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Wang, X
Lamb, D.W
Zhang, A
Vigil, M
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Authors
Stanley, J.S
Lamb, D.W
Trotter, M.G
Rahman, M.M
Walthall, C
Hatfield, J
Schneider, S
Vigil, M
Dong, J
Meng, Z
Cong, Y
Zhang, A
Fu, W
Pan, R
Yang, Q
Shang, Y
Wang, X
Miao, Y
Batchelor, W.D
Dong, R
Mulla, D.J
Wang, X
Miao, Y
Xia, T
Dong, R
Mi, G
Mulla, D.J
Dong, R
Miao, Y
Wang, X
Topics
Remote Sensing Applications in Precision Agriculture
Decision Support Systems in Precision Agriculture
Precision Agriculture and Global Food Security
Decision Support Systems
In-Season Nitrogen Management
In-Season Nitrogen Management
Type
Oral
Poster
Year
2014
2016
2018
2022
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Filter results6 paper(s) found.

1. NDVI 'Depression' In Pastures Following Grazing

Pasture biomass estimation from normalized difference vegetation index (NDVI) using ground, air or space borne sensors is becoming more widely used in precision agriculture. Proximal active optical sensors (AOS) have the potential to eliminate the confounding effects of path radiance and target illumination conditions typically encountered using passive sensors. Any algorithm that infers the green fraction of pasture from NDVI must factor in plant morphology and live/dead plant ratio, irrespective... J.S. Stanley, D.W. Lamb, M.G. Trotter, M.M. Rahman

2. Closing Yield Gaps with GxExM and Precision Agriculture

There are many challenges to be faced by agriculture if the global population of nine billion people projected for 2050 is to be fed and clothed, especially given the effects of changing climate.  A focus on the interactions of genetics x environment x management (GxExM) offers potential for meeting the yield, and environment and economic sustainability goals that are integral to these challenges.  The yield gap –defined as the difference between current farmer yields and potential... C. Walthall, J. Hatfield, S. Schneider, M. Vigil

3. An Automatic Control Method Research for 9YG-1.2 Large Round Baler

When manual or semi-automatic round baler working, the tractor driver have to frequently manual the machine according to the bale process at the same time of driving. The driver easily feel fatigue in this operating mode for a long time, so the consistency of the bale’s density can not be guaranteed. And there may be wrong operation. In this article, we use the model 9YG-1.2 large round baler as a research prototype. We study the information collection and processing of the baler’s... J. Dong, Z. Meng, Y. Cong, A. Zhang, W. Fu, R. Pan, Q. Yang, Y. Shang

4. Improving the Precision of Maize Nitrogen Management Using Crop Growth Model in Northeast China

The objective of this project was to evaluate the ability of the CERES-Maize crop growth model to simulate grain yield response to plant density and N rate for two soil types in Northeast China, with the long-term goal of using the model to identify the optimum plant density and N fertilizer rate forspecific site-years. Nitrogen experiments with six N rates, three plant densities and two soil types were conducted from 2015 to 2017 in Lishu county, Jilin Province in Northeast China. The CERES-Maize... X. Wang, Y. Miao, W.D. Batchelor, R. Dong, D.J. Mulla

5. Improving Active Canopy Sensor-Based In-Season N Recommendation Using Plant Height Information for Rain-Fed Maize in Northeast China

The inefficient utilization of nitrogen (N) fertilizer due to leaching, volatilization and denitrification has resulted in environmental pollution in rain-fed maize production in Northeast China. Active canopy sensor-based in-season N application has been proven effective to meet maize N requirement in space and time. The objective of this research was to evaluate the feasibility of using active canopy sensor for guiding in in-season N fertilizer recommendation for rain-fed maize in Northeast... X. Wang, Y. Miao, T. Xia, R. Dong, G. Mi, D.J. Mulla

6. In-season Nitrogen Management of Maize Based on Nitrogen Status and Lodging Risk Prediction

Development of effective precision nitrogen (N) management strategies is crucially important for food security and sustainable development. Lodging is one of the major constraints to increasing maize yield that can be induced by strong winds, and is also influenced by management practices, like N rate. When making in-season N application decisions, lodging risk should be considered to avoid yield loss. Little has been reported on in-season N management strategies that also incorporate lodging... R. Dong, Y. Miao, X. Wang