Parameterization of CROPGRO-soybean model and its use as a tool to assess the impact of climate change on the soybean crop

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Prior to their use in decision-making, crop models need to be calibrated with field data from the region where the model will be used. The objectives of this research were calibrate and validate the predictive ability of CROPGRO-soybean model. Data from two cultivars maturity group IV (Asgrow 4656 a...

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Autores principales: Confalone, Adriana, Lázaro, Laura, Vilatte, Carlos, Roca, Núria, Mestelan, Silvia, Aguas, Laura, Navarro, Miguel, Sau, Federico
Formato: Artículo revista
Lenguaje:Español
Publicado: Facultad de Ciencias Agrarias-UNCuyo 2016
Materias:
cambio climático
modelo de cultivo
rendimiento
soja
climate change
crop model
yield
soybean
Acceso en línea:https://revistas.uncu.edu.ar/ojs3/index.php/RFCA/article/view/3220
Aporte de:
Revista de la Facultad de Ciencias Agrarias UNCuyo de Universidad Nacional de Cuyo
id I11-R107article-3220
record_format ojs
institution Universidad Nacional de Cuyo
institution_str I-11
repository_str R-107
container_title_str Revista de la Facultad de Ciencias Agrarias UNCuyo
language Español
format Artículo revista
topic cambio climático
modelo de cultivo
rendimiento
soja
climate change
crop model
yield
soybean
spellingShingle cambio climático
modelo de cultivo
rendimiento
soja
climate change
crop model
yield
soybean
Confalone, Adriana
Lázaro, Laura
Vilatte, Carlos
Roca, Núria
Mestelan, Silvia
Aguas, Laura
Navarro, Miguel
Sau, Federico
Parameterization of CROPGRO-soybean model and its use as a tool to assess the impact of climate change on the soybean crop
topic_facet cambio climático
modelo de cultivo
rendimiento
soja
climate change
crop model
yield
soybean
author Confalone, Adriana
Lázaro, Laura
Vilatte, Carlos
Roca, Núria
Mestelan, Silvia
Aguas, Laura
Navarro, Miguel
Sau, Federico
author_facet Confalone, Adriana
Lázaro, Laura
Vilatte, Carlos
Roca, Núria
Mestelan, Silvia
Aguas, Laura
Navarro, Miguel
Sau, Federico
author_sort Confalone, Adriana
title Parameterization of CROPGRO-soybean model and its use as a tool to assess the impact of climate change on the soybean crop
title_short Parameterization of CROPGRO-soybean model and its use as a tool to assess the impact of climate change on the soybean crop
title_full Parameterization of CROPGRO-soybean model and its use as a tool to assess the impact of climate change on the soybean crop
title_fullStr Parameterization of CROPGRO-soybean model and its use as a tool to assess the impact of climate change on the soybean crop
title_full_unstemmed Parameterization of CROPGRO-soybean model and its use as a tool to assess the impact of climate change on the soybean crop
title_sort parameterization of cropgro-soybean model and its use as a tool to assess the impact of climate change on the soybean crop
description Prior to their use in decision-making, crop models need to be calibrated with field data from the region where the model will be used. The objectives of this research were calibrate and validate the predictive ability of CROPGRO-soybean model. Data from two cultivars maturity group IV (Asgrow 4656 and Don Mario DM4700) and three years of field experiments in conditions not limiting in Azul, Buenos Aires, Argentina were used. Calibration started with the coefficients of group IV that by default are in files: species, ecotype and cultivate. With the original species file, dry matter, increasing the number of pods and growth were underestimated. Minor changes in file were made to adjust phenology and growth dynamics for both cultivars. The cardinal base temperatures for photosynthesis and pod formation were reduced; with these modifications good predictions for growth and yield were obtained. With the CROPGRO-soybean calibrated and using projections for the region from PRECIS regional climate model under the SRESA2 scenario in the years 2030 and 2060, the effects of global climate change in future soybean crop yield were evaluated. Under these scenarios and rainfed conditions, are anticipated yield increases of 34 and 38% for each of the years studied with a slight improvement delaying the planting date, respect to current optimum date.
publisher Facultad de Ciencias Agrarias-UNCuyo
publishDate 2016
url https://revistas.uncu.edu.ar/ojs3/index.php/RFCA/article/view/3220
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first_indexed 2022-06-20T13:52:55Z
last_indexed 2022-06-20T13:52:55Z
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