A forage brassica simulation model using APSIM: Model calibration and validation across multiple environments
Article
Article Title | A forage brassica simulation model using APSIM: Model calibration and validation across multiple environments |
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ERA Journal ID | 5307 |
Article Category | Article |
Authors | Watt, Lucinda J. (Author), Bell, Lindsay W. (Author) and Pembleton, Keith G. (Author) |
Journal Title | European Journal of Agronomy |
Journal Citation | 137, pp. 1-14 |
Article Number | 126517 |
Number of Pages | 14 |
Year | 2022 |
Publisher | Elsevier |
Place of Publication | Netherlands |
ISSN | 1161-0301 |
1873-7331 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.eja.2022.126517 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S116103012200065X |
Abstract | Forage brassicas have historically been used in high rainfall/irrigated temperate livestock systems, but there is increasing interest in diverse forage brassicas in drier mixed crop-livestock farming systems. Computer-based modelling is an important decision support tool used in agriculture to explore the adaptability of crops to different climates and agronomic management practices, but existing modelling tools for forage brassicas are limited to temperate environments. We parameterised the APSIM (Agricultural Production Systems Simulator) model for four forage brassica genotypes, including three diverse forage rape cultivars and a raphanobrassica. The model was calibrated using two experiments with repeated measures of biomass components, nutritive value, and leaf and canopy development. We then tested the model extensively using data from a diverse set of environments within Australian and New Zealand (23 sites across four agro-climatic zones). Model predictions of biomass were good for all the genotypes (NSE > 0.60, Nash-Sutcliffe efficiency; RMSE ~1.5 t DM/ha, root mean square error). Predictions of metabolisable energy yield were satisfactory for all genotypes (NSE 0.43–0.73; RMSE ~17.8 GJ ME/ha) but forage dry matter digestibility (DMD) were poorly predicted due to the small variation in observed data. Our robust and widely tested model can be confidently used to predict forage productivity of common and new forage brassicas across a wide range of production environments and agronomic management practices. This model will enable future work to develop a better understanding of the potential value of these important forage crops for livestock production systems. |
Keywords | Canola; Forage productivity; Forage rape; Mixed farming systems; Raphanobrassica |
ANZSRC Field of Research 2020 | 300205. Agricultural production systems simulation |
300403. Agronomy | |
Byline Affiliations | Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia |
Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia | |
School of Sciences | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q77zw/a-forage-brassica-simulation-model-using-apsim-model-calibration-and-validation-across-multiple-environments
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