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

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. Th...

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Main Authors: Ojeda, Jonathan Jesus, Pembleton, Keith G., Islam, Md. Rafiqul, Agnusdei, Monica Graciela, Garcia, Sergio Carlos
Format: info:ar-repo/semantics/artículo
Language:Inglés
Published: 2017
Subjects:
Online Access: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
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author Ojeda, Jonathan Jesus
Pembleton, Keith G.
Islam, Md. Rafiqul
Agnusdei, Monica Graciela
Garcia, Sergio Carlos
author_browse Agnusdei, Monica Graciela
Garcia, Sergio Carlos
Islam, Md. Rafiqul
Ojeda, Jonathan Jesus
Pembleton, Keith G.
author_facet Ojeda, Jonathan Jesus
Pembleton, Keith G.
Islam, Md. Rafiqul
Agnusdei, Monica Graciela
Garcia, Sergio Carlos
author_sort Ojeda, Jonathan Jesus
collection INTA Digital
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
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spelling INTA12792019-06-12T15:44:28Z 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 Pembleton, Keith G. Islam, Md. Rafiqul Agnusdei, Monica Graciela Garcia, Sergio Carlos Medicago Sativa Lolium Multiflorum Contenido de Materia Seca Rendimiento Producción Dry Matter Content Yields Production Región Pampeana Alfalfa Raigras Anual 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 2017-09-21T11:52:43Z 2017-09-21T11:52:43Z 2016 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion 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 eng info:eu-repo/semantics/restrictedAccess application/pdf Argentina (nation) Australia (nation) Agricultural systems 143 : 61-75. (March 2016)
spellingShingle Medicago Sativa
Lolium Multiflorum
Contenido de Materia Seca
Rendimiento
Producción
Dry Matter Content
Yields
Production
Región Pampeana
Alfalfa
Raigras Anual
Ojeda, Jonathan Jesus
Pembleton, Keith G.
Islam, Md. Rafiqul
Agnusdei, Monica Graciela
Garcia, Sergio Carlos
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
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_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_sort evaluation of the agricultural production systems simulator simulating lucerne and annual ryegrass dry matter yield in the argentine pampas and south eastern australia
topic Medicago Sativa
Lolium Multiflorum
Contenido de Materia Seca
Rendimiento
Producción
Dry Matter Content
Yields
Production
Región Pampeana
Alfalfa
Raigras Anual
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
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