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GIS-Based Spatial Nitrogen Management Model for Maize

Published online by Cambridge University Press:  01 June 2017

E. Memic ,
S. Graeff ,
W. Claupein  and
W.D. Batchelor
E. Memic*
Affiliation:
University of Hohenheim, Stuttgart, Germany
S. Graeff
Affiliation:
University of Hohenheim, Stuttgart, Germany
W. Claupein
Affiliation:
University of Hohenheim, Stuttgart, Germany
W.D. Batchelor
Affiliation:
Biosystems Engineering Department, Auburn University, Auburn, AL 36849. USA
*
†Email: [email protected] or [email protected]
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Abstract

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.

Keywords

CERES-MaizeDSSAT crop growth modelnitrogen management
Type
Precision Nitrogen
Information
Advances in Animal Biosciences , Volume 8 , Special Issue 2: Papers presented at the 11th European Conference on Precision Agriculture (ECPA 2017), John McIntyre Centre, Edinburgh, UK, July 16–20 2017 , July 2017 , pp. 312 - 316
Copyright
© The Animal Consortium 2017 

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