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58 articles for “Loss of agricultural production”
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Assessment of Salinity Extent in Irrigated Agricultural Lands of Arbaminch Zuria and Mirab Abaya Districts in Gamo Zone, South Ethiopia Region
Abstract: AbstractThis study was aimed to assess the extent of salinity in irrigated agricultural lands and extract tangible information for soil and water sample collections in Arbaminch Zuria and Mirab Abaya Districts in Gamo Zone, South Ethiopia Region. The base line survey was collected totally from 114 households of irrigation users from both districts. The result acquired indicates that (83.27%) of the farm land was affected by salinity. According to the …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 12, Issue 3, 2023 · pp. 10–15 Read article
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Urban Expansion and Transforming Land use in Urban Centers of Ranikhet Tehsil, Uttarakhand
Abstract: Urban sprawl is increasing rapidly with the increased rate of rural to urban migration and with the tremendous population growth. Due to rural-urban migration and continuous population growth; urban centers tend to expand outwards to lodge the ever-increasing population pressure. Urban sprawl has to be considered in spatio-temporal terms to understand the phenomena of urban growth, land use and land transformation. Urban sprawl is momentous to the quality of life …
Published in Journal of Remote Sensing & GIS · Vol. 14, Issue 1, 2023 · pp. 39–45 Read article
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Information Technology: An Arising Concept in Agriculture Sector
Abstract: AbstractThe agriculture sector plays predominant role in economy of India. Information Technology is an important branch in the field of agriculture as it provides support to the farming community. Agriculture is the backbone of agro industries. IT contributing one third to the national GDP in the Indian economy. Under the changing dynamics of economical and industrial growth, agriculture has to experience changes with new approaches. The agricultural sector has to …
Published in Journal of Computer Technology & Applications · Vol. 4, Issue 1, 2013 · pp. 23–27 Read article
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CNN-based Approach for Efficient Bell Pepper Leaf Disease Recognition
Abstract: Convolutional Neural Networks (CNNs) have achieved remarkable results in the detection of diseased plant leaves, providing highly accurate predictions. This project offers a comprehensive examination of existing systems designed for the detection of plant-based diseases. Using CNN trained on a dataset of bell pepper plant images, various simulation approaches for neurons and layers were employed. Plant diseases have significant impacts on agricultural productivity, leading to economic losses, reduced crop quality, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 10, Issue 3, 2023 · pp. 16–22 Read article
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Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
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GreenDiagnosis: Intelligent Crop Disease Detection Using Deep Learning Algorithm
Abstract: Agriculture in parts of India relies on labour-intensive traditions, maintaining disease-free crops is crucial. Manual methods can be inaccurate, driving farmers towards AI-based solutions. AI offers a proactive approach to address real-time farming challenges. Among these is the invasion of pests, which diminishes crop quality. Combating pest-related diseases poses a challenge, prompting innovation. Effective surveillance and early detection of crop diseases play a pivotal role in ensuring global food security …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 8–18 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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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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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
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Machine Learning Based Approaches for the Detection and Classification of Crop Leaf Diseases
Abstract: Crop leaf diseases pose a significant threat to agricultural productivity worldwide, leading to substantial crop losses and economic consequences. Timely and precise identification and categorization of these diseases are vital for effective disease management and safeguarding crops. Over the past years, machine learning methods have gained prominence due to their potential to automate disease diagnosis and classification procedures. This review paper presents an overview of the various machine learning based …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 2, 2023 · pp. 31–38 Read article
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Leaf Disease Classification Using Artificial Neural Networks and Decision Tree Classifier
Abstract: Most of the population in India depends on agriculture production. Diseases on plant cause a significant loss of nation’s economy. The Loss can be reduced by identifying the disease at the earlier stage. Leaves are the main indicator of diseases in a plant. Hence efficient automatic leaf disease identification system is the need for the current scenario. As it detects the diseases on leaf immediately after they appear, it prevents …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 5, Issue 1, 2018 · pp. 26–32 Read article
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Revolutionizing Plant Disease Detection: A Comprehensive Review
