A systems-level yield gap assessment of maize-soybean rotation under high- and low-management inputs in the Western US Corn Belt using APSIM

Quantifying yield gaps (potential minus actual yield) and identifying management practices to close those gaps is critical for sustaining high-yielding production systems. The objectives of this study were to: 1) calibrate and validate the APSIM maize and soybean models using local field experimenta...

Full description

Bibliographic Details
Main Authors: Balboa, Guillermo R., Archontoulis, Sotirios, Salvagiotti, Fernando, Garcia, Fernando O., Stewart, W.M., Francisco, Eros Artur Bohac, Vara Prasad, P.V., Ciampitti, Ignacio A.
Format: info:ar-repo/semantics/artículo
Language:Inglés
Published: Elsevier 2019
Subjects:
Online Access:http://hdl.handle.net/20.500.12123/5266
https://www.sciencedirect.com/science/article/pii/S0308521X18304360
https://doi.org/10.1016/j.agsy.2019.04.008
_version_ 1855035468130811904
author Balboa, Guillermo R.
Archontoulis, Sotirios
Salvagiotti, Fernando
Garcia, Fernando O.
Stewart, W.M.
Francisco, Eros Artur Bohac
Vara Prasad, P.V.
Ciampitti, Ignacio A.
author_browse Archontoulis, Sotirios
Balboa, Guillermo R.
Ciampitti, Ignacio A.
Francisco, Eros Artur Bohac
Garcia, Fernando O.
Salvagiotti, Fernando
Stewart, W.M.
Vara Prasad, P.V.
author_facet Balboa, Guillermo R.
Archontoulis, Sotirios
Salvagiotti, Fernando
Garcia, Fernando O.
Stewart, W.M.
Francisco, Eros Artur Bohac
Vara Prasad, P.V.
Ciampitti, Ignacio A.
author_sort Balboa, Guillermo R.
collection INTA Digital
description Quantifying yield gaps (potential minus actual yield) and identifying management practices to close those gaps is critical for sustaining high-yielding production systems. The objectives of this study were to: 1) calibrate and validate the APSIM maize and soybean models using local field experimental data and 2) use the calibrated model to estimate and explain yield gaps in the long term as a function of management (high- vs low-input) and weather conditions (wet-warm, wet-cold, dry-warm and dry-cold years) in the western US Corn Belt. The model was calibrated and validated using in-season crop growth data from six maize-soybean rotations obtained in 2014 and 2015 in Kansas, US. Experimental data included two management systems: 1) Common Practices (CP, low-input), wide row spacing, lower seeding rate, and lack of nutrient applications (except N in maize), and 2) Intensified Practices (IP, high-input), narrow rows, high seeding rate, and balanced nutrition. Results indicated that APSIM simulated in-season crop above ground mass and nitrogen (N) dynamics as well yields with a modeling efficiency of 0.75 to 0.92 and a relative root mean square error of 18 to 31%. The simulated maize yield gap across all years was 4.2 and 2.5 Mg ha−1 for low- and high-input, respectively. Similarly, the soybean yield gap was 2.5 and 0.8 Mg ha−1. Simulation results indicated that the high-input management system had greater yield stability across all weather years. In warm-dry years, yield gaps were larger for both crops and water scenarios. Irrigation reduced yield variation in maize more than in soybean, relative to the rainfed scenario. Besides irrigation, model analysis indicated that N fertilization for maize and narrow rows for soybean were the main factors contributing to yield gains. This study provides a systems level yield gap assessment of maize and soybean cropping system in Western US Corn Belt that can initiate dialogue (both experimental and modeling activities) on finding and applying best management systems to close current yield gaps.
