Improving the estimation and partitioning of plant nitrogen in the RiceGrow model
Plant nitrogen (N) links with many physiological progresses of crop growth and yield formation. Accurate simulation is key to predict crop growth and yield correctly. The aim of the current study was to improve the estimation of N uptake and translocation processes in the whole rice plant as well as...
| Main Authors: | , , , , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Cambridge University Press
2018
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| Online Access: | https://hdl.handle.net/10568/164772 |
| _version_ | 1855518085076746240 |
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| author | Tang, L. Chang, R.J. Basso, B. Li, T. Zhen, F.X. Liu, L.L. Cao, W.X. Zhu, Y. |
| author_browse | Basso, B. Cao, W.X. Chang, R.J. Li, T. Liu, L.L. Tang, L. Zhen, F.X. Zhu, Y. |
| author_facet | Tang, L. Chang, R.J. Basso, B. Li, T. Zhen, F.X. Liu, L.L. Cao, W.X. Zhu, Y. |
| author_sort | Tang, L. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Plant nitrogen (N) links with many physiological progresses of crop growth and yield formation. Accurate simulation is key to predict crop growth and yield correctly. The aim of the current study was to improve the estimation of N uptake and translocation processes in the whole rice plant as well as within plant organs in the RiceGrow model by using plant and organ maximum, critical and minimum N dilution curves. The maximum and critical N (Nc) demand (obtained from the maximum and critical curves) of shoot and root and Nc demand of organs (leaf, stem and panicle) are calculated by N concentration and biomass. Nitrogen distribution among organs is computed differently pre- and post-anthesis. Pre-anthesis distribution is determined by maximum N demand with no priority among organs. In post-anthesis distribution, panicle demands are met first and then the remaining N is allocated to other organs without priority. The amount of plant N uptake depends on plant N demand and N supplied by the soil. Calibration and validation of the established model were performed on field experiments conducted in China and the Philippines with varied N rates and N split applications; results showed that this improved model can simulate the processes of N uptake and translocation well. |
| format | Journal Article |
| id | CGSpace164772 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| publisher | Cambridge University Press |
| publisherStr | Cambridge University Press |
| record_format | dspace |
| spelling | CGSpace1647722025-05-14T10:39:32Z Improving the estimation and partitioning of plant nitrogen in the RiceGrow model Tang, L. Chang, R.J. Basso, B. Li, T. Zhen, F.X. Liu, L.L. Cao, W.X. Zhu, Y. Plant nitrogen (N) links with many physiological progresses of crop growth and yield formation. Accurate simulation is key to predict crop growth and yield correctly. The aim of the current study was to improve the estimation of N uptake and translocation processes in the whole rice plant as well as within plant organs in the RiceGrow model by using plant and organ maximum, critical and minimum N dilution curves. The maximum and critical N (Nc) demand (obtained from the maximum and critical curves) of shoot and root and Nc demand of organs (leaf, stem and panicle) are calculated by N concentration and biomass. Nitrogen distribution among organs is computed differently pre- and post-anthesis. Pre-anthesis distribution is determined by maximum N demand with no priority among organs. In post-anthesis distribution, panicle demands are met first and then the remaining N is allocated to other organs without priority. The amount of plant N uptake depends on plant N demand and N supplied by the soil. Calibration and validation of the established model were performed on field experiments conducted in China and the Philippines with varied N rates and N split applications; results showed that this improved model can simulate the processes of N uptake and translocation well. 2018-10 2024-12-19T12:54:16Z 2024-12-19T12:54:16Z Journal Article https://hdl.handle.net/10568/164772 en Cambridge University Press Tang, L.; Chang, R. J.; Basso, B.; Li, T.; Zhen, F. X.; Liu, L. L.; Cao, W. X. and Zhu, Y. 2018. Improving the estimation and partitioning of plant nitrogen in the RiceGrow model. J. Agric. Sci., Volume 156 no. 8 p. 959-970 |
| spellingShingle | Tang, L. Chang, R.J. Basso, B. Li, T. Zhen, F.X. Liu, L.L. Cao, W.X. Zhu, Y. Improving the estimation and partitioning of plant nitrogen in the RiceGrow model |
| title | Improving the estimation and partitioning of plant nitrogen in the RiceGrow model |
| title_full | Improving the estimation and partitioning of plant nitrogen in the RiceGrow model |
| title_fullStr | Improving the estimation and partitioning of plant nitrogen in the RiceGrow model |
| title_full_unstemmed | Improving the estimation and partitioning of plant nitrogen in the RiceGrow model |
| title_short | Improving the estimation and partitioning of plant nitrogen in the RiceGrow model |
| title_sort | improving the estimation and partitioning of plant nitrogen in the ricegrow model |
| url | https://hdl.handle.net/10568/164772 |
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