Evaluation of the agricultural production systems simulator simulating Lucerne and annual ryegrass dry matter yield in the Argentine Pampas and south-eastern Australia

Autores
Ojeda, Jonathan Jesus; Pembleton, Keith G.; Islam, Md. Rafiqul; Agnusdei, Monica Graciela; Garcia, Sergio Carlos
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión aceptada
Descripción
Modelling plant growth provides a tool for evaluating interactions between environment and management of forage crops for pasture-based livestock systems. Consequently, biophysical and farm systems models are becoming important tools for studying production systems that are based on forage crops. The Agricultural Production Systems Simulator (APSIM) is a model with the potential to compare the growth of annual forage crops and perennial pastures. However, information is limited about how accurately the Lucerne and Weed modules represent the growth and development of forage crops and pastures under different managements, soil types and environments in South America. This study evaluated the capacity of APSIM to simulate the growth rates and predict the dry matter (DM) yield of Lucerne (Medicago sativa L.) and annual ryegrass (Lolium multiflorum Lam.) in contrasting climatic regions of Argentina. In addition, at several Australian locations, DM yields of both crops were simulated to ensure that possible changes to the model not interfere with the robust APSIM performance that was already shown in south-eastern Australia. Initial simulations for Lucerne and ryegrass were made with original Lucerne and Weed modules of APSIM, respectively. Simulated DM yield was then compared with field data collected from the same crops growning five locations in the Argentine Pampas and seven locations in south-eastern Australia over 5 of years. APSIM predicted DM yield of Lucerne at each harvest with reasonable accuracy [0.59, 0.77 and 0.77 for R2, correlation coefficient and concordance correlation coefficient (CCC), respectively]. However, these statistics improved when the DM yield was analysed by annual accumulation,with values of 0.87, 0.93 and 0.92 for R2, correlation coefficient and CCC, respectively. APSIM, generally, over-predicted DM yield of annual ryegrass at the first harvest. Nonetheless, when the Weed module was modified through changes in phenology and transpiration efficiency, performance improved (values of 0.89, 0.94 and 0.93 for R2, correlation coefficient and CCC, respectively). This study showed that annual DM yield of Lucerne can be successfully modelled by the APSIM Lucerne module without any modifications, using a crop modelling approach. However, successfully modelling of Lucerne DM yield by harvest will require further development of the model. Moreover, modification of model parameters associated with phenology and transpiration was required to enable the Weed module of APSIM simulate growth and yield of annual ryegrass in a range of geographic locations within the Argentine Pampas
EEA Balcarce
Fil: Ojeda, Jonathan Jesus. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; Argentina
Fil: Pembleton, Keith G. University of Tasmania. Tasmanian Institute of Agriculture; Australia. University of Southern Queensland. Institute for Agriculture and the Environment; Australia
Fil: Islam, M.R. University of Sydney. Faculty of Veterinary Science. Dairy Science Group; Australia
Fil: Agnusdei, Monica Graciela. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fil: Garcia, Sergio Carlos. University of Sydney. Faculty of Veterinary Science. Dairy Science Group; Australia
Fuente
Agricultural systems 143 : 61-75. (March 2016)
Materia
Medicago Sativa
Lolium Multiflorum
Contenido de Materia Seca
Rendimiento
Producción
Dry Matter Content
Yields
Production
Región Pampeana
Alfalfa
Raigras Anual
Nivel de accesibilidad
acceso restringido
Condiciones de uso
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/1279

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oai_identifier_str oai:localhost:20.500.12123/1279
network_acronym_str INTADig
repository_id_str l
network_name_str INTA Digital (INTA)
spelling Evaluation of the agricultural production systems simulator simulating Lucerne and annual ryegrass dry matter yield in the Argentine Pampas and south-eastern AustraliaOjeda, Jonathan JesusPembleton, Keith G.Islam, Md. RafiqulAgnusdei, Monica GracielaGarcia, Sergio CarlosMedicago SativaLolium MultiflorumContenido de Materia SecaRendimientoProducciónDry Matter ContentYieldsProductionRegión PampeanaAlfalfaRaigras AnualModelling plant growth provides a tool for evaluating interactions between environment and management of forage crops for pasture-based livestock systems. Consequently, biophysical and farm systems models are becoming important tools for studying production systems that are based on forage crops. The Agricultural Production Systems Simulator (APSIM) is a model with the potential to compare the growth of annual forage crops and perennial pastures. However, information is limited