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Dong, R
Nelson, K.J
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Authors
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
Danford, D.D
Nelson, K.J
Rhea, S.T
Stelford, M.W
Ferreyra, R
Wilson, J.A
Craker, B.E
Dong, R
Miao, Y
Wang, X
Topics
Decision Support Systems
In-Season Nitrogen Management
Big Data, Data Mining and Deep Learning
In-Season Nitrogen Management
Type
Oral
Year
2018
2022
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1. 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

2. 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

3. ADAPT: A Rosetta Stone for Agricultural Data

Modern farming requires increasing amounts of data exchange among hardware and software systems. Precision agriculture technologies were meant to enable growers to have information at their fingertips to keep accurate farm records (and calculate production costs), improve decision-making and promote effi­cien­cies in crop management, enable greater traceability, and so forth. The attainment of these goals has been limited by the plethora of proprietary, incompatible data formats among... D.D. Danford, K.J. Nelson, S.T. Rhea, M.W. Stelford, R. Ferreyra, J.A. Wilson, B.E. Craker

4. 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