Optimal soybean sowing window adjusted to climatic variability based on El Niño-Southern Oscillation using agrometeorological modeling
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 mo...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Universidade Federal de Goiás
2022-07-01
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| Series: | Pesquisa Agropecuária Tropical |
| Subjects: | |
| Online Access: | https://revistas.ufg.br/pat/article/view/72428/38488 |
| _version_ | 1811292264609087488 |
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| author | Marcus José Alves de Lima Hildo Giuseppe Garcia Caldas Nunes Leila Sobral Sampaio Paulo Jorge de Oliveira Ponte de Souza Clyde William Fraisse |
| author_facet | Marcus José Alves de Lima Hildo Giuseppe Garcia Caldas Nunes Leila Sobral Sampaio Paulo Jorge de Oliveira Ponte de Souza Clyde William Fraisse |
| author_sort | Marcus José Alves de Lima |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-13T04:42:49Z |
| format | Article |
| id | doaj.art-e642b5a437a6451c9b5f382d23113848 |
| institution | Directory Open Access Journal |
| issn | 1983-4063 |
| language | English |
| last_indexed | 2024-04-13T04:42:49Z |
| publishDate | 2022-07-01 |
| publisher | Universidade Federal de Goiás |
| record_format | Article |
| series | Pesquisa Agropecuária Tropical |
| spelling | doaj.art-e642b5a437a6451c9b5f382d231138482022-12-22T03:01:57ZengUniversidade Federal de GoiásPesquisa Agropecuária Tropical1983-40632022-07-0152e7242810.1590/1983-40632022v5272428Optimal soybean sowing window adjusted to climatic variability based on El Niño-Southern Oscillation using agrometeorological modelingMarcus José Alves de LimaHildo Giuseppe Garcia Caldas NunesLeila Sobral SampaioPaulo Jorge de Oliveira Ponte de SouzaClyde William FraisseDetermining 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.https://revistas.ufg.br/pat/article/view/72428/38488glycine maxcropgro-soybean modelclimate risk mitigation |
| spellingShingle | Marcus José Alves de Lima Hildo Giuseppe Garcia Caldas Nunes Leila Sobral Sampaio Paulo Jorge de Oliveira Ponte de Souza Clyde William Fraisse Optimal soybean sowing window adjusted to climatic variability based on El Niño-Southern Oscillation using agrometeorological modeling Pesquisa Agropecuária Tropical glycine max cropgro-soybean model climate risk mitigation |
| title | 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_short | 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 nino southern oscillation using agrometeorological modeling |
| topic | glycine max cropgro-soybean model climate risk mitigation |
| url | https://revistas.ufg.br/pat/article/view/72428/38488 |
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