Optimal soybean sowing window adjusted to climatic variability based on El Niño-Southern Oscillation using agrometeorological modeling
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Pesquisa Agropecuária Tropical (Online) |
Texto Completo: | https://revistas.ufg.br/pat/article/view/72428 |
Resumo: | Determining the optimal sowing window (OSW) based on climate variability associated with El Niño-Southern Oscillation (ENSO) can provide valuable information for agricultural planning in the tropics. This study aimed to calibrate, evaluate and apply the CROPGRO-Soybean model for determining the OSW across the ENSO phases for soybean-producing areas in the Pará State, northern Brazil. First, the model was calibrated and evaluated using experimental data collected in the field, between 2006 and 2009. In this process, the model estimates showed a good agreement with the observed data for soybean phenology, growth and yield, demonstrating potential to simulate the crop yield in this part of the Amazon. After calibration, the model was used in the seasonal mode to simulate 18 planting dates, over 39 years and in three locations. The simulated yields were divided into three ENSO phases. The set of sowing dates that showed a high frequency (> 80 %) of yields above 3,500 kg ha-1 integrated the OSW for each location and ENSO phases. The OSW duration differed between locations and ENSO phases, varying more during La Niña than El Niño events. However, regardless of the location or ENSO phase, late sowing was more suitable, because, besides favoring a greater frequency of good climate conditions for the development, growth and high yields, it also favors a lower risk of rainfall during the harvest period. KEYWORDS: Glycine max, CROPGRO-Soybean model, climate risk mitigation. |
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Optimal soybean sowing window adjusted to climatic variability based on El Niño-Southern Oscillation using agrometeorological modelingJanela ótima de semeadura da soja ajustada à variabilidade climática baseada em El Niño-Oscilação Sul utilizando-se modelagem agrometeorológicaDetermining the optimal sowing window (OSW) based on climate variability associated with El Niño-Southern Oscillation (ENSO) can provide valuable information for agricultural planning in the tropics. This study aimed to calibrate, evaluate and apply the CROPGRO-Soybean model for determining the OSW across the ENSO phases for soybean-producing areas in the Pará State, northern Brazil. First, the model was calibrated and evaluated using experimental data collected in the field, between 2006 and 2009. In this process, the model estimates showed a good agreement with the observed data for soybean phenology, growth and yield, demonstrating potential to simulate the crop yield in this part of the Amazon. After calibration, the model was used in the seasonal mode to simulate 18 planting dates, over 39 years and in three locations. The simulated yields were divided into three ENSO phases. The set of sowing dates that showed a high frequency (> 80 %) of yields above 3,500 kg ha-1 integrated the OSW for each location and ENSO phases. The OSW duration differed between locations and ENSO phases, varying more during La Niña than El Niño events. However, regardless of the location or ENSO phase, late sowing was more suitable, because, besides favoring a greater frequency of good climate conditions for the development, growth and high yields, it also favors a lower risk of rainfall during the harvest period. KEYWORDS: Glycine max, CROPGRO-Soybean model, climate risk mitigation. A determinação da janela ótima de semeadura (JOS), de acordo com a variabilidade climática associada ao El Niño-Oscilação Sul (ENOS), pode fornecer informações valiosas para o planejamento agrícola nos trópicos. Objetivou-se calibrar, avaliar e aplicar o modelo CROPGRO-Soybean na determinação da JOS nas fases de ENOS para áreas produtoras de soja no estado do Pará. Primeiramente, o modelo foi calibrado e avaliado a partir de dados experimentais coletados em campo, entre 2006 e 2009. Nesse processo, as estimativas do modelo mostraram boa concordância com os dados observados para fenologia, crescimento e produtividade da soja, demonstrando potencial para simular o rendimento da cultura nessa parte da Amazônia. Após a calibração, o modelo foi utilizado no modo sazonal, para simular 18 datas de semeadura, em 33 anos e três locais. Os rendimentos simulados foram separados de acordo com três fases ENOS. O conjunto de datas de semeadura que apresentou alta frequência (> 80 %) de rendimentos acima de 3.500 kg ha-1 integrou a JOS para cada local e fase ENOS. A duração da JOS foi diferente entre os locais e fases ENOS, variando mais durante eventos de La Niña do que de El Niño. No entanto, independentemente do local ou da fase ENOS, a semeadura tardia foi mais indicada, pois, além de favorecer uma maior frequência de boas condições climáticas para o desenvolvimento, crescimento e altas produtividades, também favorece um menor risco de chuvas durante o período de colheita. PALAVRAS-CHAVES: Glycine max, modelo CROPGRO-Soybean, mitigação de riscos climáticos.Escola de Agronomia - Universidade Federal de Goiás2022-07-13info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistas.ufg.br/pat/article/view/72428Pesquisa Agropecuária Tropical [Agricultural Research in the Tropics]; Vol. 52 (2022); e72428Pesquisa Agropecuária Tropical (Agricultural Research in the Tropics); Vol. 52 (2022); e72428Pesquisa Agropecuária Tropical; v. 52 (2022); e724281983-4063reponame:Pesquisa Agropecuária Tropical (Online)instname:Universidade Federal de Goiás (UFG)instacron:UFGenghttps://revistas.ufg.br/pat/article/view/72428/38488Copyright (c) 2022 Pesquisa Agropecuária Tropicalinfo:eu-repo/semantics/openAccessLima, Marcus José Alves deNunes, Hildo Giuseppe Garcia Caldas Sampaio , Leila Sobral Souza , Paulo Jorge de Oliveira Ponte de Fraisse , Clyde William 2022-07-13T11:25:20Zoai:ojs.revistas.ufg.br:article/72428Revistahttps://revistas.ufg.br/patPUBhttps://revistas.ufg.br/pat/oaiaseleguini.pat@gmail.com||mgoes@agro.ufg.br1983-40631517-6398opendoar:2024-05-21T19:56:35.918376Pesquisa Agropecuária Tropical (Online) - Universidade Federal de Goiás (UFG)true |
