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dc.contributor.author
Ojeda, Jonathan Jesus  
dc.contributor.author
Volenec, Jeffrey J.  
dc.contributor.author
Brouder, Sylvie M.  
dc.contributor.author
Caviglia, Octavio Pedro  
dc.contributor.author
Agnusdei, Mónica G.  
dc.date.available
2020-01-09T21:04:41Z  
dc.date.issued
2018-01  
dc.identifier.citation
Ojeda, Jonathan Jesus; Volenec, Jeffrey J.; Brouder, Sylvie M.; Caviglia, Octavio Pedro; Agnusdei, Mónica G.; Modelling stover and grain yields, and subsurface artificial drainage from long-term corn rotations using APSIM; Elsevier Science; Agricultural Water Management; 195; 1-2018; 154-171  
dc.identifier.issn
0378-3774  
dc.identifier.uri
http://hdl.handle.net/11336/94260  
dc.description.abstract
The Agricultural Production Systems Simulator (APSIM) is a key tool to identify agricultural management practices seeking to simultaneously optimize agronomic productivity and input use efficiencies. The aims of this study were to validate APSIM for prediction of stover and grain yield of corn in four contrasting soils with varied N fertilizer applications (156–269 kg N ha−1) and to predict timing and volume from artificial subsurface drains in continuous corn and corn-soybean rotations in a silty clay loam soil at West Lafayette, IN. The APSIM validation was carried-out using a long-term dataset of corn stover and grain yields from the North Central Region of IN. The CCC (Concordance Correlation Coefficient) and SB (Simulation Bias) were used to statistically evaluate the model performance. The CCC integrates precision through Pearson’s correlation coefficient and accuracy by bias, and SB indicates the bias of the simulation from the measurement. The model demonstrated very good (CCC = 0.96; SB = 0%) and satisfactory (CCC = 0.85; SB = 2%) ability to simulate stover and grain yield, respectively. Grain yield was better predicted in continuous corn (CCC = 0.73–0.91; SB = 19–21%) than in corn-soybean rotations (CCC = 0.56–0.63; SB = 17–18%), while stover yield was well predicted in both crop rotations (CCC = 0.85–0.98; SB = 1–17%). The model demonstrated acceptable ability to simulate annual subsurface drainage in both rotations (CCC = 0.63–0.75; SB = 2–37%) with accuracy being lower in the continuous corn system than in corn-soybean rotation system (CCC = 0.61-0.63; SB = 9–12%). Daily subsurface drainage events were well predicted by APSIM during late spring and summer when crop water use was high, but under-predicted during fall, winter and early spring when evapotranspiration was low. Occasional flow events occurring in summer when soils were not saturated were not predicted by APSIM and may represent preferential flow paths currently not represented in the model. APSIM is a promising tool for simulating yield and water losses for corn-based cropping systems in north central Indiana US.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Elsevier Science  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
CORN-BASED CROPPING SYSTEMS  
dc.subject
INDIANA  
dc.subject
MAIZE  
dc.subject
MODEL VALIDATION  
dc.subject
WATER FLOW  
dc.subject.classification
Agricultura  
dc.subject.classification
Agricultura, Silvicultura y Pesca  
dc.subject.classification
CIENCIAS AGRÍCOLAS  
dc.title
Modelling stover and grain yields, and subsurface artificial drainage from long-term corn rotations using APSIM  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2019-12-20T22:55:08Z  
dc.journal.volume
195  
dc.journal.pagination
154-171  
dc.journal.pais
Países Bajos  
dc.journal.ciudad
Amsterdam  
dc.description.fil
Fil: Ojeda, Jonathan Jesus. Universidad Nacional de Entre Ríos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina  
dc.description.fil
Fil: Volenec, Jeffrey J.. Purdue University; Estados Unidos  
dc.description.fil
Fil: Brouder, Sylvie M.. Purdue University; Estados Unidos  
dc.description.fil
Fil: Caviglia, Octavio Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires; Argentina  
dc.description.fil
Fil: Agnusdei, Mónica G.. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires; Argentina  
dc.journal.title
Agricultural Water Management  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0378377417303293  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.agwat.2017.10.010