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Modeling sugarcane development and growth within ECOSMOS biophysical model

dc.contributor.authorColmanetti, Michel Anderson Almeida
dc.contributor.authorCuadra, Santiago Vianna
dc.contributor.authorLamparelli, Rubens Augusto Camargo
dc.contributor.authorCabral, Osvaldo Machado Rodrigues
dc.contributor.authorde Castro Victoria, Daniel
dc.contributor.authorAlmeida Monteiro, José Eduardo Boffino de
dc.contributor.authorde Freitas, Helber Custódio [UNESP]
dc.contributor.authorGaldos, Marcelo Valadares
dc.contributor.authorMarafon, Anderson Carlos
dc.contributor.authorAndrade Junior, Aderson Soares de
dc.contributor.authorAnjos e Silva, Sergio Delmar dos
dc.contributor.authorBuffon, Vinicius Bof
dc.contributor.authorHernandes, Thayse Aparecida Dourado
dc.contributor.authorle Maire, Guerric
dc.contributor.institutionUniversidade Estadual de Campinas (UNICAMP)
dc.contributor.institutionEmpresa Brasileira de Pesquisa Agropecuária (EMBRAPA)
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionRothamsted Research
dc.contributor.institutionBrazilian Center for Research in Energy and Materials (CNPEM) - Brazilian Biorenewables National Laboratory
dc.contributor.institutionUMR Eco&Sols
dc.contributor.institutionSupAgro
dc.date.accessioned2025-04-29T20:11:25Z
dc.date.issued2024-03-01
dc.description.abstractSugarcane plays an important role in electricity and sugar production and is a viable biofuel. Developing and optimizing a mechanism that can predict crop growth and yield at different spatiotemporal scales can promote the understanding of the effects of cultivation on the ecosystem, while providing options for optimizing management measures and improving the operational procedures of sugarcane growers. The main objective of this study is to integrate the sugarcane module into the ECOSystem MOdel Simulator (ECOSMOS) model and calibrate a parameter set for sugarcane genotypes groups (using different datasets); the model supports datasets that vary in complexity (from flux tower experiments to operational plots), while accounting for high genotype-by-environment-by-management (GxExM) variability. First, we calibrated the ECOSMOS biophysical and physiological parameters for the sugarcane module using two micrometeorological experimental sites, based on eddy-covariance and biomass measurements. Second, sugarcane genotypes located in different regions of contrasting climate conditions were split into two groups based on their period of harvest, i.e., early or mid-to-late harvest season, and two parameter sets were proposed. The sugarcane module was used to estimate the yield of numerous plots, using two different parameter sets, namely, the general and regionally-specific parameter sets. The model could successfully simulate the biophysical and physiological processes of the biomass of stalks and leaves, energy and carbon fluxes, and soil-water dynamics; for Experimental Site 2, the Nash-Sutcliffe efficiency (NSE) was 0.14–0.86 and the relative root mean square error (RRMSE) was 13–112. However, the generic parameter set did not perform well in all production environments, and the difference between the observed and simulated yields ranged from 0.9 to 14.5 (Mg ha-1). Hence, a novel calibration approach adopted in this study improved the module's accuracy, while improving the performances for all five production environments, with the difference between the observed and simulate yields being 0.3–2.2 (Mg ha-1). Although the two parameter sets can be used as a reference for sugarcane plantations in Brazil, we recommend recalibrating the model (for ensuring higher accuracy) before operational applications. Notably, the ECOSMOS-sugarcane model is emerging as a complex ecosystem model that can support the quantifications and evaluations of the effects of sugarcane plantations on the carbon and water balances in different environmental conditions, particularly in tropical regions.en
dc.description.affiliationCenter of Energy Planning/University of Campinas, SP
dc.description.affiliationEMBRAPA Digital Agriculture, SP
dc.description.affiliationEMBRAPA Environment, SP
dc.description.affiliationSão Paulo State University, SP
dc.description.affiliationSustainable Soils and Crops Rothamsted Research
dc.description.affiliationEMBRAPA Coastal Tablelands, AL
dc.description.affiliationEMBRAPA Mid-North
dc.description.affiliationEMBRAPA Temperate Agriculture, RS
dc.description.affiliationEMBRAPA Cerrados, DF
dc.description.affiliationBrazilian Center for Research in Energy and Materials (CNPEM) - Brazilian Biorenewables National Laboratory, SP
dc.description.affiliationCIRAD UMR Eco&Sols
dc.description.affiliationEco&Sols University of Montpellier CIRAD INRA IRD SupAgro
dc.description.affiliationUnespSão Paulo State University, SP
dc.identifierhttp://dx.doi.org/10.1016/j.eja.2023.127061
dc.identifier.citationEuropean Journal of Agronomy, v. 154.
dc.identifier.doi10.1016/j.eja.2023.127061
dc.identifier.issn1161-0301
dc.identifier.scopus2-s2.0-85181973546
dc.identifier.urihttps://hdl.handle.net/11449/308148
dc.language.isoeng
dc.relation.ispartofEuropean Journal of Agronomy
dc.sourceScopus
dc.subjectECOSMOS
dc.subjectProcess-based modeling
dc.subjectSugarcane
dc.titleModeling sugarcane development and growth within ECOSMOS biophysical modelen
dc.typeArtigopt
dspace.entity.typePublication

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