format info:ar-repo/semantics/artículo
id INTA5266
institution Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina)
language Inglés
publishDate 2019
publishDateRange 2019
publishDateSort 2019
publisher Elsevier
publisherStr Elsevier
record_format dspace
spelling INTA52662024-10-25T12:30:09Z A systems-level yield gap assessment of maize-soybean rotation under high- and low-management inputs in the Western US Corn Belt using APSIM Balboa, Guillermo R. Archontoulis, Sotirios Salvagiotti, Fernando Garcia, Fernando O. Stewart, W.M. Francisco, Eros Artur Bohac Vara Prasad, P.V. Ciampitti, Ignacio A. Maíz Soja Rotación de Cultivos Rendimiento de Cultivos Estados Unidos Maize Soybeans Crop Rotation Yield Gap Crop Yield Quantifying yield gaps (potential minus actual yield) and identifying management practices to close those gaps is critical for sustaining high-yielding production systems. The objectives of this study were to: 1) calibrate and validate the APSIM maize and soybean models using local field experimental data and 2) use the calibrated model to estimate and explain yield gaps in the long term as a function of management (high- vs low-input) and weather conditions (wet-warm, wet-cold, dry-warm and dry-cold years) in the western US Corn Belt. The model was calibrated and validated using in-season crop growth data from six maize-soybean rotations obtained in 2014 and 2015 in Kansas, US. Experimental data included two management systems: 1) Common Practices (CP, low-input), wide row spacing, lower seeding rate, and lack of nutrient applications (except N in maize), and 2) Intensified Practices (IP, high-input), narrow rows, high seeding rate, and balanced nutrition. Results indicated that APSIM simulated in-season crop above ground mass and nitrogen (N) dynamics as well yields with a modeling efficiency of 0.75 to 0.92 and a relative root mean square error of 18 to 31%. The simulated maize yield gap across all years was 4.2 and 2.5 Mg ha−1 for low- and high-input, respectively. Similarly, the soybean yield gap was 2.5 and 0.8 Mg ha−1. Simulation results indicated that the high-input management system had greater yield stability across all weather years. In warm-dry years, yield gaps were larger for both crops and water scenarios. Irrigation reduced yield variation in maize more than in soybean, relative to the rainfed scenario. Besides irrigation, model analysis indicated that N fertilization for maize and narrow rows for soybean were the main factors contributing to yield gains. This study provides a systems level yield gap assessment of maize and soybean cropping system in Western US Corn Belt that can initiate dialogue (both experimental and modeling activities) on finding and applying best management systems to close current yield gaps. EEA Oliveros Fil: Balboa, Guillermo R. Kansas State University. Department of Agronomy; Estados Unidos. Universidad Nacional de Río Cuarto; Argentina Fil: Archontoulis, Sotirios. Iowa State University. Department of Agronomy; Estados Unidos Fil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros. Departamento de Agronomía; Argentina Fil: García, Fernando O. International Plant Nutrition Institute. Latin American Southern Cone; Argentina Fil: Stewart, W.M. International Plant Nutrition Institute. Great Plains Region; Estados Unidos Fil: Francisco, Eros Artur Bohac. International Plant Nutrition Institute. Cerrados; Brasil Fil: Vara Prasad, P.V. Kansas State University. Department of Agronomy; Estados Unidos Fil: Ciampitti, Ignacio A. Kansas State University. Department of Agronomy; Estados Unidos 2019-06-06T12:59:08Z 2019-06-06T12:59:08Z 2019-08 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/5266 https://www.sciencedirect.com/science/article/pii/S0308521X18304360 0308-521X https://doi.org/10.1016/j.agsy.2019.04.008 eng info:eu-repo/semantics/restrictedAccess application/pdf Elsevier Agricultural Systems 174 : 145-154 (August 2019)
spellingShingle Maíz
Soja
Rotación de Cultivos
Rendimiento de Cultivos
Estados Unidos
Maize
Soybeans
Crop Rotation
Yield Gap
Crop Yield
Balboa, Guillermo R.
Archontoulis, Sotirios
Salvagiotti, Fernando
Garcia, Fernando O.
Stewart, W.M.
Francisco, Eros Artur Bohac
Vara Prasad, P.V.
Ciampitti, Ignacio A.
