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resumen

Resumen
Simulation models for perennial energy crops such as switchgrass (Panicum virgatum L.) and Miscanthus (Miscanthus x giganteus) can be useful tools to design management strategies for biomass productivity improvement in US environments. The Agricultural Production Systems Simulator (APSIM) is a biophysical model with the potential to simulate the growth of perennial crops. APSIM crop modules do not exist for switchgrass and Miscanthus, however, [ver mas...]
dc.contributor.authorOjeda, Jonathan Jesus
dc.contributor.authorVolenec, Jeffrey J.
dc.contributor.authorBrouder, Sylvie M.
dc.contributor.authorCaviglia, Octavio
dc.contributor.authorAgnusdei, Monica Graciela
dc.date.accessioned2018-09-28T15:14:41Z
dc.date.available2018-09-28T15:14:41Z
dc.date.issued2017
dc.identifier.issn1757-1707
dc.identifier.otherhttps://doi.org/10.1111/gcbb.12384
dc.identifier.urihttp://hdl.handle.net/20.500.12123/3508
dc.identifier.urihttps://onlinelibrary.wiley.com/doi/full/10.1111/gcbb.12384
dc.description.abstractSimulation models for perennial energy crops such as switchgrass (Panicum virgatum L.) and Miscanthus (Miscanthus x giganteus) can be useful tools to design management strategies for biomass productivity improvement in US environments. The Agricultural Production Systems Simulator (APSIM) is a biophysical model with the potential to simulate the growth of perennial crops. APSIM crop modules do not exist for switchgrass and Miscanthus, however, re-parameterization of existing APSIM modules could be used to simulate the growth of these perennials. Our aim was to evaluate the ability of APSIM to predict the dry matter (DM) yield of switchgrass and Miscanthus at several US locations. The Lucerne (for switchgrass) and Sugarcane (for Miscanthus) APSIM modules were calibrated using data from four locations in Indiana. A sensitivity analysis informed the relative impact of changes in plant and soil parameters of APSIM Lucerne and APSIM Sugarcane modules. An independent dataset of switchgrass and Miscanthus DM yields from several US environments was used to validate these re-parameterized APSIM modules. The re-parameterized modules simulated DM yields of switchgrass [0.95 for CCC (concordance correlation coefficient) and 0 for SB (bias of the simulation from the measurement)] and Miscanthus (0.65 and 0% for CCC and SB, respectively) accurately at most locations with the exception of switchgrass at southern US sites (0.01 for CCC and 2% for SB). Therefore, the APSIM model is a promising tool for simulating DM yields for switchgrass and Miscanthus while accounting for environmental variability. Given our study was strictly based on APSIM calibrations at Indiana locations, additional research using more extensive calibration data may enhance APSIM robustness.eng
dc.formatapplication/pdfeng
dc.language.isoeng
dc.publisherWiley
dc.rightsinfo:eu-repo/semantics/restrictedAccesseng
dc.sourceGlobal change biology Bioenergy 9 (4) : 796–816. (April 2017)eng
dc.subjectPanicum Virgatumes_AR
dc.subjectMiscanthuses_AR
dc.subjectSistemas de Explotaciónes_AR
dc.subjectFarming Systemseng
dc.subjectRendimientoes_AR
dc.subjectYieldseng
dc.subjectTécnicas de Predicciónes_AR
dc.subjectForecastingeng
dc.subjectModelos de Simulaciónes_AR
dc.subjectSimulation Modelseng
dc.subjectBioenergíaes_AR
dc.subjectBioenergyeng
dc.subjectBiomasaes_AR
dc.subjectBiomasseng
dc.subject.otherEstados Unidoses_AR
dc.subject.otherSwitchgrasseng
dc.subject.otherAgricultural Production Systems Simulatoreng
dc.subject.otherAPSIMeng
dc.titleEvaluation of Agricultural Production Systems Simulator as yield predictor of Panicum virgatum and Miscanthus x giganteus in several US environmentseng
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articleeng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.description.origenEEA Paranáes_AR
dc.description.filFil: Ojeda, Jonathan Jesus. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentinaes_AR
dc.description.filFil: Volenec, Jeffrey J. Purdue University. Department of Agronomy; Estados Unidoses_AR
dc.description.filFil: Brouder, Sylvie M. Purdue University. Department of Agronomy; Estados Unidoses_AR
dc.description.filFil: Caviglia, Octavio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná. Grupo Ecología Forestal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; Argentinaes_AR
dc.description.filFil: Agnusdei, Monica Graciela. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentinaes_AR
dc.subtypecientifico


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