spacing, and depth of seed placement are required for different agro-climatic conditions and crop kinds. A comparative analysis is conducted between …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 2, Issue 1, 2024 · pp. 20–28 Read article
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Advancements in Agricultural Forecasting: A Review of Machine Learning Based Crop Yield Prediction
Abstract: Agricultural productivity plays a critical role in global food security, and accurate crop yield prediction is essential for optimizing resource allocation and decision-making in farming. The rapid advancements in Machine Learning (ML) and Deep Learning(DL)have transformed agricultural forecasting, enabling data-driven approaches for crop prediction. This review paper provides a comprehensive analysis of various ML and DL techniques applied in crop yield forecast, highlighting the ineffectiveness, challenges, and future directions. The …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 32–38 Read article
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A Python-Based Investigation of Clinical Data and Ultrasound Images for PCOS Diagnosis
Abstract: PCOS is a common endocrine disorder that impacts women in their reproductive years characterized by irregular menstrual cycles, hyperandrogenism, and polycystic ovaries. The full diagnostic plan is mainly a combination of a pelvic ultrasound besides blood tests of specific parameters that indicate the presence of PCOS. Since PCOS is a hard-to-diagnose widespread hormonal disorder, blood tests, symptoms, and other parameters with the help of a computer can form a new …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 2, 2025 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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Synthesis, Production, and Mass Balance Analysis of Ten High-Volume Herbicides
Abstract: Herbicides play a crucial role in modern agriculture, enabling effective weed management and safeguarding crop yields amid rising global food demands and growing weed resistance, which can reduce productivity by up to 40%. This study provides a detailed examination of synthesis pathways, production methodologies, and mass balance dynamics for ten high-volume herbicides: Aclonifen, Ametryn, Amidosulfuron, Aminocyclopyrachlor, Aminopyralid, Atrazine, Azimsulfuron, Beflubutamid, Bensulfuron Methyl, and Bentazone, used to control broadleaf weeds, grasses, …
Published in Emerging Trends in Chemical Engineering · Vol. 12, Issue 3, 2025 · pp. 30–44 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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Non-Lethal Protection of Farmlands Against Wild Animals and Crop Estimation
Abstract: This paper is an integrated smart system that aims to enhance productivity related to agriculture along with agricultural safety through modern technology. Crop estimation system uses IoT sensors and machine learning algorithms for the analysis of real-time environmental data in terms of soil moisture, temperature, pH levels, and humidity. This data will further be used to provide the optimal crop for cultivation and appropriate fertilizer requirements for prediction of requirements. …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 1, 2025 · pp. 18–24 Read article
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Transforming Agricultural Waste into Opportunities: Crop Residues for Sustainable Livestock Feeding and Productivity
Abstract: As global agricultural systems strive to meet the growing demand for livestock products while minimizing environmental impact, the sustainable utilization of crop residues has emerged as a key strategy for improving feed resource availability. In Bangladesh and many other developing regions, vast quantities of crop residues are produced annually, yet their potential as a valuable feed resource remains underutilized. This review evaluates the role of crop residues in livestock feeding, …
Published in Research and Reviews : Journal of Dairy Science and Technology · Vol. 13, Issue 3, 2024 · pp. 12–21 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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Enhancing Farm Efficiency with IoT-Driven Real-Time Monitoring and Analysis
Abstract: This project proposes an Internet of Things (IoT) solution for enhancing agricultural practices by leveraging real-time data monitoring and analysis. The system utilizes NodeMCU, DHT11, pH sensor, soil moisture sensor, and an LCD display for data collection and visualization. NodeMCU facilitates internet connectivity, enabling the transmission of data to the ThingSpeak platform. Temperature and humidity are measured by the DHT11 sensor, and soil acidity is tracked by the pH sensor. …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 14, Issue 2, 2024 · pp. 9–15 Read article
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Determinants of the Adoption of chemical Fertilizer in Kaffa, Bench Sheko and Sheka zones of Southwest Ethiopia
Abstract: Agriculture is the backbone of the Ethiopian economy, but the production system was backward, and the adoption of agricultural technology was low. This study aims to identify and determine factors affecting smallholder farmers' adoption of chemical fertilizer. Bita, Chena, Andiracha, and Sheyi Bench district of the southwest Ethiopia region was selected for this study. Household individual survey interview, key informant interview, and focus group discussion were the primary data collection …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 1–12 Read article