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From ORYZA2000 to ORYZA (v3): An improved simulation model for rice in drought and nitrogen-deficient environments
The worldwide usage of and increasing citations for ORYZA2000 has established it as a robust and reliable ecophysiological model for predicting the growth and yield of rice in an irrigated lowland ecosystem. Because of its focus on irrigated lowlands, its computation ability is limited to the repres...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Science Publishers B.V
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5391805/ https://www.ncbi.nlm.nih.gov/pubmed/28469286 http://dx.doi.org/10.1016/j.agrformet.2017.02.025 |
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author | Li, Tao Angeles, Olivyn Marcaida, Manuel Manalo, Emmali Manalili, Mervin Pogs Radanielson, Ando Mohanty, Samarendu |
author_facet | Li, Tao Angeles, Olivyn Marcaida, Manuel Manalo, Emmali Manalili, Mervin Pogs Radanielson, Ando Mohanty, Samarendu |
author_sort | Li, Tao |
collection | PubMed |
description | The worldwide usage of and increasing citations for ORYZA2000 has established it as a robust and reliable ecophysiological model for predicting the growth and yield of rice in an irrigated lowland ecosystem. Because of its focus on irrigated lowlands, its computation ability is limited to the representation of the effects of the highly dynamic environments of upland, rainfed, and aerobic ecosystems on rice growth and yield. Additional modules and routines to quantify daily variations in soil temperature, carbon, nitrogen, and environmental stresses were then developed and integrated into ORYZA2000 to capture their effects on primary production, assimilate allocation, root growth, and water and nitrogen uptake. The newest version has been renamed “ORYZA version 3 (v3)”. Case studies have shown that the root mean square errors (RMSE) between simulated and measured values for total biomass and yields ranged from 11.2% to 16.6% across experiments in non-drought and drought and/or nitrogen-deficient environments. ORYZA (v3) showed a significant reduction of the RMSE by at least 20%, thereby improving the model’s capability to represent values measured under extreme conditions. It has also been significantly improved in representing the dynamics of soil water and crop leaf nitrogen contents. With an enhanced capability to simulate rice growth and development and predict yield in non-stressed, water-stressed and nitrogen-stressed environments, ORYZA (v3) is a reliable successor of ORYZA2000. |
format | Online Article Text |
id | pubmed-5391805 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Elsevier Science Publishers B.V |
record_format | MEDLINE/PubMed |
spelling | pubmed-53918052017-05-01 From ORYZA2000 to ORYZA (v3): An improved simulation model for rice in drought and nitrogen-deficient environments Li, Tao Angeles, Olivyn Marcaida, Manuel Manalo, Emmali Manalili, Mervin Pogs Radanielson, Ando Mohanty, Samarendu Agric For Meteorol Research Paper The worldwide usage of and increasing citations for ORYZA2000 has established it as a robust and reliable ecophysiological model for predicting the growth and yield of rice in an irrigated lowland ecosystem. Because of its focus on irrigated lowlands, its computation ability is limited to the representation of the effects of the highly dynamic environments of upland, rainfed, and aerobic ecosystems on rice growth and yield. Additional modules and routines to quantify daily variations in soil temperature, carbon, nitrogen, and environmental stresses were then developed and integrated into ORYZA2000 to capture their effects on primary production, assimilate allocation, root growth, and water and nitrogen uptake. The newest version has been renamed “ORYZA version 3 (v3)”. Case studies have shown that the root mean square errors (RMSE) between simulated and measured values for total biomass and yields ranged from 11.2% to 16.6% across experiments in non-drought and drought and/or nitrogen-deficient environments. ORYZA (v3) showed a significant reduction of the RMSE by at least 20%, thereby improving the model’s capability to represent values measured under extreme conditions. It has also been significantly improved in representing the dynamics of soil water and crop leaf nitrogen contents. With an enhanced capability to simulate rice growth and development and predict yield in non-stressed, water-stressed and nitrogen-stressed environments, ORYZA (v3) is a reliable successor of ORYZA2000. Elsevier Science Publishers B.V 2017-05-01 /pmc/articles/PMC5391805/ /pubmed/28469286 http://dx.doi.org/10.1016/j.agrformet.2017.02.025 Text en © 2017 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Paper Li, Tao Angeles, Olivyn Marcaida, Manuel Manalo, Emmali Manalili, Mervin Pogs Radanielson, Ando Mohanty, Samarendu From ORYZA2000 to ORYZA (v3): An improved simulation model for rice in drought and nitrogen-deficient environments |
title | From ORYZA2000 to ORYZA (v3): An improved simulation model for rice in drought and nitrogen-deficient environments |
title_full | From ORYZA2000 to ORYZA (v3): An improved simulation model for rice in drought and nitrogen-deficient environments |
title_fullStr | From ORYZA2000 to ORYZA (v3): An improved simulation model for rice in drought and nitrogen-deficient environments |
title_full_unstemmed | From ORYZA2000 to ORYZA (v3): An improved simulation model for rice in drought and nitrogen-deficient environments |
title_short | From ORYZA2000 to ORYZA (v3): An improved simulation model for rice in drought and nitrogen-deficient environments |
title_sort | from oryza2000 to oryza (v3): an improved simulation model for rice in drought and nitrogen-deficient environments |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5391805/ https://www.ncbi.nlm.nih.gov/pubmed/28469286 http://dx.doi.org/10.1016/j.agrformet.2017.02.025 |
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