Modelling stover and grain yields, and subsurface artificial drainagefrom long-term corn rotations using APSIM

The Agricultural Production Systems Simulator (APSIM) is a key tool to identify agricultural managementpractices seeking to simultaneously optimize agronomic productivity and input use efficiencies. The aimsof this study were to validate APSIM for prediction of stover and grain yield of corn in four...

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Main Authors: Ojeda, Jonathan Jesus, Volenec, Jeffrey J., Brouder, Sylvie M., Caviglia, Octavio, Agnusdei, Monica Graciela
Format: info:ar-repo/semantics/artículo
Language:Inglés
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/20.500.12123/2842
https://www.sciencedirect.com/science/article/pii/S0378377417303293?via%3Dihub
https://doi.org/10.1016/j.agwat.2017.10.010
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author Ojeda, Jonathan Jesus
Volenec, Jeffrey J.
Brouder, Sylvie M.
Caviglia, Octavio
Agnusdei, Monica Graciela
author_browse Agnusdei, Monica Graciela
Brouder, Sylvie M.
Caviglia, Octavio
Ojeda, Jonathan Jesus
Volenec, Jeffrey J.
author_facet Ojeda, Jonathan Jesus
Volenec, Jeffrey J.
Brouder, Sylvie M.
Caviglia, Octavio
Agnusdei, Monica Graciela
author_sort Ojeda, Jonathan Jesus
collection INTA Digital
description The Agricultural Production Systems Simulator (APSIM) is a key tool to identify agricultural managementpractices seeking to simultaneously optimize agronomic productivity and input use efficiencies. The aimsof this study were to validate APSIM for prediction of stover and grain yield of corn in four contrasting soilswith varied N fertilizer applications (156–269 kg N ha−1) and to predict timing and volume from artificialsubsurface 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 fromthe 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’scorrelation coefficient and accuracy by bias, and SB indicates the bias of the simulation from the mea-surement. 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 continuouscorn (CCC = 0.73–0.91; SB = 19–21%) than in corn-soybean rotations (CCC = 0.56–0.63; SB = 17–18%), whilestover yield was well predicted in both crop rotations (CCC = 0.85–0.98; SB = 1–17%). The model demon-strated 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 sys-tem (CCC = 0.61-0.63; SB = 9–12%). Daily subsurface drainage events were well predicted by APSIM duringlate spring and summer when crop water use was high, but under-predicted during fall, winter and earlyspring when evapotranspiration was low. Occasional flow events occurring in summer when soils werenot saturated were not predicted by APSIM and may represent preferential flow paths currently not rep-resented in the model. APSIM is a promising tool for simulating yield and water losses for corn-basedcropping systems in north central Indiana US.
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institution Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina)
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publishDate 2018
publishDateRange 2018
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spelling INTA28422018-07-20T15:36:43Z Modelling stover and grain yields, and subsurface artificial drainagefrom long-term corn rotations using APSIM Ojeda, Jonathan Jesus Volenec, Jeffrey J. Brouder, Sylvie M. Caviglia, Octavio Agnusdei, Monica Graciela Maíz Zea Mays Rastrojo Granos Drenaje Subterráneo Rotación de Cultivos Rendimiento de Cultivos Modelos de Simulación Simulation Models Yields Crop Rotation Subsurface Drainage Grain Maize APSIM Corn-based Cropping Systems Indiana, Estados Unidos The Agricultural Production Systems Simulator (APSIM) is a key tool to identify agricultural managementpractices seeking to simultaneously optimize agronomic productivity and input use efficiencies. The aimsof this study were to validate APSIM for prediction of stover and grain yield of corn in four contrasting soilswith varied N fertilizer applications (156–269 kg N ha−1) and to predict timing and volume from artificialsubsurface 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 fromthe 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’scorrelation coefficient and accuracy by bias, and SB indicates the bias of the simulation from the mea-surement. 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 continuouscorn (CCC = 0.73–0.91; SB = 19–21%) than in corn-soybean rotations (CCC = 0.56–0.63; SB = 17–18%), whilestover yield was well predicted in both crop rotations (CCC = 0.85–0.98; SB = 1–17%). The model demon-strated 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 sys-tem (CCC = 0.61-0.63; SB = 9–12%). Daily subsurface drainage events were well predicted by APSIM duringlate spring and summer when crop water use was high, but under-predicted during fall, winter and earlyspring when evapotranspiration was low. Occasional flow events occurring in summer when soils werenot saturated were not predicted by APSIM and may represent preferential flow paths currently not rep-resented in the model. APSIM is a promising tool for simulating yield and water losses for corn-basedcropping systems in north central Indiana US. EEA Paraná Fil: Ojeda, Jonathan Jesus. University of Tasmania. Tasmanian Institute of Agriculture; Australia. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; Argentina Fil: Volenec, Jeffrey J. Purdue University. Department of Agronomy; Estados Unidos Fil: Brouder, Sylvie M. Purdue University. Department of Agronomy; Estados Unidos Fil: 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; Argentina Fil: Agnusdei, Monica Graciela. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina 2018-07-20T15:27:58Z 2018-07-20T15:27:58Z 2018 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/2842 https://www.sciencedirect.com/science/article/pii/S0378377417303293?via%3Dihub 0378-3774 https://doi.org/10.1016/j.agwat.2017.10.010 eng info:eu-repo/semantics/restrictedAccess application/pdf Agricultural water management 195 : 154–171. (2018)
spellingShingle Maíz
Zea Mays
Rastrojo
Granos
Drenaje Subterráneo
Rotación de Cultivos
Rendimiento de Cultivos
Modelos de Simulación
Simulation Models
Yields
Crop Rotation
Subsurface Drainage
Grain
Maize
APSIM
Corn-based Cropping Systems
Indiana, Estados Unidos
Ojeda, Jonathan Jesus
Volenec, Jeffrey J.
Brouder, Sylvie M.
Caviglia, Octavio
Agnusdei, Monica Graciela
Modelling stover and grain yields, and subsurface artificial drainagefrom long-term corn rotations using APSIM
title Modelling stover and grain yields, and subsurface artificial drainagefrom long-term corn rotations using APSIM
title_full Modelling stover and grain yields, and subsurface artificial drainagefrom long-term corn rotations using APSIM
title_fullStr Modelling stover and grain yields, and subsurface artificial drainagefrom long-term corn rotations using APSIM
title_full_unstemmed Modelling stover and grain yields, and subsurface artificial drainagefrom long-term corn rotations using APSIM
title_short Modelling stover and grain yields, and subsurface artificial drainagefrom long-term corn rotations using APSIM
title_sort modelling stover and grain yields and subsurface artificial drainagefrom long term corn rotations using apsim
topic Maíz
Zea Mays
Rastrojo
Granos
Drenaje Subterráneo
Rotación de Cultivos
Rendimiento de Cultivos
Modelos de Simulación
Simulation Models
Yields
Crop Rotation
Subsurface Drainage
Grain
Maize
APSIM
Corn-based Cropping Systems
Indiana, Estados Unidos
url http://hdl.handle.net/20.500.12123/2842
https://www.sciencedirect.com/science/article/pii/S0378377417303293?via%3Dihub
https://doi.org/10.1016/j.agwat.2017.10.010
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