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| Filter results6 paper(s) found. |
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1. Disease Scouting For Aerial Blight Based On Logical Areas Of Collection In Soybean Fields Rotated With RiceRhizoctonia solani AG1-IA causes sheath blight in rice and aerial blight in soybean. In Arkansas, rice and soybean rotations facilitate a continuous source of R. solani AG1-IA inoculum from one year to the next. Aerial blight is a two stage disease where colonization of the plant occurs during the early vegetative growth stages and aerial blight symptoms occur during the reproductive growth stages after canopy closure. At canopy closure,... C.S. Rothrock, W.S. Monfort, T.W. Griffin, T.N. Spurlock |
2. Deep Learning-Based Corn Disease Tracking Using RTK Geolocated UAS ImageryDeep learning-based solutions for precision agriculture have achieved promising results in recent times. Deep learning has been used to accurately classify different disease types and disease severity estimation as an initial stage for developing robust disease management systems. However, tracking the spread of diseases, identifying disease hot spots within cornfields, and notifying farmers using deep learning and UAS imagery remains a critical research gap. Therefore, in this study, high resolution,... A. Ahmad, V. Aggarwal, D. Saraswat, A. El gamal, G. Johal |
3. Enhancing Nutrient-related Stress Detection: High Throughput Phenotyping and Image Analysis for Improved PrecisionIn the 21-century agriculture has the unique responsibility to provide food, fuel, fiber and feed for the growing population under the stress of climate change and diminishing natural resources. A feat that will take considerable change to the sustainability of such practices. One of which is the idea of assessing phenotypic expression of complex traits in response to environmental factors. This idea elevates the use of phenotyping to quantitatively monitor stress manifestation. Therefore,... K.J. Bathke, Y. Ge, S.D. Choudhury, J.D. Luck |
4. Fertigation Management Strategies Effect on Residual Nitrates in the Soil Profile and Ground WaterNitrogen is an input that is vital for growth and productivity within the corn belt states of the U.S. However, when nitrogen as an input into agricultural cropping systems is often over-applied and thus not optimally utilized by the cropping system. Therefore, it is at risk of loss within the environment through processes of leaching, denitrification, and volatilization. This is a major concern in Nebraska, as the reality is that much of the state’s groundwater has been contaminated with... K.J. Bathke, T. Cross, J.D. Luck |
5. Sensor Based Fertigation ManagementSensor-based fertigation management (SBFM) is a relatively new technology for directing nitrogen (N) decisions, specifically tailored for delivery of N via center pivot irrigation systems (fertigation). The development of SBFM began in 2018 at the University of Nebraska-Lincoln with the help of cooperating producers across the state. Over two dozen field sites provided testbeds for the development and evaluation of the technology. The key technique in this fertigation approach is the... J. Stansell, J.D. Luck, T. Cross, K.J. Bathke, T. Smith |
6. In-Season Nitrogen Management: Leveraging Data Visualization for Precision AgricultureThe agricultural sector nitrogen management-related research has been extensively high by experiencing a data revolution, with an increasing influx of information from diverse sources like sensors, satellites, and Unmanned Aerial Vehicles (UAVs) imaging technologies. In this context, effective in-season nitrogen data management has become a critical factor; however, the ability of farmers to visualize the impact of such technologies in field research settings has been limited. This project... C. Narayana, S. vanderplas, K.J. Bathke, J.D. Luck |