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

By S. Soufizadeh, E. Munaro, Greg McLean, A. Massignam, E. V. van Oosterom, Scott C. Chapman, C. Messina, Mark Cooper, Graeme L. Hammer. European Journal of Agronomy, 2018

76 citations recorded by the source corpus.

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.

Subfields: Agronomy and Crop Science, Plant Science

View Paper: https://www.semanticscholar.org/paper/d2c6eacf1968d42b6f60c8749f2a866909195cac

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In Agronomy and Crop Science

  1. Jerry L. Hatfield
  2. Frank Ewert
  3. Kenneth J. Boote
  4. Sotirios V. Archontoulis
  5. J. Durand

In Plant Science

  1. Sotirios V. Archontoulis
  2. Jerry L. Hatfield
  3. Frank Ewert
  4. Soo-Hyung Kim
  5. Claudio O. Stöckle
  6. Kenneth J. Boote
  7. Dennis Timlin
  8. J. Durand

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