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Casey, F
Clarke, S
Aijun, Z
An, X
Castro, S.G
Camberato, J.J
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Authors
Meng, Z
Wang, Z
Wu, G
Fu, W
An, X
Castro, S.G
Kolln, O.T
Nakao, H.S
Franco, H.C
Braunbeck, O
Graziano Magalhães, P.S
Sanches, G.M
Xiongkui, H
Longlong, L
Jianli, S
Aijun, Z
Yajia, L
Franzen, D.W
Casey, F
Staricka, J
Long, D
Lamb, J
Sims, A
Halvorson, M
Hofman, V
Kindred, D
Sylvester-Bradley, R
Clarke, S
Roques, S
Hatley, D
Marchant, B
Li, D
Miao, Y
Fernández, .G
Kitchen, N.R
Ransom, C.
Bean, G.M
Sawyer, .E
Camberato, J.J
Carter, .R
Ferguson, R.B
Franzen, D.W
Franzen, D.W
Franzen, D.W
Franzen, D.W
Laboski, C.A
Nafziger, E.D
Shanahan, J.F
Topics
Spatial Variability in Crop, Soil and Natural Resources
Precision Nutrient Management
Engineering Technologies and Advances
Spatial and Temporal Variability in Crop, Soil and Natural Resources
On Farm Experimentation with Site-Specific Technologies
ISPA Community: Nitrogen
Type
Poster
Oral
Year
2014
2016
2008
2018
2022
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Filter results6 paper(s) found.

1. The Spatial And Temporal Variability Analysis Of Wheat Yield in suburban of Beijing

  Abstract: The yield map is the basis of the fertilization maps and plant maps. In order to diagnose the cause of variation accurately, not only the spatial variation of annual yield data, but also the successive annual yield data of temporal variability should be understood.The introduction of yield monitor system, global positioning system (GPS), and geographic information system have provided new methods to obtain wheat yield in precision agriculture.... Z. Meng, Z. Wang, G. Wu, W. Fu, X. An

2. The Most Sensitive Growth Stage To Quantify Nitrogen Stress In Sugarcane Using Active Crop Canopy Sensor

The use of sensors that allow the application of nitrogen fertilizer at variable rate has been widely used by researchers in many agricultural crops, but without success in sugarcane, probably due to the difficulty of diagnosing the nutritional status of the crop for nitrogen (N). Active crop canopy sensors are based on the principle that the spectral reflectance curve of the leaves are modified by N level. Researchers in USA indicated that in-season N stress in corn can be detected... S.G. Castro, O.T. Kolln, H.S. Nakao, H.C. Franco, O. Braunbeck, P.S. Graziano magalhães, G.M. Sanches

3. Design of VAV System of Air Assisted Sprayer in Orchard and Experimental Study in China

One type of new automatic target detecting based on size of canopy with variable chemical dosage and air-flow of fan orchard sprayer was designed and developed to meet the demand of chemical pest control in orchards. Canopy parameter data scanned by infrared sensors and LIDAR (Light Detection and Ranging) were used to detect the target and to design spraying algorithm and PWM (Pulse Width Modulation) control system. Four integrated five-finger atomizers were equipped on each side of sprayer, independent... H. Xiongkui, L. Longlong, S. Jianli, Z. Aijun, L. Yajia

4. Regional Usefulness of Nitrogen Management Zone Delineation Tools

In the Northern Plains of Montana, North Dakota and Minnesota, a number of site-specific tools have been used to delineate nitrogen management zones. A three-year study was conducted using yield mapping, elevation measurements, satellite imagery, aerial Ektochrome® photography, and soil EC to delineate nitrogen management zones and compare these zones to residual fall soil nitrate. At most of the sites, variable-rate N was applied and compared with uniform N application. The site-specific... D. Franzen, F. Casey, J. Staricka, D. Long, J. Lamb, A. Sims, M. Halvorson, V. Hofman

5. Supporting and Analysing On-Farm Nitrogen Tramline Trials So Farmers, Industry, Agronomists and Scientists Can LearN Together

Nitrogen fertilizer decisions are considered important for the agronomic, economic and environmental performance of cereal crop production. Despite good recommendation systems large unpredicted variation exists in measured N requirements. There may be fields and farms that are consistently receiving too much or too little N fertilizer, therefore losing substantial profit from wasted fertilizer or lost yield. Precision farming technologies can enable farmers (& researchers) to test appropriate... D. Kindred, R. Sylvester-bradley, S. Clarke, S. Roques, D. Hatley, B. Marchant

6. Developing a Machine Learning and Proximal Sensing-based In-season Site-specific Nitrogen Management Strategy for Corn in the US Midwest

Effective in-season site-specific nitrogen (N) management strategies are urgently needed to ensure both food security and sustainable agricultural development. Different active canopy sensor-based precision N management strategies have been developed and evaluated in different parts of the world. Recent studies evaluating several sensor-based N recommendation algorithms across the US Midwest indicated that these locally developed algorithms generally did not perform well when used broadly across... D. Li, Y. Miao, .G. Fernández, N.R. Kitchen, C. . Ransom, G.M. Bean, .E. Sawyer, J.J. Camberato, .R. Carter, R.B. Ferguson, D.W. Franzen, D.W. Franzen, D.W. Franzen, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J.F. Shanahan