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Hawkins, E
Rabia, A.H
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Authors
Colley III, R
Fulton, J
Virk, S
Hawkins, E
Fulton, J.P
Hawkins, E
Colley III, R
Port, K
Shearer, S
Klopfenstein, A
Fulton, J.P
Shearer, S.A
Gauci, A
Lindsey, A
Barker, D
Hawkins, E
Fulton, J.P
Hawkins, E
Shearer, S
Klopfenstein, A
Hartschuh, J
Custer, S
Rabia, A.H
Eldeeb, E
Rabia, A.H
Eldeeb, E
Coppola, A
Fulton, J.P
Wilson, D
Tietje, R
Hawkins, E
Rabia, A.H
Allam, D.G
Abdelaty, E.F
Abderaouf, E.A
Rabia, A.H
Salem, M.A
Salem, M.A
Rabia, A.H
Topics
Site-Specific Nutrient, Lime and Seed Management
On Farm Experimentation with Site-Specific Technologies
On Farm Experimentation with Site-Specific Technologies
In-Season Nitrogen Management
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Land Improvement and Conservation Practices
On Farm Experimentation with Site-Specific Technologies
Big Data, Data Mining and Deep Learning
Precision Crop Protection
Type
Oral
Poster
Year
2018
2022
2024
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1. Field Level Management and Data Verification of Variable Rate Fertilizer Application

Increased cost efficiencies and ease of use make spinner-disc spreaders the primary method of applying fertilizers throughout much of the United States. Recently, advances in spreader systems have enabled multiple fertilizer products to be applied at variable application rates. This provides greater flexibility during site-specific management of in-field fertility. Physical and aerodynamic properties vary for fertilizer granules of different sources and densities, these properties in turn affect... R. Colley iii, J. Fulton, S. Virk, E. Hawkins

2. eFields – An On-Farm Research Network to Inform Farm Recommendations

On-farm research has been traditionally used to provide local, field-scale information about agronomic practices. Farmers tend to have more confidence in on-farm research results because they are perceived to be more relevant to their farm operations compared to small plot research results. In recent years, more farmers have been conducting on-farm studies to help evaluate practices and input decisions.  Recent advances in precision agriculture technologies have stream-lined the on-farm... J.P. Fulton, E. Hawkins, R. Colley iii, K. Port, S. Shearer, A. Klopfenstein

3. Limitations of Yield Monitor Data to Support Field-scale Research

Precision agriculture adoption on farms continues to grow globally on farms.  Today, yield monitors have become standard technologies on grain, cotton and sugarcane harvesters.  In recent years, we have seen industry and even academics leveraging the adoption of precision agriculture technologies to conduct field-scale, on-farm research.  Industry has been a primary driver of the increase in on-farm research globally through the development of software to support on-farm research. ... J.P. Fulton, S.A. Shearer, A. Gauci, A. Lindsey, D. Barker, E. Hawkins

4. Nitrogen Placement Considerations for Maize Production in the Eastern US Cornbelt

Proper fertilizer placement is essential to optimize crop performance and amount of applied nitrogen (N) along with crop yield potential. There exists several practices currently used in both research within farming operations on how and when to apply N to maize (Zea mays L). Split applications of N in Ohio is popular with farmers and provides an economic benefit but more recently some farmers have been using mid- and late-season N fertilizer applications for their maize production. ... J.P. Fulton, E. Hawkins, S. Shearer, A. Klopfenstein, J. Hartschuh, S. Custer

5. Dynamic Management Zones for Real-time Precision Agriculture Optimization

Precision agriculture is an evolving management approach aimed at optimizing resource utilization, enhancing financial returns, and mitigating environmental impacts. The dynamic nature of agricultural conditions throughout a growing season necessitates the integration of innovative remote sensing and precision agriculture techniques. This research explores the creation of dynamic management zones (DMZ) that adapt in real-time to evolving soil and crop conditions. This study focuses on the establishment... A.H. Rabia, E. Eldeeb

6. Modelling Hydrological Processes in a Wadi Basin in Egypt: Wadi Kharouba Case Study

Wadi Flash Flood (WFF) is one of the most crucial problems facing the north‐western coastal region in Egypt. Water harvesting (WH) approaches may be an effective tool to reduce the WFF risk while storing the runoff water for agricultural activities. In this study, the Agarma sub-catchment of the Wadi Kharouba was taken as a reference investigation site to study terraced WA systems. The main problem in this area is that local farmers independently build terraces using traditional knowledge to... A.H. Rabia, E. Eldeeb, A. Coppola

7. Creating Value from On-farm Research: Efields Data Workflow and Management Successes and Challenges

Farm operations today generate a large amount of data that can be difficult to properly manage. This challenge is further compounded when conducting on-farm research. The Ohio State University eFields program partners with farmers to conduct on-farm research and share results in a timely manner. Since 2017, the team has conducted and shared 987 trials across Ohio with the annual number of trials increasing from 45 to 292. This rapid increase has required development of a data workflow that streamlines... J.P. Fulton, D. Wilson, R. Tietje, E. Hawkins

8. Utilizing Thermal and RGB Imaging for Nutrient Deficiency and Chlorophyll Status Evaluation in Plants

As global population growth and climate change continue to challenge food security, addressing agricultural issues efficiently and cost-effectively is vital for enhancing productivity. Integrating technology into agriculture, particularly through timely interventions, offers promising solutions to mitigate challenges before they escalate. This study investigates the feasibility of using thermal and RGB imaging as efficient, non-destructive methods to assess nutrient deficiencies and chlorophyll... A.H. Rabia, D.G. Allam, E.F. Abdelaty, E.A. Abderaouf

9. Potato Disease Detection Using Laser Speckle Imaging and Deep Learning

Early detection of potato diseases is essential for minimizing crop loss. Implementing advanced imaging techniques can significantly improve the accuracy and efficiency of disease detection in potato crops. Leveraging machine learning algorithms can further enhance the speed and precision of disease identification, enabling timely intervention measures. This work presents a novel potato disease detection technique using whole-potato speckle imaging and deep learning. Laser Speckle Imaging (LSI),... A.H. Rabia, M.A. Salem

10. Development of a High-throughput UAV System for Precision Weed Detection and Control Using Laser Speckle Imaging and UV-C Irradiation

Traditional weed control methods, predominantly reliant on herbicides or labor-intensive ground robots, present notable environmental and efficiency challenges within agricultural practices. To address these concerns, this study introduces an innovative approach utilizing unmanned aerial vehicles (UAVs) for autonomous weed detection and control in agricultural fields. Our proposed system depends on the agility of UAV platforms, integrating two primary technologies. Firstly, Laser Speckle Imaging... M.A. Salem, A.H. Rabia