about how accurately the Lucerne and Weed modules represent the growth and development of forage crops and pastures under different managements, soil types and environments in South America. This study evaluated the capacity of APSIM to simulate the growth rates and predict the dry matter (DM) yield of Lucerne (Medicago sativa L.) and annual ryegrass (Lolium multiflorum Lam.) in contrasting climatic regions of Argentina. In addition, at several Australian locations, DM yields of both crops were simulated to ensure that possible changes to the model not interfere with the robust APSIM performance that was already shown in south-eastern Australia. Initial simulations for Lucerne and ryegrass were made with original Lucerne and Weed modules of APSIM, respectively. Simulated DM yield was then compared with field data collected from the same crops growning five locations in the Argentine Pampas and seven locations in south-eastern Australia over 5 of years. APSIM predicted DM yield of Lucerne at each harvest with reasonable accuracy [0.59, 0.77 and 0.77 for R2, correlation coefficient and concordance correlation coefficient (CCC), respectively]. However, these statistics improved when the DM yield was analysed by annual accumulation,with values of 0.87, 0.93 and 0.92 for R2, correlation coefficient and CCC, respectively. APSIM, generally, over-predicted DM yield of annual ryegrass at the first harvest. Nonetheless, when the Weed module was modified through changes in phenology and transpiration efficiency, performance improved (values of 0.89, 0.94 and 0.93 for R2, correlation coefficient and CCC, respectively). This study showed that annual DM yield of Lucerne can be successfully modelled by the APSIM Lucerne module without any modifications, using a crop modelling approach. However, successfully modelling of Lucerne DM yield by harvest will require further development of the model. Moreover, modification of model parameters associated with phenology and transpiration was required to enable the Weed module of APSIM simulate growth and yield of annual ryegrass in a range of geographic locations within the Argentine PampasEEA BalcarceFil: Ojeda, Jonathan Jesus. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; ArgentinaFil: Pembleton, Keith G. University of Tasmania. Tasmanian Institute of Agriculture; Australia. University of Southern Queensland. Institute for Agriculture and the Environment; AustraliaFil: Islam, M.R. University of Sydney. Faculty of Veterinary Science. Dairy Science Group; AustraliaFil: Agnusdei, Monica Graciela. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; ArgentinaFil: Garcia, Sergio Carlos. University of Sydney. Faculty of Veterinary Science. Dairy Science Group; Australia2017-09-21T11:52:43Z2017-09-21T11:52:43Z2016info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/1279http://www.sciencedirect.com/science/article/pii/S0308521X153006390308-521Xhttps://doi.org/10.1016/j.agsy.2015.12.005Agricultural systems 143 : 61-75. (March 2016)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología AgropecuariaengArgentina (nation)Australia (nation)info:eu-repo/semantics/restrictedAccess2025-10-23T11:16:23Zoai:localhost:20.500.12123/1279instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-10-23 11:16:23.755INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Evaluation of the agricultural production systems simulator simulating Lucerne and annual ryegrass dry matter yield in the Argentine Pampas and south-eastern Australia
title Evaluation of the agricultural production systems simulator simulating Lucerne and annual ryegrass dry matter yield in the Argentine Pampas and south-eastern Australia
spellingShingle Evaluation of the agricultural production systems simulator simulating Lucerne and annual ryegrass dry matter yield in the Argentine Pampas and south-eastern Australia
Ojeda, Jonathan Jesus
Medicago Sativa
Lolium Multiflorum
Contenido de Materia Seca
Rendimiento
Producción
Dry Matter Content
Yields
Production
Región Pampeana
Alfalfa
Raigras Anual
title_short Evaluation of the agricultural production systems simulator simulating Lucerne and annual ryegrass dry matter yield in the Argentine Pampas and south-eastern Australia
title_full Evaluation of the agricultural production systems simulator simulating Lucerne and annual ryegrass dry matter yield in the Argentine Pampas and south-eastern Australia
title_fullStr Evaluation of the agricultural production systems simulator simulating Lucerne and annual ryegrass dry matter yield in the Argentine Pampas and south-eastern Australia
title_full_unstemmed Evaluation of the agricultural production systems simulator simulating Lucerne and annual ryegrass dry matter yield in the Argentine Pampas and south-eastern Australia
title_sort Evaluation of the agricultural production systems simulator simulating Lucerne and annual ryegrass dry matter yield in the Argentine Pampas and south-eastern Australia
dc.creator.none.fl_str_mv Ojeda, Jonathan Jesus
Pembleton, Keith G.
