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117 articles for “crop yield”
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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 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 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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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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The Role of Precision Agriculture in Enhancing Horticultural Crop Yields
Abstract: This article explores the quantification of lithium and mapping of mineral composition in crushed lithium ore utilizing two distinct calibration techniques with Laser-Induced Breakdown Spectroscopy (LIBS). Thirty samples from a pegmatite lithium deposit were analyzed, with representative mineral samples extracted, mixed with resin, and polished into disks. These disks underwent examination via an analyzer and an integrated mineral analyzer, facilitating mineral identification. The first calibration technique used empirical mineral chemistry …
Published in International Journal of Trends in Horticulture · Vol. 1, Issue 1, 2024 · pp. 18–23 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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Fertilizer Prediction Using Machine Learning
Abstract: Fertilizer prediction is a critical aspect of modern agriculture, aimed at optimizing resource utilization while maximizing crop yields. In recent years, machine learning (ML) techniques have emerged as powerful tools for addressing this challenge by leveraging data-driven approaches to predict the optimal type and quantity of fertilizer required for different crops and soil conditions. This research paper provides a comprehensive review of the existing literature and methodologies employed in fertilizer …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 2, 2024 · pp. 26–35 Read article
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Multivariant Disease Detection from Different Plant Leaves and Classification
Abstract: Agricultural growth is significant in Indian GDP which is based on yield of crops, quality of the plants and procedure of the plants taken. To maintain good quality of plant, the plant diseases should be identified and then given proper suggestions to farmers for specific fertilizers and pesticides to be used. The use of specific fertilizers or pesticides makes plant more health with good quality so that farmers can get …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 27–35 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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Restoration of Degraded Agricultural Soils Through Organic Amendments and Sustainable Farming Practices
Abstract: This study investigates the efficacy of organic amendments and sustainable farming practices in restoring degraded agricultural soils, addressing a critical global challenge affecting food security and environmental sustainability. The research was conducted over three growing seasons on degraded semi-arid agricultural land, utilizing a randomized complete block design with five treatments: The following farming practices: pure control, organic amendments but market conventional farming practices, sustainable farming practices but market standard conventional, …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 13, Issue 3, 2024 · pp. 19–27 Read article
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Contribution, Limitations and Future Of Plant Growth Promoting Consortium in Sustainable Agriculture
Abstract: Current agricultural methods rely significantly on chemical fertilizers, pesticides, and other agrochemicals to enhance plant growth and combat pathogens, aiming to boost crop yields. However, the accumulation of chemical residues in the soil diminishes soil fertility considerably over a period. These accumulated chemicals gradually alter the soil's chemical composition, ultimately rendering it infertile. The high-risk conditions associated with these agricultural chemicals such as bioaccumulation, chemical toxicity and development of resistance …
Published in Research & Reviews : Journal of Botany · Vol. 13, Issue 2, 2024 · pp. 29–51 Read article
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Plant Disease Detection Using Machine Learning
Abstract: Plant diseases significantly threaten global crop yields and affect both nutritional safety and farmer income. Accurate and early detection of plant diseases is essential for effective intervention and treatment. In this study, we used the CNN model (convolutional neural network) to explore a deep learning-based approach for plant disease classification. The model was trained and evaluated on a large dataset encompassing 38 different classes of plant disease, including healthy leaves. …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 2, 2025 · pp. 07–19 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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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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Smart Crop Recommendation Using IoT Sensor for Precision Agriculture
Abstract: This study addresses precision agriculture, which leverages modern technologies to enhance farming efficiency and sustainability. This study proposes a Smart Crop Recommendation System using IoT sensors to optimize crop selection based on real-time environmental conditions. The system integrates multiple sensors, including a temperature sensor, flame sensor, soil sensor, moisture sensor, and LDR sensor, to monitor crucial parameters such as temperature, soil moisture, light intensity, and fire hazards. An Arduino microcontroller …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 3, 2025 · pp. 29–41 Read article
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Effect of Different Doses of Phosphorus on the Growth and Yield of Mung Bean (Vigna radiata L.)
Abstract: Phosphatic fertilizers play a vital role in enhancing mung bean production by not only improving crop yield but also increasing the quality of the produce. A field trial was done at the Nepal Polytechnic Institute research field to determine the effect of different levels of phosphorus on yield of Mung bean at Bharatpur, Chitwan during the summer season 2024. The test was carried out as per Randomized Complete Block Design …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 1–7 Read article
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Evaluation of Irrigation Regime on Onion Yield in Konta Special Woreda, Ethiopia
Abstract: Irrigation scheduling (when and how much to apply) is the primary tool to improve water use efficiency, increase crop yields, increase the availability of water resources, and contribute positive effect for the quality of soil and ground water. Field experiment was conducted for two consecutive years to determine appropriate scheduling of onion production. The experiments were arranged in randomized complete block design (RCBD) with four treatments (T1 = 125% manageable …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 16, Issue 1, 2025 · pp. 9–14 Read article
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Assessment of Agricultural Potentials and Constraints of Natural Resources Management for Research Implementation in Gedeo Zone South Ethiopia Region
Abstract: This study aimed at assessing agricultural potentials and constraints of natural resources management for research implementation in Gedeo zone south Ethiopia Region. The result indicates that the use of organic and inorganic fertilizers was not efficient and the crop yield was decreasing from year to year. Use of organic fertilizer is for only high value crops of enset and coffee without determined rate. Farmers were not practiced organic fertilizers like …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 2, 2026 · pp. 82–93 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