Modelling forage yield and water productivity of continuous crop sequences in the Argentinian Pampas
Article
Article Title | Modelling forage yield and water productivity of continuous crop sequences in the Argentinian Pampas |
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ERA Journal ID | 5307 |
Article Category | Article |
Authors | Ojeda, J. J. (Author), Pembleton, K. G. (Author), Caviglia, O. P. (Author), Islam, M. R. (Author), Agnusdei, M. G. (Author) and Garcia, S. C. (Author) |
Journal Title | European Journal of Agronomy |
Journal Citation | 92, pp. 84-96 |
Number of Pages | 13 |
Year | 2018 |
Publisher | Elsevier |
Place of Publication | Netherlands |
ISSN | 1161-0301 |
1873-7331 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.eja.2017.10.004 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S1161030117301508 |
Abstract | In recent years, the use of forage crop sequences (FCS) has been increased as a main component into the animal rations of the Argentinian pasture-based livestock systems. However, it is unclear how year-by-year rainfall variability and interactions with soil properties affect FCS dry matter (DM) yield in these environments. Biophysical crop models, such as Agricultural Production Systems Simulator (APSIM), are tools that enable the evaluation of crop yield variability across a wide of environments. The objective of this study was to evaluate the APSIM ability to predict forage DM yield and water productivity (WP) of multiple continuous FCS. Thirteen continuous FCS, including winter and summer crops, were simulated by APSIM during two/three growing seasons in five locations across the Argentinian Pampas. Our modelling approach was based on the simulation of multiple continuous FCS, in which crop DM yields depend on the performance of the previous crop in the same sequence and the final soil variables of the previous crop are the initial conditions for the next crop. Overall, APSIM was able to accurately simulate FCS DM yield (0.93 and 3.2 Mg ha−1 for concordance correlation coefficient [CCC] and root mean square error [RMSE] respectively). On the other hand, the model predictions were better for annual (CCC = 0.94; RMSE = 0.4 g m−2 mm−1) than for seasonal WP (CCC = 0.71; RMSE = 1.9 g m−2 mm−1), i.e. at the crop level. The model performance to predict WP was associated with better estimations of the soil water dynamics over the long-term, i.e. at the FCS level, rather than the short-term, i.e. at the crop level. The ability of APSIM to predict WP decreased as seasonal WP values increased, i.e. for low water inputs. For seasonal water inputs, <200 mm, the model tended to under-predict WP, which was directly associated with crop DM yield under-predictions for frequently harvested crops. Even though APSIM showed some weaknesses in predicting seasonal DM yield and WP, i.e. at the crop level, it appears as a potential tool for further research on complementary forage crops based on multiple continuous FCS in the Argentinian livestock systems. |
Keywords | APSIM; forages; livestock systems; model validation; maize |
ANZSRC Field of Research 2020 | 300205. Agricultural production systems simulation |
300207. Agricultural systems analysis and modelling | |
300403. Agronomy | |
Public Notes | File reproduced in accordance with the copyright policy of the publisher/author. |
Byline Affiliations | National Scientific and Technical Research Council, Argentina |
School of Agricultural, Computational and Environmental Sciences | |
National Research Council, Argentina | |
University of Sydney | |
National Agricultural Technology Institute (INTA), Argentina | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q47y6/modelling-forage-yield-and-water-productivity-of-continuous-crop-sequences-in-the-argentinian-pampas
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