Islam, Md. Rafiqul
Agnusdei, Monica Graciela
Garcia, Sergio Carlos
author Ojeda, Jonathan Jesus
author_facet Ojeda, Jonathan Jesus
Pembleton, Keith G.
Islam, Md. Rafiqul
Agnusdei, Monica Graciela
Garcia, Sergio Carlos
author_role author
author2 Pembleton, Keith G.
Islam, Md. Rafiqul
Agnusdei, Monica Graciela
Garcia, Sergio Carlos
author2_role author
author
author
author
dc.subject.none.fl_str_mv Medicago Sativa
Lolium Multiflorum
Contenido de Materia Seca
Rendimiento
Producción
Dry Matter Content
Yields
Production
Región Pampeana
Alfalfa
Raigras Anual
topic Medicago Sativa
Lolium Multiflorum
Contenido de Materia Seca
Rendimiento
Producción
Dry Matter Content
Yields
Production
Región Pampeana
Alfalfa
Raigras Anual
dc.description.none.fl_txt_mv Modelling plant growth provides a tool for evaluating interactions between environment and management of forage crops for pasture-based livestock systems. Consequently, biophysical and farm systems models are becoming important tools for studying production systems that are based on forage crops. The Agricultural Production Systems Simulator (APSIM) is a model with the potential to compare the growth of annual forage crops and perennial pastures. However, information is limited about how accurately the Lucerne and Weed modules represent the growth and development of forage crops and pastures under different managements, soil types and environments in South America. This study evaluated the capacity of APSIM to simulate the growth rates and predict the dry matter (DM) yield of Lucerne (Medicago sativa L.) and annual ryegrass (Lolium multiflorum Lam.) in contrasting climatic regions of Argentina. In addition, at several Australian locations, DM yields of both crops were simulated to ensure that possible changes to the model not interfere with the robust APSIM performance that was already shown in south-eastern Australia. Initial simulations for Lucerne and ryegrass were made with original Lucerne and Weed modules of APSIM, respectively. Simulated DM yield was then compared with field data collected from the same crops growning five locations in the Argentine Pampas and seven locations in south-eastern Australia over 5 of years. APSIM predicted DM yield of Lucerne at each harvest with reasonable accuracy [0.59, 0.77 and 0.77 for R2, correlation coefficient and concordance correlation coefficient (CCC), respectively]. However, these statistics improved when the DM yield was analysed by annual accumulation,with values of 0.87, 0.93 and 0.92 for R2, correlation coefficient and CCC, respectively. APSIM, generally, over-predicted DM yield of annual ryegrass at the first harvest. Nonetheless, when the Weed module was modified through changes in phenology and transpiration efficiency, performance improved (values of 0.89, 0.94 and 0.93 for R2, correlation coefficient and CCC, respectively). This study showed that annual DM yield of Lucerne can be successfully modelled by the APSIM Lucerne module without any modifications, using a crop modelling approach. However, successfully modelling of Lucerne DM yield by harvest will require further development of the model. Moreover, modification of model parameters associated with phenology and transpiration was required to enable the Weed module of APSIM simulate growth and yield of annual ryegrass in a range of geographic locations within the Argentine Pampas
EEA Balcarce
Fil: Ojeda, Jonathan Jesus. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; Argentina
Fil: Pembleton, Keith G. University of Tasmania. Tasmanian Institute of Agriculture; Australia. University of Southern Queensland. Institute for Agriculture and the Environment; Australia
Fil: Islam, M.R. University of Sydney. Faculty of Veterinary Science. Dairy Science Group; Australia