Abstract: Rise in population demands more food production but the diseases in plants contribute to loss. The advancement in agricultural field has a remarkable effect in detecting plant diseases. These diseases will have a major impact on the quality of plant and yield and hence can destroy the entire plant if they are not controlled on time. To reduce disease-related losses, it is necessary to identify different types of diseases and …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 2, 2023 · pp. 44–55 Read article
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Crossroads of Ecology and Medicine: Evaluating Pollutant-Induced Risks to Biodiversity and Human Health
Abstract: Environmental pollution has emerged as a central challenge at the crossroads of ecology and human medicine. The rapid pace of industrialization, urbanization, and agricultural intensification has led to an unprecedented release of pollutants into the air, water, and soil—triggering cascading effects on ecosystems and human health. Pollutants such as particulate matter, heavy metals, pesticides, microplastics, endocrine-disrupting chemicals, and persistent organic pollutants not only degrade biodiversity but also exert multifaceted health …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 1, 2025 · pp. 41–53 Read article
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Land Use and Land Cover Change: A Comprehensive Review of Environmental Implications
Abstract: Changes in land use and cover have a substantial impact on environmental dynamics and sustainability. These changes arise from various human activities, including urbanization, agriculture, and forestry, and have profound implications for biodiversity, ecosystem services, and land health. As urban areas expand, often at the expense of agricultural and forested landscapes, the transformation of land use alters ecological processes, leading to habitat loss and fragmentation. This article examines the implications …
Published in International Journal of Land · Vol. 1, Issue 2, 2024 · pp. 01–05 Read article
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Separation methods and application possibilities of pyrolysis bio-oil: a short review
Abstract: Bio-oil is a renewable energy source and has many compounds of industrial interest, but it also has undesirable characteristics such as high viscosity, corrosivity and high oxygen content, so separation means are necessary according to its application. There are many methods for the separation of bio-oil, so this review addresses the most used extraction techniques, among them: liquid-liquid, distillation, supercritical fluid extraction, catalytic cracking and adsorption. In addition, pyrolysis oils …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 11, Issue 3, 2022 · pp. 36–49 Read article
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Effective Strategies for Sustainable Soil and Water Management: Enhancing Agricultural Productivity and Environmental Conservation
Abstract: Soil and water are essential natural resources, and their degradation due to erosion, overgrazing and other factors is ongoing. Water erosion is influenced by climate, topography, vegetation and soil, while wind erosion is affected by wind characteristics, surface features, topography and soil properties. Unsustainable land and water management practices lead to reduced soil fertility, soil loss, lower crop yields, water depletion, deforestation, and diminished biomass. Of the 1386 million cubic …
Published in International Journal of Land · Vol. 1, Issue 1, 2024 · pp. 11–36 Read article
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Optimizing Silage Quality: Best Practices for Maximum Nutrient Retention and Sustainable Dairy Development
Abstract: Silage is a critical component in dairy production systems, offering a consistent and high-quality feed source throughout the year. Optimizing silage quality begins in the field, requiring strategic practices to maximize nutrient retention and support sustainable dairy development. This study reviews best practices across silage production stages, including crop selection, timely harvesting, precise chopping, controlled fermentation, and efficient storage techniques. Emphasis is placed on achieving the ideal moisture content, reducing …
Published in International Journal of Nutritions · Vol. 2, Issue 2, 2025 Read article
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Assessment of Soil Erosion Impacts at the Panchhari Sub-district of Chittagong Hill Tracts in Bangladesh Using Remote Sensing and GIS Techniques Based on RUSLE Model
Abstract: Soil erosion has been identified as a significant issue around the world. It is often exacerbated due to land deterioration, conversion of agricultural land, and other anthropogenic activities. It negatively impacts soil productivity, water quality deterioration, river and reservoir bed sedimentation, nutrient loss, and sustainability of natural resources. Understanding the controlling factors of soil erosion can help us to identify erosion-prone areas and improve land use management. The novelty of …
Published in International Journal of Climate Conditions · Vol. 1, Issue 2, 2024 · pp. 9–30 Read article
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Next-Gen Agriculture: Deep Learning Algorithms for Real-Time Plant Disease Detection via IoT
Abstract: In addition to providing high-quality food, the agriculture industry plays a critical role in supporting expanding people and economies. Plant diseases can have a detrimental effect on biodiversity and result in significant losses in food production. Automated methods for early and precise identification of plant diseases can reduce financial losses and enhance the quality of food produced. Deep learning has significantly improved object detection and picture classification accuracy in recent …
Published in Recent Trends in Sensor Research & Technology · Vol. 11, Issue 1, 2024 · pp. 18–23 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