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Camberato, J.J
Chen, J
Clay, D.E
Crawford, M
Chung, K
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Authors
Chou, T
Yeh, M
Chen, J
Basso, B
Clay, D.E
Clay, S.A
Reicks, G
Horvath, D
Tumenjargal, E
Batbayar, E
Munkhbayar, S
Tsogt-Ochir, S
Oyumaa, M
Chung, K
Ham, W
Bean, G.M
Kitchen, N.R
Camberato, J.J
Ferguson, R.B
Fernandez, F.G
Franzen, D.W
Laboski, C.A
Nafziger, E.D
Sawyer, J.E
Scharf, P.C
Jha, S
Krogmeier, J
Buckmaster, D
Love, D.J
Grant, R.H
Crawford, M
Brinton, C
Wang, C
Cappelleri, D
Balmos, A
Topics
Modeling and Geo-statistics
Spatial and Temporal Variability in Crop, Soil and Natural Resources
Robotics, Guidance and Automation
In-Season Nitrogen Management
Big Data, Data Mining and Deep Learning
Type
Poster
Oral
Year
2012
2008
2018
2024
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Filter results5 paper(s) found.

1. I-SALUS: New Web Based Spatial Systems for Simulating Crop Yield and Environmental Impact

  SALUS (System Approach to Land Use Sustainability) model is designed to simulate the impact of agronomic management on yield and environmental impact. SALUS model has new approaches and algorithms for simulating soil carbon, nitrogen, phosphorous, tillage, soil water balance and yield components. In the past, the use of the crop model was not easy for general... T. Chou, M. Yeh, J. Chen, B. Basso

2. Plant and N Impacts on Corn (Zea Mays) Growth: Whats Controlling Yield?

Studies were conducted in South Dakota to assess mechanisms of intraspecific competition between corn (Zea mays) plants. Treatments were two plant populations (74,500 and 149,000 plants ha-1), three levels of shade (0, 40, and 60%) on the low plant population, two water treatments (natural precipitation and natural + irrigation), and two N rates (0 and 228 kg N ha-1). In-season leaf chlorophyll content was measured. At harvest, grain and stover yields were quantified with grain 13C-discrimination... D.E. Clay, S.A. Clay, G. Reicks, D. Horvath

3. Design and Analysis of ISO 11783 Task Controller's Functionality in Server - Client ECU for Agricultural Vehicles

A modern agricultural vehicle's electronic control units (ECU) communicated based on the ISO 11783 standards. The connection of different machines, implements, different manufacturers into a single bus for the exchange of control commands and sensor data are a challenge for the precision agriculture. One of main functionality is the Task controller in the intelligent monitoring system. The task controller is to log data and assign set-point values for automated work (task) sequences... E. Tumenjargal, E. Batbayar, S. Munkhbayar, S. Tsogt-ochir, M. Oyumaa, K. Chung, W. Ham

4. Corn Nitrogen Fertilizer Recommendation Models Based on Soil Hydrologic Groups Aid in Predicting Economically Optimal Nitrogen Rates

Nitrogen (N) fertilizer recommendations that match corn (Zea mays L.) N needs maximize grower profits and minimize water quality consequences. However, spatial and temporal variability makes determining future N requirements difficult. Studies have shown no single soil or weather measurement is consistently increases accuracy, especially when applied over a regional scale, in predicting economically optimal N rate (EONR). Basing site N response on soil hydrological group could help account for... G.M. Bean, N.R. Kitchen, J.J. Camberato, R.B. Ferguson, F.G. Fernandez, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J.E. Sawyer, P.C. Scharf

5. Design of an Autonomous Ag Platform Capable of Field Scale Data Collection in Support of Artificial Intelligence

The Pivot+ Array is intended to serve as an innovative, multi-user research platform dedicated to the autonomous monitoring, analysis, and manipulation of crops and inputs at the plant scale, covering extensive areas. It will effectively address many constraints that have historically limited large-scale agricultural sensor and robotic research. This achievement will be made possible by augmenting the well-established center pivot technology, known for its autonomy, with robust power infrastructure,... S. Jha, J. Krogmeier, D. Buckmaster, D.J. Love, R.H. Grant, M. Crawford, C. Brinton, C. Wang, D. Cappelleri, A. Balmos