Fil: Agnusdei, Monica Graciela. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fil: Garcia, Sergio Carlos. University of Sydney. Faculty of Veterinary Science. Dairy Science Group; Australia
description Modelling plant growth provides a tool for evaluating interactions between environment and management of forage crops for pasture-based livestock systems. Consequently, biophysical and farm systems models are becoming important tools for studying production systems that are based on forage crops. The Agricultural Production Systems Simulator (APSIM) is a model with the potential to compare the growth of annual forage crops and perennial pastures. However, information is limited about how accurately the Lucerne and Weed modules represent the growth and development of forage crops and pastures under different managements, soil types and environments in South America. This study evaluated the capacity of APSIM to simulate the growth rates and predict the dry matter (DM) yield of Lucerne (Medicago sativa L.) and annual ryegrass (Lolium multiflorum Lam.) in contrasting climatic regions of Argentina. In addition, at several Australian locations, DM yields of both crops were simulated to ensure that possible changes to the model not interfere with the robust APSIM performance that was already shown in south-eastern Australia. Initial simulations for Lucerne and ryegrass were made with original Lucerne and Weed modules of APSIM, respectively. Simulated DM yield was then compared with field data collected from the same crops growning five locations in the Argentine Pampas and seven locations in south-eastern Australia over 5 of years. APSIM predicted DM yield of Lucerne at each harvest with reasonable accuracy [0.59, 0.77 and 0.77 for R2, correlation coefficient and concordance correlation coefficient (CCC), respectively]. However, these statistics improved when the DM yield was analysed by annual accumulation,with values of 0.87, 0.93 and 0.92 for R2, correlation coefficient and CCC, respectively. APSIM, generally, over-predicted DM yield of annual ryegrass at the first harvest. Nonetheless, when the Weed module was modified through changes in phenology and transpiration efficiency, performance improved (values of 0.89, 0.94 and 0.93 for R2, correlation coefficient and CCC, respectively). This study showed that annual DM yield of Lucerne can be successfully modelled by the APSIM Lucerne module without any modifications, using a crop modelling approach. However, successfully modelling of Lucerne DM yield by harvest will require further development of the model. Moreover, modification of model parameters associated with phenology and transpiration was required to enable the Weed module of APSIM simulate growth and yield of annual ryegrass in a range of geographic locations within the Argentine Pampas
publishDate 2016
dc.date.none.fl_str_mv 2016
2017-09-21T11:52:43Z
2017-09-21T11:52:43Z
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12123/1279
http://www.sciencedirect.com/science/article/pii/S0308521X15300639
0308-521X
https://doi.org/10.1016/j.agsy.2015.12.005
url http://hdl.handle.net/20.500.12123/1279
http://www.sciencedirect.com/science/article/pii/S0308521X15300639
https://doi.org/10.1016/j.agsy.2015.12.005
identifier_str_mv 0308-521X
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/restrictedAccess
eu_rights_str_mv restrictedAccess
dc.format.none.fl_str_mv application/pdf
dc.coverage.none.fl_str_mv Argentina (nation)
Australia (nation)
dc.source.none.fl_str_mv Agricultural systems 143 : 61-75. (March 2016)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
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