Description of Crop Growth and Development Framework in APSIM Crop Models
This document provides a verbal description and diagrammatic overview of the algorithms underpinning simulation of the crop growth and development dynamics in APSIM using the sorghum crop model as an exemplar (for further detail see Hammer et al., 2019). A description of the wheat model is also available in Brown et al. (2018). All references in the attached document can be found in Hammer et al., 2019.
There are many other crop modules in APSIM that are now being developed in, or re-coded into, the Plant Modelling Framework (PMF) (Brown et al., 2014) for APSIM NextGen. The general framework in these crop models as exemplified in the attached document incorporates approaches to predicting crop phenology, canopy development, resource (light, water, N) capture and use efficiency, and arbitration rules for assimilate and N allocation and redistribution among organs. The approaches utilise daily weather data and detailed soil characterisation to simulate the soil-plant-atmosphere continuum at a daily time step and generate predictions of crop stage, leaf area, biomass and yield along with the dynamics of soil water and N content. Given the modularity of this framework, more detailed options for specific processes have also been developed and interfaced into this general framework for specific purposes (eg grain set and abortion – Messina et al (2019); leaf and canopy photosynthesis – Wu et al., (2019)).
References
Brown HE, Huth N, Holzworth D. 2018. Crop model improvement in APSIM: using wheat as a case study. European Journal of Agronomy 100:141–150. https://doi.org/10.1016/j.eja.2018.02.002
Brown HE, Huth NI, Holzworth DP, Teixeira EI, Zyskowski RF, Hargreaves JNG, Moot DJ. 2014. Plant modelling framework: software for building and running crop models on the APSIM platform. Environmental Modelling & Software 62:385–398. http://dx.doi.org/10.1016/j.envsoft.2014.09.005
Hammer G, McLean G, Doherty A, van Oosterom E, Chapman S. 2019. Sorghum crop modelling and its utility in agronomy and breeding. In: Prasad V, Ciampitti I, eds. Sorghum: state of the art and future perspectives. Madison, WI: ASA and CSSA. Agronomy Monographs 58, 215-239. https://doi.org/10.2134/agronmonogr58.c10
Messina CD, Hammer GL, McLean G, Cooper M, van Oosterom EJ, Tardieu F, Chapman SC, Doherty A, Gho C. 2019. On the dynamic determinants of reproductive failure under drought in maize. In Silico Plants 2019: diz003; https://doi.org/10.1093/insilicoplants/diz003
Wu A, Hammer GL, Doherty A, von Caemmerer S, Farquhar GD. 2019. Quantifying impacts of enhancing photosynthesis on crop yield. Nature Plants 5:380–388. https://doi.org/10.1038/s41477-019-0398-8