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261 articles for “Crop”
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Crop Metabolism: A Biochemical Perspective on the Synthesis of Key Biomolecules and Structural Adaptations
Abstract: Crop metabolism involves intricate biochemical pathways that govern the biosynthesis of essential biomolecules, ensuring growth, development, and adaptability in various environmental conditions. Key processes include the synthesis of nucleic acids, amino acids, proteins, carbohydrates, organic acids, lipids, and natural products, each playing vital roles in maintaining cellular homeostasis. Nucleic acids drive genetic information storage and transfer, while amino acids and proteins form the backbone of enzymatic and structural cellular functions. …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 1, 2025 · pp. 26–31 Read article
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Crop Yield Prediction Using Machine Learning Algorithm Based on Climate Variables
Abstract: India's economy is based primarily on agriculture, as over 50% of the country's population depends on it for their livelihood. The long-term viability of agriculture is seriously threatened by variations in the weather, climate, and other environmental factors. Because machine learning provides tools for decision assistance in agricultural yield prediction, including guidance on which crops to plant and when to plant them during the growing season, it is essential to …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 49–52 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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Enhancement of Soil Fertility Using Natural Fiber-Based Engineering Composite Materials for Higher Crop Production: A Review Paper
Abstract: Enhancement of Soil fertility using engineering composite materials via efficient nutrient management strategies is essential as is rising natural fiber based composite material crop production every land area unit to satisfy next diets and fiber consumption. Major developments have improved the production's nutrient-use economy Improved crop flexibility to applied nutrients, decreased off shore nutrient move, and greater predictions of the nutrients available to plants in the root zone have all …
Published in Journal of Polymer & Composites · Vol. 12, Issue 6, 2024 · pp. 79–87 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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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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Deep Learning models for real time detection of crop diseases in the Maharashtra/Mumbai district
Abstract: This research project addresses the critical agricultural challenge of crop disease management in the Maharashtra region of India by leveraging modern deep learning techniques. The primary objective is to identify, implement, and compare the efficacy of various deep learning architectures—including Convolutional Neural Networks (CNNs), MobileNet, and EfficientNet—for the real-time classification of diseases in key crops such as cotton, soybean, and sugarcane. A custom dataset of agricultural images specific to Maharashtra's …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 36–48 Read article
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Assessment of Crop Production System and Agricultural Technology Adoption in Afalech Watershed, Shishonde District
Abstract: In a developing country like Ethiopia, agriculture plays an active role in determining the economic, social, and political systems of a society by forming the basis for every economic activity. Methods: The objectives of this study were to identify and examine the major crop production systems and agricultural technology adoption in the Afalech Watershed, Shishonde District of Southwest Ethiopia. Results: The results of this study indicate that enset, coffee, maize, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 97–106 Read article
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Sustainable Cotton Crop Productivity through Precision Weed Detection: A Deep Learning-Based Approach with UAV Integration
Abstract: Weeds present a major challenge to crop productivity by competing with crops for vital resources, including water, sunlight, and nutrients, often resulting in significant yield reductions. On a global scale, weeds are responsible for approximately 13.2% of annual crop losses, a quantity sufficient to feed nearly one billion people. These invasive plants disrupt agricultural systems and adversely impact crop yields. Given their uneven distribution in fields, ground or aerial robots …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 19–26 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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Farmer’s Pal
Abstract: Precision agriculture, characterized by data-driven decision-making, has transformed contemporary farming practices. To increase agricultural sustainability and efficiency, this abstract investigates the combination of sensor monitoring, machine learning, and picture processing. A network of sensors continuously collects vital environmental data, including temperature, humidity, rainfall, sunshine, soil moisture, and conductivity, for precision agriculture. By providing real-time insights, these sensors enable farmers to make informed choices about pest control, fertilization, and irrigation. This …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 19–31 Read article
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Adoption of Major Improved Crop Varieties in Selected Districts of the Southwest Ethiopia Region
Abstract: Agriculture forms the backbone of the Ethiopian economy and significantly contributes to the livelihoods of the majority of the population. It remains a central pillar of food security, employment, and rural development across the country.The present study aims to examine the adoption of improved major crop varieties and to identify the key factors influencing their uptake in the southwest Ethiopia region. The research was carried out in the districts of …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 2, 2026 · pp. 18–31 Read article
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The Effect of a Shift in the Cropping Pattern and Traditional Farming Methods on Sustainable Development (Referring to the Pauri District’s Rural Areas)
Abstract: This research explores the impact of changes in traditional farming methods and cropping patterns on sustainable development in the rural areas of Pauri district, Uttarakhand. Emphasizing the significance of agriculture in the Indian economy, the study delves into factors influencing agricultural techniques, land use, and crop patterns. To investigate the direction of the conventional agricultural pattern shift in Pauri district and the primary variables driving this shift.By addressing the role …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 13, Issue 1, 2024 · pp. 1–10 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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Harvestify: ML Based Tool for Home Gardening and Farming
Abstract: This study presents a cutting-edge application that will transform home gardening and agriculture practices using machine learning (ML) approaches. The main goal is to provide data-driven insights to home gardeners and farmers, enabling them to implement efficient and sustainable farming practices. Crop disease detection, fertiliser recommendation, and a community section for user engagement comprise the three main elements that make up the system's architecture. The Crop Disease Detection module analyses …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 2, 2024 · pp. 18–28 Read article
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Advancements in Plant Molecular Biology and Genetics: Insights into Genetic Engineering, Genomics, and Crop Improvement
Abstract: This comprehensive review explores the rapidly advancing fields of plant molecular biology and genetics, offering a thorough examination of contemporary research and innovative methodologies that contribute to a deeper understanding of plant development, improved crop productivity, and the mitigation of environmental challenges. Recent breakthroughs in genetic engineering, genomics, and transcriptomics are thoroughly analyzed to provide valuable insights into their practical applications for sustainable agriculture. The integration of cutting-edge tools and …
Published in International Journal of Trends in Horticulture · Vol. 2, Issue 1, 2025 · pp. 25–27 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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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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Millets as a Sustainable Crop for Nutritional Security: Addressing Malnutrition Challenges
Abstract: Millets are cereal crops belonging to the Poaceae family, which is the scientific name for the grass family. They are classified into two main groups: major millets which include Sorghum, Pearl, Finger millet, and minor millets, such as Little, Foxtail, Proso, Barnyard, and Kodo millet. India is the chief producer of millets, with an annual production of more than 17 million tonnes. This accounts for 80% of Asia’s millet production …
Published in International Journal of Nutritions · Vol. 2, Issue 1, 2025 · pp. 33–46 Read article
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Morphological, Phenological and Yield assessment of Cosmic Yantras on Solanum lycopersicum L. and Pisum sativum L. crop plants under normal climatic conditions
Abstract: Vegetables are edible plants or parts of plants (roots, stems, leaves, flowers and seeds) that are consumed for their nutritional value. They are rich in vitamins, fiber and antioxidants. The study was conducted in cropping season (April to October 2024) to observe the comparative effect of cosmic yantras and organic manures on growth and morphology of Pisum sativum and Solanum lycopersicum under normal climatic conditions. The objective of this research …
Published in Research & Reviews : Journal of Botany · Vol. 15, Issue 3, 2026 Read article