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Abdinoor, J.A
Admasu, W.A
Andersson, K
Abbas, A
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Authors
Trotter, M
Andersson, K
Welch, M
Chau, M
Frizzel, L
Schneider, D
Brockgreitens, J
Bui, M
Abbas, A
Mulla, D
Mandal, D
Longchamps, L
Khosla, R
Admasu, W.A
Zsebő, S
Kukorelli, G
Vona, V
Bede, L
Stencinger, D
Kovacs, A
Milics, G
Kulmany, I.M
Horváth, B
Hegedűs, G
Abdinoor, J.A
Joshi, R
Khosla, R
Mandal, D
Unruh, R
Admasu, W.A
Unruh, R
Admasu, W.A
Mandal, D
Joshi, R
Khosla, R
Kulmany, I.M
Horváth, B
Kukorelli, G
Zsebő, S
Stencinger, D
Borbás, Z
Pecze, R
Bede, L
Varga, Z
Kósa, A
Pinke, G
Hashim, Z.K
Hegedűs, G
Abdinoor, J.A
Agampodi, G.S
Admasu, W.A
Mandal, D
Khosla, R
Admasu, W.A
Mandal, D
Khosla, R
Topics
Proximal Sensing in Precision Agriculture
Engineering Technologies and Advances
Artificial Intelligence (AI) in Agriculture
Scouting and Field Data collection with Unmanned Aerial Systems
In-Season Nitrogen Management
Drainage Optimization and Variable Rate Irrigation
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Decision Support Systems
Digital Agriculture Solutions for Soil Health and Water Quality
Type
Oral
Poster
Year
2016
2024
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Filter results9 paper(s) found.

1. Evaluating low-cost Lidar and Active Optical Sensors for pasture and forage biomass assessment

Accurate and reliable assessment of pasture or forage biomass remains one of the key challenges for grazing industries. Livestock managers require accurate estimates of the grassland biomass available over their farm to enable optimal stocking rate decisions. This paper reports on our investigations into the potential application of affordable Lidar (Light Detection and Ranging) systems and Active Optical (reflectance) Sensors (AOS) to estimate pasture biomass. We evaluated the calibration accuracy... M. Trotter, K. Andersson, M. Welch, M. Chau, L. Frizzel, D. Schneider

2. Field Sampling and Electrochemical Detection of Nitrate in Agricultural Soils

Nitrate is an essential plant nutrient and is added to farm fields to increase crop yields. While the addition of nitrate is important for production, over-fertilization with nitrate can lead to leaching and contamination of water bodies. Increased nitrate loading in water sources then leads to eutrophication and hypoxia in downstream regions. Many efforts are being made to accurately control nitrate fertilizer additions to fields. Here, we present a soil sampling device that directly samples... J. Brockgreitens, M. Bui, A. Abbas, D. Mulla

3. Optimal Placement of Soil Moisture Sensors in an Irrigated Corn Field

Precision agricultural practices rely on characterization of spatially and temporally variable soil and crop properties to precisely synchronize inputs (water, fertilizer, etc.) to crop needs; thereby enhancing input use efficiency and farm profitability. Generally, the spatial dependency range for soil water content is shorter near the soil surface compared to deeper depths, suggesting a need for more sampling locations to accurately characterize near-surface soil water content. However, determining... D. Mandal, L. Longchamps, R. Khosla

4. Comparison of NDVI Values at Different Phenological Stages of Winter Wheat (Triticum Aestivum L.)

The main objective of this study is to monitor, detect and quantify the presence of live green vegetation with the MicaSense RedEdge-MX Dual Camera System (MS) mounted on a DJI Matrice 210 V2 and GreenSeeker HCS 250 (GS) in winter wheat (Triticum aestivum L.) by using Normalized Difference Vegetation Index (NDVI). Surveys were conducted in the North-Western part of Hungary, in Mosonmagyaróvár on six different dates. A small-scale field trial in winter wheat was constructed as a randomized... S. Zsebő, G. Kukorelli, V. Vona, L. Bede, D. Stencinger, A. Kovacs, G. Milics, I.M. Kulmany, B. Horváth, G. Hegedűs, J.A. Abdinoor

5. Delineation of Site-Specific Management Zones using Sensor-based Data for Precision N management

Nitrogen is a critical nutrient influencing crop yield, but the common practice of uniform application of nitrogen fertilizer across a field often results in spatially variable nitrogen availability for the crop, leading to over-application in some areas and under-application in others. This imbalance can cause economic losses and significant environmental issues. Precision nitrogen application involves application of N fertilizers based on soil conditions and crop requirements. One approach for... R. Joshi, R. Khosla, D. Mandal, R. Unruh, W.A. Admasu

6. Delineating Dynamic Variable Rate Irrigation Management Zones

Agriculture irrigation strategies have traditionally been made without accounting for the natural small-scale variability in the field, leading to uniform applications that often over-irrigate parts of the field that do not need as much water. The future success of irrigated agriculture depends on advancements in the capability to account for and leverage the natural variability in croplands for optimum irrigation management both in space and time. Variable Rate Irrigation (VRI) management offers... R. Unruh, W.A. Yilma, D. Mandal, R. Joshi, R. Khosla

7. Evaluation of the Effect of Different Herbicide Treatments by Using UAV in Maise (Zea mays L.) Cultivation – First Experiences in a Long-term Experiment at Széchenyi István University, Hungary

As part of the Green Deal, the European Union has set a goal to reduce the use of chemical pesticides by 50 percent until 2030. To achieve this goal, in addition to reducing the amount of pesticide used, attention must also be paid to monitoring the temporal and spatial effects of pesticides on weeds during the cultivation of various crops. Hence, Syngenta Ltd., collaborating with researchers, aimed to monitor the effect of five different types of herbicides by UAV in two tillage treatments (CN... I.M. Kulmany, B. Horváth, G. Kukorelli, S. Zsebő, D. Stencinger, Z. Borbás, R. Pecze, L. Bede, Z. Varga, A. Kósa, G. Pinke, Z.K. Hashim, G. Hegedűs, J.A. Abdinoor, G.S. Agampodi

8. Coupling Macro-scale Variability in Soil and Micro-scale Variability in Crop Canopy for Delineation of Site-specific Management Grid

The efficient application of fertilizers via Site-Specific Management Units (SSMUs) or Management Zones (MZs) can significantly enhance crop productivity and nitrogen use efficiency. Conventional mathematical and data-driven clustering methods for MZ delineation, while prevalent, often lack precision in identifying productivity zones. This research introduces a knowledge-driven productivity zone to mitigate these limitations, offering a more precise and efficacious approach. The hypothesis... W.A. Admasu, D. Mandal, R. Khosla

9. Hyperspectral Sensing to Estimate Soil Nitrogen and Reduce Soil Sampling Intensity

Recognizing soil's critical role in agriculture, swift and accurate quantification of soil components, specifically nitrogen, becomes paramount for effective field management. Traditional laboratory methods are time-consuming, prone to errors, and require hazardous chemicals. Consequently, this research advocates the use of non-imaging hyperspectral data and VIS-NIR spectroscopy as a safer, quicker, and more efficient alternative. These methods take into account various soil components, including... W.A. Admasu, D. Mandal, R. Khosla