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| 5. |  | MARIN, F. R.; JONES, J. W.; ROYCE, F.; SUGUITANI, C.; DONZELLI, J. L.; PALLONE FILHO, W.; NASSIF, D. S. P. Parameterization and evaluation of predictions of DSSAT/CANEGRO for Brazilian sugarcane. In: CONGRESSO BRASILEIRO DE AGROMETEOROLOGIA, 17., 2011, Guarapari. Riscos climáticos e cenários agrícolas futuros: anais. Guarapari: Incaper, 2011. p. 1-5. 1 CD-ROM. CBA 2011.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 6. | | MARIN, F. R.; SUGUITANI, C.; DONZELLI, J. L.; PALLONE, W. J.; NASSIF, D. S. P.; SAKAI, R. H.; POLZER, D. L.; VIANA, M. S. Avaliação do modelo CANEGRO/DSSAT para quatro cultivares de cana-de-açúcar. In: CONGRESSO BRASILEIRO DE AGROMETEOROLOGIA, 16, 2009, Belo Horizonte. Anais... Viçosa, MG: UFV; Sete Lagoas: Embrapa Milho e Sorgo, 2009. Não paginado. 1 CD-ROM. CBA 2009.| Biblioteca(s): Embrapa Agricultura Digital. |
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| Registros recuperados : 6 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
19/10/2011 |
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Data da última atualização: |
03/03/2023 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
MARIN, F. R.; JONES, J. W.; ROYCE, F.; SUGUITANI, C.; DONZELLI, J. L.; PALLONE FILHO, W.; NASSIF, D. S. P. |
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Afiliação: |
FÁBIO RICARDO MARIN, CNPTIA; JAMES W. JONES, Universidade da Florida; FEDERICK ROYCE, Universidade da Florida; CARLOS SUGUITANI, Centro de Tecnologia Canavieira; JORGE L. DONZELLI, Centro de Tecnologia Canavieira; WANDER PALLONE FILHO, Centro de Tecnologia; DANIEL S. P. NASSIF, ESALQ/USP. |
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Título: |
Parameterization and evaluation of predictions of DSSAT/CANEGRO for Brazilian sugarcane. |
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Ano de publicação: |
2011 |
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Fonte/Imprenta: |
In: CONGRESSO BRASILEIRO DE AGROMETEOROLOGIA, 17., 2011, Guarapari. Riscos climáticos e cenários agrícolas futuros: anais. Guarapari: Incaper, 2011. |
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Páginas: |
p. 1-5. |
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Descrição Física: |
1 CD-ROM. |
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Idioma: |
Inglês |
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Notas: |
CBA 2011. |
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Conteúdo: |
The DSSAT/CANEGRO model was parameterized and its predictions evaluated using data from five sugarcane experiments conducted in Southern Brazil. Some parameters whose values were either directly measured or considered to be well-known were not adjusted. Ten of the 20 parameters were optimized using a Generalized Likelihood Uncertainty Estimation (GLUE) algorithm using the leave-one-out cross-validation technique. Model predictions were evaluated using measured data of LAI, stalk and aerial dry mass, sucrose content, and soil water content, using bias, root mean squared error (RMSE), modeling efficiency (Eff), correlation coefficient and agreement index. The DSSAT/CANEGRO model simulated the sugarcane crop in Southern Brazil well, using the parameterization reported here. The soil water content predictions were better for rainfed (mean RMSE=0.122mm) than for irrigated treatment (mean RMSE=0.214mm). Predictions were best for aerial dry mass (Eff=0.85), followed by stalk dry mass (Eff=0.765) and then sucrose mass (Eff=0.17). Number of green leaves showed the worst fit (Eff=-2.300). |
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Palavras-Chave: |
Cana-de-açúcar; Modelagem de culturas; Modeling; Modelo DSSAT/CANEGRO; Validação. |
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Thesaurus NAL: |
Model validation; Saccharum; Sugarcane. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/43917/1/cba04-285-366.pdf
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Marc: |
LEADER 02049nam a2200301 a 4500
001 1903514
005 2023-03-03
008 2011 bl uuuu u00u1 u #d
100 1 $aMARIN, F. R.
245 $aParameterization and evaluation of predictions of DSSAT/CANEGRO for Brazilian sugarcane.$h[electronic resource]
260 $aIn: CONGRESSO BRASILEIRO DE AGROMETEOROLOGIA, 17., 2011, Guarapari. Riscos climáticos e cenários agrícolas futuros: anais. Guarapari: Incaper$c2011
300 $ap. 1-5.$c1 CD-ROM.
500 $aCBA 2011.
520 $aThe DSSAT/CANEGRO model was parameterized and its predictions evaluated using data from five sugarcane experiments conducted in Southern Brazil. Some parameters whose values were either directly measured or considered to be well-known were not adjusted. Ten of the 20 parameters were optimized using a Generalized Likelihood Uncertainty Estimation (GLUE) algorithm using the leave-one-out cross-validation technique. Model predictions were evaluated using measured data of LAI, stalk and aerial dry mass, sucrose content, and soil water content, using bias, root mean squared error (RMSE), modeling efficiency (Eff), correlation coefficient and agreement index. The DSSAT/CANEGRO model simulated the sugarcane crop in Southern Brazil well, using the parameterization reported here. The soil water content predictions were better for rainfed (mean RMSE=0.122mm) than for irrigated treatment (mean RMSE=0.214mm). Predictions were best for aerial dry mass (Eff=0.85), followed by stalk dry mass (Eff=0.765) and then sucrose mass (Eff=0.17). Number of green leaves showed the worst fit (Eff=-2.300).
650 $aModel validation
650 $aSaccharum
650 $aSugarcane
653 $aCana-de-açúcar
653 $aModelagem de culturas
653 $aModeling
653 $aModelo DSSAT/CANEGRO
653 $aValidação
700 1 $aJONES, J. W.
700 1 $aROYCE, F.
700 1 $aSUGUITANI, C.
700 1 $aDONZELLI, J. L.
700 1 $aPALLONE FILHO, W.
700 1 $aNASSIF, D. S. P.
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