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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
18/08/2025 |
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Data da última atualização: |
19/08/2025 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
OLIVEIRA, M. P. G. de; CUADRA, S. V.; BENDER, F. D.; MONTEIRO, J. E. B. de A. |
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Afiliação: |
MONIQUE PIRES GRAVINA DE OLIVEIRA; SANTIAGO VIANNA CUADRA, CNPTIA; FABIANI DENISE BENDER; JOSE EDUARDO BOFFINO DE ALMEIDA MONTEIRO, CNPTIA. |
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Título: |
A role for regression trees in the calibration of a new process-based crop model. |
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Ano de publicação: |
2025 |
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Fonte/Imprenta: |
European Journal of Agronomy, v. 171, 127805, 2025. |
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DOI: |
https://doi.org/10.1016/j.eja.2025.127805 |
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Idioma: |
Inglês |
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Conteúdo: |
While some researchers aim to standardize crop model calibration, there is still room for enhancing current practices. In this study, we explore the use of regression trees to enhance model understanding within the commonly used trial-and-error method. As an approximation of this approach, we sampled multiple values and combined them into different parameter sets. We used regression trees to model simulation errors from these sets and investigated the relationships they made explicit. We also used the trees to aid in the choice of parameter values. From the multiple sets, we selected the best among those that followed the rule leading to the lowest average simulation error. We compared these results to those of the set that directly minimizes simulation error and to a recently developed calibration protocol, used as a performance reference. Different subsets of the dataset were used for calibration and evaluation to assess robustness. The trees consistently identified relationships between parameter values and low errors across all subsets and approaches, including how parameter choices compensate for one another. As a calibration approach, all methods assessed performed similarly well for aboveground biomass and evapotranspiration, as well as for yield in one of the three calibrated cultivars. The most marked differences appeared in the variability of parameter values obtained across subsets, for which none of the approaches matched the protocol. While regression trees contributed to improved model understanding, particularly in support of manual calibration, a combined approach using the protocol to determine values and trees to visualize outcomes appears promising. MenosWhile some researchers aim to standardize crop model calibration, there is still room for enhancing current practices. In this study, we explore the use of regression trees to enhance model understanding within the commonly used trial-and-error method. As an approximation of this approach, we sampled multiple values and combined them into different parameter sets. We used regression trees to model simulation errors from these sets and investigated the relationships they made explicit. We also used the trees to aid in the choice of parameter values. From the multiple sets, we selected the best among those that followed the rule leading to the lowest average simulation error. We compared these results to those of the set that directly minimizes simulation error and to a recently developed calibration protocol, used as a performance reference. Different subsets of the dataset were used for calibration and evaluation to assess robustness. The trees consistently identified relationships between parameter values and low errors across all subsets and approaches, including how parameter choices compensate for one another. As a calibration approach, all methods assessed performed similarly well for aboveground biomass and evapotranspiration, as well as for yield in one of the three calibrated cultivars. The most marked differences appeared in the variability of parameter values obtained across subsets, for which none of the approaches matched the protocol. While regression trees cont... Mostrar Tudo |
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Palavras-Chave: |
AgS model; Árvores de regressão; Calibração; Metamodel; Surrogate model. |
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Thesaurus Nal: |
Calibration. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 02427naa a2200241 a 4500
001 2178074
005 2025-08-19
008 2025 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.eja.2025.127805$2DOI
100 1 $aOLIVEIRA, M. P. G. de
245 $aA role for regression trees in the calibration of a new process-based crop model.$h[electronic resource]
260 $c2025
520 $aWhile some researchers aim to standardize crop model calibration, there is still room for enhancing current practices. In this study, we explore the use of regression trees to enhance model understanding within the commonly used trial-and-error method. As an approximation of this approach, we sampled multiple values and combined them into different parameter sets. We used regression trees to model simulation errors from these sets and investigated the relationships they made explicit. We also used the trees to aid in the choice of parameter values. From the multiple sets, we selected the best among those that followed the rule leading to the lowest average simulation error. We compared these results to those of the set that directly minimizes simulation error and to a recently developed calibration protocol, used as a performance reference. Different subsets of the dataset were used for calibration and evaluation to assess robustness. The trees consistently identified relationships between parameter values and low errors across all subsets and approaches, including how parameter choices compensate for one another. As a calibration approach, all methods assessed performed similarly well for aboveground biomass and evapotranspiration, as well as for yield in one of the three calibrated cultivars. The most marked differences appeared in the variability of parameter values obtained across subsets, for which none of the approaches matched the protocol. While regression trees contributed to improved model understanding, particularly in support of manual calibration, a combined approach using the protocol to determine values and trees to visualize outcomes appears promising.
650 $aCalibration
653 $aAgS model
653 $aÁrvores de regressão
653 $aCalibração
653 $aMetamodel
653 $aSurrogate model
700 1 $aCUADRA, S. V.
700 1 $aBENDER, F. D.
700 1 $aMONTEIRO, J. E. B. de A.
773 $tEuropean Journal of Agronomy$gv. 171, 127805, 2025.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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| 9. |  | SANTOS JÚNIOR, J. B. O.; AMORIM, J. R. de A.; RESENDE, R. S.; SANTOS LIMA, M. A.; MATOS, J. D. S. de; SILVA, P. S. da. Caracterização hidrodinâmica de poços tubulares na bacia hidrográfica do rio Sergipe. In: CONGRESSO NACIONAL DE IRRIGAÇÃO E DRENAGEM, 17., 2007, Mossoró. Agricultura no semi-árido: anais. Mossoró: [s.n.], 2007. 1 CD-ROM.| Tipo: Artigo em Anais de Congresso / Nota Técnica | Circulação/Nível: -- - -- |
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| 13. | | MUNIZ, E. N.; FONTES, J. A.; ALMEIDA, S. A.; MATOS, J. D. S. de; SOUZA, T. C. B. de; SILVA, A. V. C. da; EZEQUIEL, J. M. B.; RANGEL, J. H. de A. Adição de metionina protegida da degradação ruminal na dieta de cordeiros Santa Inês confinados. In: REUNIÃO ANUAL DA SOCIEDADE BRASILEIRA DE ZOOTECNIA, 43., 2006, João Pessoa. Anais dos resumos... Viçosa, MG: Sociedade Brasileira de Zootecnia, 2006.| Tipo: Artigo em Anais de Congresso |
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| Registros recuperados : 13 | |
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