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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Radanielson, Ando
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article
Modeling salinity effect on rice growth and rice yield with ORYZA v3 and APSIM-Oryza
Abstract
Development and testing of reliable tools for simulating rice production in salt-affected areas are presented in this paper. New functions were implemented in existing crop models ORYZA v3 (the new version of ORYZA2000) and the cropping systems modeling framework APSIM.Field experiments covering two years, two different sites, and three varieties were used to validate both improved models. The systems model APSIM was able to simulate the observed soil salinity dynamics to an acceptable degree (RMSEn < 35%), whereas ORYZA v3 requires the soil salinity dynamic as a model input.Both models presented similarly good accuracy in simulating aboveground biomass, leaf area index, and grain yield for IR64 over a gradient of salinity conditions. Model index of agreement ranged from 0.86 to 0.99. Variability of yield under stressed and non-stressed conditions was simulated with a RMSE, of 190.75 kg ha-1 and 221.76 kg ha-1, respectively, for ORYZA v3 and APSIM-Oryza, corresponding to an RMSEn % of 14.8% and 17.3%, indicating acceptable model performance. The model test simulating genotypic variability of rice crop responses resulted in similar levels of acceptable model performance with RMSEn ranging from 11.3 to 39.9% for observed total above ground biomass for IR64 and panicle biomass for IR29, respectively. With the improved models, opportunities are now available for greater reliability in risk assessment and evaluation of suitable management options for rice production in salt-affected areas.The methodology we have followed may also suggest a path for improvement of other non-rice crop modelsto integratea response to soil salinity - particularly inprocess-based modelswhich capture stage-relatedstresstolerance variability and resource use efficiency.