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Lacerda, L.N
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Authors
Mizuta, K
Miao, Y
Morales, A.C
Lacerda, L.N
Cammarano, D
Nielsen, R.L
Gunzenhauser, R
Kuehner, K
Wakahara, S
Coulter, J.A
Mulla, D.J
Quinn, D.
McArtor, B
Lacerda, L.N
Miao, Y
Mizuta, K
Stueve, K
Topics
In-Season Nitrogen Management
Big Data, Data Mining and Deep Learning
Type
Oral
Year
2022
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1. Evaluating a Satellite Remote Sensing and Calibration Strip-based Precision Nitrogen Management Strategy for Corn in Minnesota and Indiana

Precision nitrogen (N) management (PNM) aims to match N supply with crop N demand in both space and time and has the potential to improve N use efficiency (NUE), increase farmer profitability, and reduce N losses and negative environmental impacts. However, current PNM adoption rate is still quite low. A remote sensing and calibration strip-based PNM strategy (RS-CS-PNM) has been developed by the Precision Agriculture Center at the University of Minnesota.... K. Mizuta, Y. Miao, A.C. Morales, L.N. Lacerda, D. Cammarano, R.L. Nielsen, R. Gunzenhauser, K. Kuehner, S. Wakahara, J.A. Coulter, D.J. Mulla, D. . Quinn, B. Mcartor

2. Identifying Key Factors Influencing Yield Spatial Pattern and Temporal Stability for Management Zone Delineation

Management zone delineation is a practical strategy for site-specific management. Numerous approaches have been used to identify these homogenous areas in the field, including approaches using multiple years of historical yield maps. However, there are still knowledge gaps in identifying variables influencing spatial and temporal variability of crop yield that should be used for management zone delineation. The objective of this study is to identify key soil and landscape properties affecting... L.N. Lacerda, Y. Miao, K. Mizuta, K. Stueve