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176 articles for “crop productivity”
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Nanotechnology and Nanoparticles for High Altitude Agro-ecosystem and Environmental Sustainability
Abstract: High-altitude agro-ecosystems are widely distributed throughout the world. In the Indian subcontinent, Himalayan region represents the high-altitude ecosystems, which demand extensive management due to their increasing deterioration in recent times. The extremely low temperature, proneness to natural calamities, recurring floods, droughts, low soil moisture and fertility, high solar intensity impose constraints for sustenance of hill agriculture. To enhance crop productivity to sustain increasing population, hill farmers are using excessive amount …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 155–164 Read article
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The Impact of Environmental Changes on Indian Agriculture: Strategies for Resilience
Abstract: With more than 61 years of independence, the portion of agriculture in the whole national revenue has been come down from 50 percent in the year 1950 to 18 percent in the year 2007-08. But, as sup above specified, more than 60 percent of workforce in the country are involved in the agricultural activity. But the economy in general depends to a great extent on the performance of agriculture. For …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 13, Issue 3, 2024 · pp. 01–08 Read article
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Mathematical Models of Agricultural Cycles in Tribal Astronomy
Abstract: This paper delves into the intricate connection between traditional tribal agricultural practices and astronomical observations, showcasing how indigenous communities have historically relied on celestial movements to guide essential farming activities. By observing the phases of the moon, solar cycles, and the positions of star constellations, tribes have developed precise methods for determining the optimal timing for planting, harvesting, and seasonal planning. These astronomical practices are deeply embedded in their cultural …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 Read article
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Tea Waste Recovery System
Abstract: The Tea Waste Recovery Management System aims to solve the problem of waste from tea shops, which can harm the environment and waste valuable resources. Every day, tea shops throw away large amounts of used tea powder, causing pollution and missing the chance to recycle these organic materials. If tea waste is not managed properly, it can pile up in landfills, releasing harmful gases into the air. This not only …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 15, Issue 2, 2025 · pp. 1–7 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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Climate-Induced Drought, Food Insecurity, and Adaptation Governance: A Multiscale Review of Risks and Policy Responses in Africa and South Asia
Abstract: Drought is one of the most critical climate-induced hazards, severely affecting agricultural systems, water resources, and human well-being, particularly in Sub-Saharan Africa and South Asia. This review provides a comprehensive analysis of the multidimensional impacts of drought by examining its effects on food security, population displacement, and institutional adaptation across selected case studies from West Africa, South Africa, and coastal Bangladesh. The findings reveal that increasing climate variability and prolonged …
Published in International Journal of Environmental Planning and Development Architecture · Vol. 4, Issue 1, 2026 · pp. 1–8 Read article
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Photochemical Detoxification of Arsenic- and Mercury-Contaminated Soils: Geochemical Mechanisms and Pathways
Abstract: This study evaluates the geochemical aspects of soil detoxification in areas contaminated with arsenic (As) and mercury (Hg), emphasizing sustainable strategies for improving soil health and ensuring safe crop production. The research provides an ecological and toxicological assessment of regional soils and classifies them base on the concentration and mobility of toxic elements. Although the current levels of As and Hg do not yet present a critical risk to agricultural …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 4, Issue 1, 2026 · pp. 06–10 Read article
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Prospects and Growth Opportunities of Female-Owned Rural Farm Businesses in Plateau State, Nigeria
Abstract: The potential and growth chances of female-owned rural agricultural companies in Nigeria's Plateau State were investigated in this study. The objectives were to assess the prospects and opportunities available to female-owned rural farm businesses and to determine their effect on business growth and development across the state. The study covered female farm business owners engaged in crop production, livestock farming, mixed farming, and agro- processing across all 17 Local Government …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 16, Issue 2, 2026 Read article
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Review on Automatic Irrigation System
Abstract: The Automatic Irrigation System is a contemporary technological innovation aimed at improving water efficiency in farming and landscaping uses. This system guarantees that water reaches plants according to real-time data including soil moisture, weather conditions, and set irrigation schedules by combining sensors, microcontrollers, and automated valves or pumps. The main objective of an automated irrigation system is to increase water efficiency, decrease waste, and boost crop production while limiting human …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 2, 2026 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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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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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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Silage Beyond Green Fodder: Nutritional, Health, Economic and Environmental Implications for Sustainable Livestock Production
Abstract: Silage is a pivotal component in modern livestock feeding systems, offering far more than just an alternative to green fodder. This study explores the multifaceted roles of silage in enhancing livestock nutrition, health, and overall farm sustainability. The preservation of crops through fermentation allows for year-round availability of high-quality feed, ensuring consistent nutritional intake, particularly during periods of forage scarcity. Beyond its basic function as a feedstuff, silage improves the …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 01–23 Read article
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Crop residue management by different Farm machinery
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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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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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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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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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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Causes and Measures to Control Root Rot Fungus in Mulberry Ecosystem
Abstract: Root rot is a severe plant disease caused by various soil-borne fungi, including Phytophthora sp., Pythium sp., Rhizoctonia sp., Fusarium sp., and Armillaria sp. These pathogens attack plant roots, leading to decay, stunted growth, wilting, yellowing leaves, and plant death. Root rot typically develops in waterlogged soils with poor drainage, as these conditions create an environment favorable for fungal growth. Factors such as warm temperatures, compacted soil, improper watering practices, …
Published in International Journal of Fungi · Vol. 1, Issue 2, 2024 · pp. 36–41 Read article
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Machine Learning for Soil Moisture Detection: Introduction, Approaches and Challenges
Abstract: The demand for agricultural is increasing day by day as the population of the world is increasing. So, it becomes necessary for us to increase the production of agricultural products. Traditional ways of agriculture cannot meet such requirements. Nowadays, machine learning based technologies are being used to develop models for agriculture. Machine learning-based applications are very fast and produce high-quality results. It includes recurrent neural networks (RNN), convolution neural networks …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 88–96 Read article