Increasing nitrogen (N) use efficiency could be possible by better in-season N fertilization management. The goal of this study was to test and develop a methodology for combining normalized difference vegetation index data and simulation modeling to assess spatial variability of corn N stress and in-season N rate. Using 2008-2009 data from five corn fields located in north Italy, spatial modeling calibration and simulation were conducted in the CERES-Maize model in DSSAT using the interface with the Geospatial Simulation (GeoSim) tool in the Quantum GIS software. Spatial simulation of yield variability and N stress were possible.
Combining crop sensing and simulation modeling to assess within-field corn nitrogen stress
ZANELLA, VALENTINA;MORARI, FRANCESCO;MOSCA, GIULIANO;
2015
Abstract
Increasing nitrogen (N) use efficiency could be possible by better in-season N fertilization management. The goal of this study was to test and develop a methodology for combining normalized difference vegetation index data and simulation modeling to assess spatial variability of corn N stress and in-season N rate. Using 2008-2009 data from five corn fields located in north Italy, spatial modeling calibration and simulation were conducted in the CERES-Maize model in DSSAT using the interface with the Geospatial Simulation (GeoSim) tool in the Quantum GIS software. Spatial simulation of yield variability and N stress were possible.
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PRECISION Agriculture Israel 2015.pdf
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Descrizione: Increasing nitrogen (N) use efficiency could be possible by better in-season N fertilization management. The goal of this study was to test and develop a methodology for combining normalized difference vegetation index data and simulation modeling to assess spatial variability of corn N stress and in-season N rate. Using 2008-2009 data from five corn fields located in north Italy, spatial modeling calibration and simulation were conducted in the CERES-Maize model in DSSAT using the interface with the Geospatial Simulation (GeoSim) tool in the Quantum GIS software. Spatial simulation of yield variability and N stress were possible.
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