GIS-Based Spatial Nitrogen Management Model for Maize

Publikations-Art

Kongressbeitrag

Autoren

E. Memic, S. Graeff, W. Claupein and W.D. Batchelor

Erscheinungsjahr

2017

Veröffentlicht in

Advances in Animal Biosciences: Precision Agriculture (ECPA)

Herausgeber

© The Animal Consortium 2017

Band/Volume

8/2

DOI

10.1017/S2040470017000309

Seite (von - bis)

312-316

Tagungsname

11th European Conference on Precision Agriculture (ECPA 2017)

Tagungsort

John McIntyre Centre, Edinburgh, UK

Tagungsdatum

16. bis 20.July 2017

Crop growth models including CERES-Maize and CROPGRO-Soybean have been
used in the past to evaluate causes of spatial yield variability and
to evaluate economic consequences of variable rate prescriptions.
However, these modelling techniques have not been widely used because
of an absence of user-friendly software. In this work, a nitrogen
prescription model to simulate the consequences of different nitrogen
prescriptions using the DSSAT crop growth models is developed. The
objective is to describe a site-specific nitrogen prescription and
economic optimizer program developed for computing optimum spatial
nitrogen rates for maize using the CERES-Maize model. The application
of the model is demonstrated on two different fields in Germany and
the US. The program simulated optimum N applications that averaged 42%
(McGarvey field, US) and 39% (Riech field, Germany) lower than the
uniform rates actually applied in the fields. The software is written
in Python and will ultimately be distributed in the public domain as a
plug-in to the QGIS software.