Optimal soybean sowing window adjusted to climatic variability based on El Niño-Southern Oscillation using agrometeorological modeling

Authors

  • Marcus José Alves de Lima
  • Hildo Giuseppe Garcia Caldas Nunes
  • Leila Sobral Sampaio
  • Paulo Jorge de Oliveira Ponte de Souza
  • Clyde William Fraisse

Abstract

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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Author Biography

Marcus José Alves de Lima

Agrometeorológia

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Published

2022-07-13

How to Cite

LIMA, M. J. A. de; NUNES, H. G. G. C. .; SAMPAIO , L. S. .; SOUZA , P. J. . de O. P. de .; FRAISSE , C. W. . Optimal soybean sowing window adjusted to climatic variability based on El Niño-Southern Oscillation using agrometeorological modeling. Pesquisa Agropecuária Tropical [Agricultural Research in the Tropics], Goiânia, v. 52, p. e72428, 2022. Disponível em: https://revistas.ufg.br/pat/article/view/72428. Acesso em: 17 jul. 2024.

Issue

Section

Special Supplement: Climate Change in Agriculture