Soybean yield in the Matopiba region under climate changes
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista Brasileira de Engenharia Agrícola e Ambiental (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662020000100008 |
Resumo: | ABSTRACT The climatic conditions along the cycle are the main factors responsible for the final production of any crop. This study aimed to evaluate the current conditions and the effects of climate change scenarios on the yield of soybean grown in the Matopiba region, located between the states of Tocantins, south and northeast of Maranhão, south of Piauí and west of Bahia, Brazil. The AquaCrop model of FAO, version 5.0, was calibrated with data of 2014 and validated with those of 2016, using climate, soil and crop management parameters collected in two experimental campaigns conducted between June and October in 2014 and 2016 in Palmas, TO, Brazil. The performance of the model was evaluated using the following statistical indicators: prediction error (PE), coefficient of determination (R2), normalized root mean square error (NRMSE), Nash-Sutcliffe model efficiency coefficient (EF) and Willmott’s index of agreement (d). It was verified that the AquaCrop model underestimates soybean grain yield under severe water stress conditions throughout the growing cycle. The increase in CO2 concentration and in the air temperature, projected by the climate models HadGEM2-ES and MIROC5 under the scenario of stabilization (RCP 4.5) and the scenario of progression (RCP 8.5), have contributed to the increase in soybean yield by the end of this century. |
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Soybean yield in the Matopiba region under climate changesGlycine maxyieldAquaCrop modelclimate variabilityABSTRACT The climatic conditions along the cycle are the main factors responsible for the final production of any crop. This study aimed to evaluate the current conditions and the effects of climate change scenarios on the yield of soybean grown in the Matopiba region, located between the states of Tocantins, south and northeast of Maranhão, south of Piauí and west of Bahia, Brazil. The AquaCrop model of FAO, version 5.0, was calibrated with data of 2014 and validated with those of 2016, using climate, soil and crop management parameters collected in two experimental campaigns conducted between June and October in 2014 and 2016 in Palmas, TO, Brazil. The performance of the model was evaluated using the following statistical indicators: prediction error (PE), coefficient of determination (R2), normalized root mean square error (NRMSE), Nash-Sutcliffe model efficiency coefficient (EF) and Willmott’s index of agreement (d). It was verified that the AquaCrop model underestimates soybean grain yield under severe water stress conditions throughout the growing cycle. The increase in CO2 concentration and in the air temperature, projected by the climate models HadGEM2-ES and MIROC5 under the scenario of stabilization (RCP 4.5) and the scenario of progression (RCP 8.5), have contributed to the increase in soybean yield by the end of this century.Departamento de Engenharia Agrícola - UFCG2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662020000100008Revista Brasileira de Engenharia Agrícola e Ambiental v.24 n.1 2020reponame:Revista Brasileira de Engenharia Agrícola e Ambiental (Online)instname:Universidade Federal de Campina Grande (UFCG)instacron:UFCG10.1590/1807-1929/agriambi.v24n1p8-14info:eu-repo/semantics/openAccessSilva,Vicente de P. R. daSilva,Roberta A. eMaciel,Girlene F.Souza,Enio P. deBraga,Célia C.Holanda,Romildo M. deeng2019-12-04T00:00:00Zoai:scielo:S1415-43662020000100008Revistahttp://www.scielo.br/rbeaaPUBhttps://old.scielo.br/oai/scielo-oai.php||agriambi@agriambi.com.br1807-19291415-4366opendoar:2019-12-04T00:00Revista Brasileira de Engenharia Agrícola e Ambiental (Online) - Universidade Federal de Campina Grande (UFCG)false |
dc.title.none.fl_str_mv |
Soybean yield in the Matopiba region under climate changes |
title |
Soybean yield in the Matopiba region under climate changes |
spellingShingle |
Soybean yield in the Matopiba region under climate changes Silva,Vicente de P. R. da Glycine max yield AquaCrop model climate variability |
title_short |
Soybean yield in the Matopiba region under climate changes |
title_full |
Soybean yield in the Matopiba region under climate changes |
title_fullStr |
Soybean yield in the Matopiba region under climate changes |
title_full_unstemmed |
Soybean yield in the Matopiba region under climate changes |
title_sort |
Soybean yield in the Matopiba region under climate changes |
author |
Silva,Vicente de P. R. da |
author_facet |
Silva,Vicente de P. R. da Silva,Roberta A. e Maciel,Girlene F. Souza,Enio P. de Braga,Célia C. Holanda,Romildo M. de |
author_role |
author |
author2 |
Silva,Roberta A. e Maciel,Girlene F. Souza,Enio P. de Braga,Célia C. Holanda,Romildo M. de |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Silva,Vicente de P. R. da Silva,Roberta A. e Maciel,Girlene F. Souza,Enio P. de Braga,Célia C. Holanda,Romildo M. de |
dc.subject.por.fl_str_mv |
Glycine max yield AquaCrop model climate variability |
topic |
Glycine max yield AquaCrop model climate variability |
description |
ABSTRACT The climatic conditions along the cycle are the main factors responsible for the final production of any crop. This study aimed to evaluate the current conditions and the effects of climate change scenarios on the yield of soybean grown in the Matopiba region, located between the states of Tocantins, south and northeast of Maranhão, south of Piauí and west of Bahia, Brazil. The AquaCrop model of FAO, version 5.0, was calibrated with data of 2014 and validated with those of 2016, using climate, soil and crop management parameters collected in two experimental campaigns conducted between June and October in 2014 and 2016 in Palmas, TO, Brazil. The performance of the model was evaluated using the following statistical indicators: prediction error (PE), coefficient of determination (R2), normalized root mean square error (NRMSE), Nash-Sutcliffe model efficiency coefficient (EF) and Willmott’s index of agreement (d). It was verified that the AquaCrop model underestimates soybean grain yield under severe water stress conditions throughout the growing cycle. The increase in CO2 concentration and in the air temperature, projected by the climate models HadGEM2-ES and MIROC5 under the scenario of stabilization (RCP 4.5) and the scenario of progression (RCP 8.5), have contributed to the increase in soybean yield by the end of this century. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662020000100008 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662020000100008 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1807-1929/agriambi.v24n1p8-14 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Departamento de Engenharia Agrícola - UFCG |
publisher.none.fl_str_mv |
Departamento de Engenharia Agrícola - UFCG |
dc.source.none.fl_str_mv |
Revista Brasileira de Engenharia Agrícola e Ambiental v.24 n.1 2020 reponame:Revista Brasileira de Engenharia Agrícola e Ambiental (Online) instname:Universidade Federal de Campina Grande (UFCG) instacron:UFCG |
instname_str |
Universidade Federal de Campina Grande (UFCG) |
instacron_str |
UFCG |
institution |
UFCG |
reponame_str |
Revista Brasileira de Engenharia Agrícola e Ambiental (Online) |
collection |
Revista Brasileira de Engenharia Agrícola e Ambiental (Online) |
repository.name.fl_str_mv |
Revista Brasileira de Engenharia Agrícola e Ambiental (Online) - Universidade Federal de Campina Grande (UFCG) |
repository.mail.fl_str_mv |
||agriambi@agriambi.com.br |
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1750297687007166464 |