A systems-level yield gap assessment of maize-soybean rotation under high- and low-management inputs in the Western US Corn Belt using APSIM
title A systems-level yield gap assessment of maize-soybean rotation under high- and low-management inputs in the Western US Corn Belt using APSIM
title_full A systems-level yield gap assessment of maize-soybean rotation under high- and low-management inputs in the Western US Corn Belt using APSIM
title_fullStr A systems-level yield gap assessment of maize-soybean rotation under high- and low-management inputs in the Western US Corn Belt using APSIM
title_full_unstemmed A systems-level yield gap assessment of maize-soybean rotation under high- and low-management inputs in the Western US Corn Belt using APSIM
title_short A systems-level yield gap assessment of maize-soybean rotation under high- and low-management inputs in the Western US Corn Belt using APSIM
title_sort systems level yield gap assessment of maize soybean rotation under high and low management inputs in the western us corn belt using apsim
topic Maíz
Soja
Rotación de Cultivos
Rendimiento de Cultivos
Estados Unidos
Maize
Soybeans
Crop Rotation
Yield Gap
Crop Yield
url http://hdl.handle.net/20.500.12123/5266
https://www.sciencedirect.com/science/article/pii/S0308521X18304360
https://doi.org/10.1016/j.agsy.2019.04.008
work_keys_str_mv AT balboaguillermor asystemslevelyieldgapassessmentofmaizesoybeanrotationunderhighandlowmanagementinputsinthewesternuscornbeltusingapsim
AT archontoulissotirios asystemslevelyieldgapassessmentofmaizesoybeanrotationunderhighandlowmanagementinputsinthewesternuscornbeltusingapsim
AT salvagiottifernando asystemslevelyieldgapassessmentofmaizesoybeanrotationunderhighandlowmanagementinputsinthewesternuscornbeltusingapsim
AT garciafernandoo asystemslevelyieldgapassessmentofmaizesoybeanrotationunderhighandlowmanagementinputsinthewesternuscornbeltusingapsim
AT stewartwm asystemslevelyieldgapassessmentofmaizesoybeanrotationunderhighandlowmanagementinputsinthewesternuscornbeltusingapsim
AT franciscoerosarturbohac asystemslevelyieldgapassessmentofmaizesoybeanrotationunderhighandlowmanagementinputsinthewesternuscornbeltusingapsim
AT varaprasadpv asystemslevelyieldgapassessmentofmaizesoybeanrotationunderhighandlowmanagementinputsinthewesternuscornbeltusingapsim
AT ciampittiignacioa asystemslevelyieldgapassessmentofmaizesoybeanrotationunderhighandlowmanagementinputsinthewesternuscornbeltusingapsim
AT balboaguillermor systemslevelyieldgapassessmentofmaizesoybeanrotationunderhighandlowmanagementinputsinthewesternuscornbeltusingapsim
AT archontoulissotirios systemslevelyieldgapassessmentofmaizesoybeanrotationunderhighandlowmanagementinputsinthewesternuscornbeltusingapsim
AT salvagiottifernando systemslevelyieldgapassessmentofmaizesoybeanrotationunderhighandlowmanagementinputsinthewesternuscornbeltusingapsim
AT garciafernandoo systemslevelyieldgapassessmentofmaizesoybeanrotationunderhighandlowmanagementinputsinthewesternuscornbeltusingapsim
AT stewartwm systemslevelyieldgapassessmentofmaizesoybeanrotationunderhighandlowmanagementinputsinthewesternuscornbeltusingapsim
AT franciscoerosarturbohac systemslevelyieldgapassessmentofmaizesoybeanrotationunderhighandlowmanagementinputsinthewesternuscornbeltusingapsim
AT varaprasadpv systemslevelyieldgapassessmentofmaizesoybeanrotationunderhighandlowmanagementinputsinthewesternuscornbeltusingapsim
AT ciampittiignacioa systemslevelyieldgapassessmentofmaizesoybeanrotationunderhighandlowmanagementinputsinthewesternuscornbeltusingapsim