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Modelling the nitrogen dynamics of maize crops – Enhancing the APSIM maize model

Soufizadeh, S. and Munaro, E. and McLean, G. and Massignam, A. and van Oosterom, E. J. and Chapman, S. C. and Messina, C. and Cooper, M. and Hammer, G. L. Modelling the nitrogen dynamics of maize crops – Enhancing the APSIM maize model. European Journal of Agronomy . ISSN 1161-0301

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Article Link(s): https://doi.org/10.1016/j.eja.2017.12.007

Publisher URL: https://www.sciencedirect.com/science/article/pii/S1161030117301880

Abstract

Crop growth simulation models require robust ecophysiological functionality to support credible simulation of diverse genotype × management × environment (G × M × E) combinations. Most efforts on modeling the nitrogen (N) dynamics of crops use a minimum, critical, and maximum N concentration per unit biomass based empirically on experimental observations. Here we present a physiologically more robust approach, originally implemented in sorghum, which uses the N content per unit leaf area as a key driver of N demand. The objective was to implement the conceptual framework of the APSIM sorghum nitrogen dynamics model in APSIM maize and to validate the robustness of the model across a range of G × M × E combinations. The N modelling framework is described and its parameterisation for maize is developed based on three previously reported detailed field experiments, conducted at Gatton (27°34′S, 152°20′), Queensland, Australia, supplemented by literature data. There was considerable correspondence with parameterisation results found for sorghum, suggesting potential for generality of this framework for modelling crop N dynamics in cereals. Comprehensive model testing indicated accurate predictions at organ and crop scale across a diverse range of experiments and demonstrated that observed responses to a range of management factors were reproduced credibly. This supports the use of the model to extrapolate and predict performance and adaptation under new G × M × E combinations. Capturing this advance with reduced complexity compared to the N concentration approach provides a firm basis to progress the role of modelling in exploring the genetic underpinning of complex traits and in plant breeding and crop improvement generally.

Item Type:Article
Business groups:Crop and Food Science
Keywords:Maize Nitrogen Modelling Simulation Ecophysiology
Subjects:Science > Statistics > Simulation modelling
Agriculture > Agriculture (General) > Methods and systems of culture. Cropping systems
Agriculture > Agriculture (General) > Fertilisers
Plant culture > Field crops > Corn. Maize
Deposited On:16 Jan 2018 00:40
Last Modified:16 Jan 2018 00:40

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