dc.title.none.fl_str_mv |
Optimal soybean sowing window adjusted to climatic variability based on El Niño-Southern Oscillation using agrometeorological modeling Janela ótima de semeadura da soja ajustada à variabilidade climática baseada em El Niño-Oscilação Sul utilizando-se modelagem agrometeorológica |
title |
Optimal soybean sowing window adjusted to climatic variability based on El Niño-Southern Oscillation using agrometeorological modeling |
spellingShingle |
Optimal soybean sowing window adjusted to climatic variability based on El Niño-Southern Oscillation using agrometeorological modeling Lima, Marcus José Alves de |
title_short |
Optimal soybean sowing window adjusted to climatic variability based on El Niño-Southern Oscillation using agrometeorological modeling |
title_full |
Optimal soybean sowing window adjusted to climatic variability based on El Niño-Southern Oscillation using agrometeorological modeling |
title_fullStr |
Optimal soybean sowing window adjusted to climatic variability based on El Niño-Southern Oscillation using agrometeorological modeling |
title_full_unstemmed |
Optimal soybean sowing window adjusted to climatic variability based on El Niño-Southern Oscillation using agrometeorological modeling |
title_sort |
Optimal soybean sowing window adjusted to climatic variability based on El Niño-Southern Oscillation using agrometeorological modeling |
author |
Lima, Marcus José Alves de |
author_facet |
Lima, Marcus José Alves de Nunes, Hildo Giuseppe Garcia Caldas Sampaio , Leila Sobral Souza , Paulo Jorge de Oliveira Ponte de Fraisse , Clyde William |
author_role |
author |
author2 |
Nunes, Hildo Giuseppe Garcia Caldas Sampaio , Leila Sobral Souza , Paulo Jorge de Oliveira Ponte de Fraisse , Clyde William |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Lima, Marcus José Alves de Nunes, Hildo Giuseppe Garcia Caldas Sampaio , Leila Sobral Souza , Paulo Jorge de Oliveira Ponte de Fraisse , Clyde William |
description |
Determining the optimal sowing window (OSW) based on climate variability associated with El Niño-Southern Oscillation (ENSO) can provide valuable information for agricultural planning in the tropics. This study aimed to calibrate, evaluate and apply the CROPGRO-Soybean model for determining the OSW across the ENSO phases for soybean-producing areas in the Pará State, northern Brazil. First, the model was calibrated and evaluated using experimental data collected in the field, between 2006 and 2009. In this process, the model estimates showed a good agreement with the observed data for soybean phenology, growth and yield, demonstrating potential to simulate the crop yield in this part of the Amazon. After calibration, the model was used in the seasonal mode to simulate 18 planting dates, over 39 years and in three locations. The simulated yields were divided into three ENSO phases. The set of sowing dates that showed a high frequency (> 80 %) of yields above 3,500 kg ha-1 integrated the OSW for each location and ENSO phases. The OSW duration differed between locations and ENSO phases, varying more during La Niña than El Niño events. However, regardless of the location or ENSO phase, late sowing was more suitable, because, besides favoring a greater frequency of good climate conditions for the development, growth and high yields, it also favors a lower risk of rainfall during the harvest period. KEYWORDS: Glycine max, CROPGRO-Soybean model, climate risk mitigation. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-07-13 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://revistas.ufg.br/pat/article/view/72428 |
url |
https://revistas.ufg.br/pat/article/view/72428 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://revistas.ufg.br/pat/article/view/72428/38488 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2022 Pesquisa Agropecuária Tropical info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2022 Pesquisa Agropecuária Tropical |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Escola de Agronomia - Universidade Federal de Goiás |
publisher.none.fl_str_mv |
Escola de Agronomia - Universidade Federal de Goiás |
dc.source.none.fl_str_mv |
Pesquisa Agropecuária Tropical [Agricultural Research in the Tropics]; Vol. 52 (2022); e72428 Pesquisa Agropecuária Tropical (Agricultural Research in the Tropics); Vol. 52 (2022); e72428 Pesquisa Agropecuária Tropical; v. 52 (2022); e72428 1983-4063 reponame:Pesquisa Agropecuária Tropical (Online) instname:Universidade Federal de Goiás (UFG) instacron:UFG |
instname_str |
Universidade Federal de Goiás (UFG) |
instacron_str |
UFG |
institution |
UFG |
reponame_str |
Pesquisa Agropecuária Tropical (Online) |
collection |
Pesquisa Agropecuária Tropical (Online) |
repository.name.fl_str_mv |
Pesquisa Agropecuária Tropical (Online) - Universidade Federal de Goiás (UFG) |
repository.mail.fl_str_mv |
aseleguini.pat@gmail.com||mgoes@agro.ufg.br |
_version_ |
1799874821466619904 |