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

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Soufizadeh, S., Munaro, E., McLean, G., Massignam, A., van Oosterom, E. J., Chapman, S. C., Messina, C., Cooper, M. and Hammer, G. L. (2018) Modelling the nitrogen dynamics of maize crops – Enhancing the APSIM maize model. European Journal of Agronomy, 100 . pp. 118-131. ISSN 1161-0301

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Article Link: 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
Live Archive:16 Jan 2018 00:40
Last Modified:03 Sep 2021 16:44

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