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Liu, X
Silverman, N
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Authors
Liu, X
Cao, Q
Tian, Y
Zhu, Y
Zhang, Z
Cao, W
Li, S
Cao, Q
Liu, X
Tian, Y
Zhu, Y
Maxwell, B.D
Bekkerman, A
Silverman, N
Payn, R
Sheppard, J
Izurieta, C
Davis, P
Hegedus, P.B
Topics
Applications of Unmanned Aerial Systems
In-Season Nitrogen Management
On Farm Experimentation with Site-Specific Technologies
Type
Poster
Oral
Year
2018
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Filter results3 paper(s) found.

1. Using Unmanned Aerial Vehicle and Active-Optical Sensor to Monitor Growth Indices and Nitrogen Nutrition of Winter Wheat

Using unmanned aerial vehicle (UAV) remote sensing monitoring system can rapidly and cost-effectively provide crop canopy information for growth diagnosis and precision fertilizer regulation. RapidScan CS-45 (Holland, Lincoln, NE, USA) is a portable active-optical sensor designed for timely, non-destructive obtaining plant canopy information without being affected by weather condition. UAV equipped with RapidScan, is of great significant for rapidly monitoring crop growth and nitrogen (N) status.... X. Liu, Q. Cao, Y. Tian, Y. Zhu, Z. Zhang, W. Cao

2. Using a UAV-Based Active Canopy Sensor to Estimate Rice Nitrogen Status

Active canopy sensors have been widely used in the studies of crop nitrogen (N) estimation as its suitability for different environmental conditions. Unmanned aerial vehicle (UAV) is a low-cost remote sensing platform for its great flexibility compared to traditional ways of remote sensing. UAV-based active canopy sensor is expected to take the advantages of both sides. The objective of this study is to determine whether UAV-based active canopy sensor has potential for monitoring rice N status,... S. Li, Q. Cao, X. Liu, Y. Tian, Y. Zhu

3. Can Optimization Associated with On-Farm Experimentation Using Site-Specific Technologies Improve Producer Management Decisions?

Crop production input decisions have become increasingly difficult due to uncertainty in global markets, input costs, commodity prices, and price premiums. We hypothesize that if producers had better knowledge of market prices, spatial variability in crop response, and weather conditions that drive crop response to inputs, they could more cost-effectively make profit-maximizing input decisions. Understanding the drivers of variability in crop response and designing accompanying management strategies... B.D. Maxwell, A. Bekkerman, N. Silverman, R. Payn, J. Sheppard, C. Izurieta, P. Davis, P.B. Hegedus