Importance of genetic parameters and uncertainty of MANIHOT, a new mechanistic cassava simulation model
We identified the most sensitive genotype-specific parameters (GSPs) and their contribution to the uncertainty ofthe MANIHOT simulation model. We applied a global sensitivity and uncertainty analysis (GSUA) of the GSPs tothe simulation outputs for the cassava development, growth, and yield in contra...
| Autores principales: | , , , , , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2020
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/107816 |
| _version_ | 1855513893339660288 |
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| author | Moreno Cadena, Leidy Patricia Hoogenboom, Gerrit Fisher, James Myles Ramírez Villegas, Julián Armando Prager, Steven D. Becerra López Lavelle, Luis Augusto Pypers, Pieter Mejia de Tafur, Maria Sara Wallach, Daniel Muñoz Carpena, Rafael Asseng, Senthold |
| author_browse | Asseng, Senthold Becerra López Lavelle, Luis Augusto Fisher, James Myles Hoogenboom, Gerrit Mejia de Tafur, Maria Sara Moreno Cadena, Leidy Patricia Muñoz Carpena, Rafael Prager, Steven D. Pypers, Pieter Ramírez Villegas, Julián Armando Wallach, Daniel |
| author_facet | Moreno Cadena, Leidy Patricia Hoogenboom, Gerrit Fisher, James Myles Ramírez Villegas, Julián Armando Prager, Steven D. Becerra López Lavelle, Luis Augusto Pypers, Pieter Mejia de Tafur, Maria Sara Wallach, Daniel Muñoz Carpena, Rafael Asseng, Senthold |
| author_sort | Moreno Cadena, Leidy Patricia |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | We identified the most sensitive genotype-specific parameters (GSPs) and their contribution to the uncertainty ofthe MANIHOT simulation model. We applied a global sensitivity and uncertainty analysis (GSUA) of the GSPs tothe simulation outputs for the cassava development, growth, and yield in contrasting environments. We com-pared enhanced Sampling for Uniformity, a qualitative screening method new to crop simulation modeling, andSobol, a quantitative, variance-based method. About 80% of the GSPs contributed to most of the variation inmaximum leaf area index (LAI), yield, and aboveground biomass at harvest. Relative importance of the GSPsvaried between warm and cool temperatures but did not differ between rainfed and no water limitation con-ditions. Interactions between GSPs explained 20% of the variance in simulated outputs. Overall, the most im-portant GSPs were individual node weight, radiation use efficiency, and maximum individual leaf area. Basetemperature for leaf development was more important for cool compared to warm temperatures. Parameteruncertainty had a substantial impact on model predictions in MANIHOT simulations, with the uncertainty 2–5times larger for warm compared to cool temperatures. Identification of important GSPs provides an objectiveway to determine the processes of a simulation model that are critical versus those that have little relevance. |
| format | Journal Article |
| id | CGSpace107816 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | CGSpace1078162025-12-08T09:54:28Z Importance of genetic parameters and uncertainty of MANIHOT, a new mechanistic cassava simulation model Moreno Cadena, Leidy Patricia Hoogenboom, Gerrit Fisher, James Myles Ramírez Villegas, Julián Armando Prager, Steven D. Becerra López Lavelle, Luis Augusto Pypers, Pieter Mejia de Tafur, Maria Sara Wallach, Daniel Muñoz Carpena, Rafael Asseng, Senthold manihot analysis efficiency temperatures cassava We identified the most sensitive genotype-specific parameters (GSPs) and their contribution to the uncertainty ofthe MANIHOT simulation model. We applied a global sensitivity and uncertainty analysis (GSUA) of the GSPs tothe simulation outputs for the cassava development, growth, and yield in contrasting environments. We com-pared enhanced Sampling for Uniformity, a qualitative screening method new to crop simulation modeling, andSobol, a quantitative, variance-based method. About 80% of the GSPs contributed to most of the variation inmaximum leaf area index (LAI), yield, and aboveground biomass at harvest. Relative importance of the GSPsvaried between warm and cool temperatures but did not differ between rainfed and no water limitation con-ditions. Interactions between GSPs explained 20% of the variance in simulated outputs. Overall, the most im-portant GSPs were individual node weight, radiation use efficiency, and maximum individual leaf area. Basetemperature for leaf development was more important for cool compared to warm temperatures. Parameteruncertainty had a substantial impact on model predictions in MANIHOT simulations, with the uncertainty 2–5times larger for warm compared to cool temperatures. Identification of important GSPs provides an objectiveway to determine the processes of a simulation model that are critical versus those that have little relevance. 2020-04 2020-03-19T20:49:53Z 2020-03-19T20:49:53Z Journal Article https://hdl.handle.net/10568/107816 en Open Access Elsevier Moreno-Cadena, L.P.; Hoogenboom, G.; Fisher, J.M.; Ramirez-Villegas, J.; Prager, S.D.; Becerra Lopez-Lavalle, L.A.; Pypers, P.; Mejia de Tafur, M.S.; Wallach, D.; Muñoz-Carpena, R.; Asseng, S. (2020). Importance of genetic parameters and uncertainty of MANIHOT, a newmechanistic cassava simulation model. European Journal of Agronomy ISSN: 1161-0301 14 p. |
| spellingShingle | manihot analysis efficiency temperatures cassava Moreno Cadena, Leidy Patricia Hoogenboom, Gerrit Fisher, James Myles Ramírez Villegas, Julián Armando Prager, Steven D. Becerra López Lavelle, Luis Augusto Pypers, Pieter Mejia de Tafur, Maria Sara Wallach, Daniel Muñoz Carpena, Rafael Asseng, Senthold Importance of genetic parameters and uncertainty of MANIHOT, a new mechanistic cassava simulation model |
| title | Importance of genetic parameters and uncertainty of MANIHOT, a new mechanistic cassava simulation model |
| title_full | Importance of genetic parameters and uncertainty of MANIHOT, a new mechanistic cassava simulation model |
| title_fullStr | Importance of genetic parameters and uncertainty of MANIHOT, a new mechanistic cassava simulation model |
| title_full_unstemmed | Importance of genetic parameters and uncertainty of MANIHOT, a new mechanistic cassava simulation model |
| title_short | Importance of genetic parameters and uncertainty of MANIHOT, a new mechanistic cassava simulation model |
| title_sort | importance of genetic parameters and uncertainty of manihot a new mechanistic cassava simulation model |
| topic | manihot analysis efficiency temperatures cassava |
| url | https://hdl.handle.net/10568/107816 |
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