With current annual production of over 110 million metric tons, US soybean [Glycine max (L.) Mer.] grain production can drop drastically due to extreme weather. The record heat and drought of 2012, a La Niña year, caused a 10% decline in national soybean yield. Inclement years are often linked to El Niño-Southern Oscillation (ENSO) phenomenon, causing drought, heavy rainfall, or extreme temperatures. Thus, management strategies to minimize impact of extreme weather events (EWE) on soybean crop growth are important for the sustainability of farming systems. In this study, we evaluate how soybean sowing date and maturity group (MG) can mitigate the effects of ENSO on yield variability in the Southeastern US. A calibrated DSSAT-CROPGRO-Soybean crop model for three MGs (5.6, 6.1, and 7.0) was used to simulate yield and quantify the occurrence of extreme weather events (EWE) during vegetative and reproductive soybean stages. Historical (36 years, between 1984 and 2019) soybean yield simulations were conducted using ten different sowing dates ranging from April to early August, at eight locations across the Southeastern US. Additionally, data analyses were performed using principal component analysis to understand the major factors of soybean yield variability in this region and which management conditions could reduce the impact of EWE. Our results showed that soybean yield variability could be minimized through the adjustment of sowing dates according to ENSO phases that also impact the occurrence of EWE during reproductive and vegetative stages in this region.

目前年产量超过 1.1 亿吨，美国大豆 [ Glycinemax (L.) Mer.] 谷物产量会因极端天气而急剧下降。2012 年是拉尼娜年，创纪录的高温和干旱导致全国大豆产量下降 10%。恶劣年份通常与厄尔尼诺-南方涛动 (ENSO) 现象有关，会导致干旱、暴雨或极端温度。因此，尽量减少极端天气事件 (EWE) 对大豆作物生长的影响的管理策略对于农业系统的可持续性非常重要。在本研究中，我们评估了大豆播种日期和成熟度组 (MG) 如何减轻 ENSO 对美国东南部产量变异性的影响。使用三个 MG（5.6、6.1 和 7.0）的校准 DSSAT-CROPGRO-大豆作物模型来模拟产量和量化大豆营养和生殖阶段极端天气事件 (EWE) 的发生。历史（36 年，1984 年至 2019 年）大豆产量模拟是在美国东南部的八个地点使用从 4 月到 8 月初的十个不同播种日期进行的。此外，使用主成分分析进行数据分析，以了解该地区大豆产量变化的主要因素以及哪些管理条件可以减少 EWE 的影响。我们的研究结果表明，通过根据 ENSO 阶段调整播种日期可以最小化大豆产量变异性，这也会影响该地区生殖和营养阶段 EWE 的发生。使用主成分分析进行数据分析，以了解该地区大豆产量变化的主要因素以及哪些管理条件可以减少 EWE 的影响。我们的研究结果表明，通过根据 ENSO 阶段调整播种日期可以最小化大豆产量变异性，这也会影响该地区生殖和营养阶段 EWE 的发生。使用主成分分析进行数据分析，以了解该地区大豆产量变化的主要因素以及哪些管理条件可以减少 EWE 的影响。我们的研究结果表明，通过根据 ENSO 阶段调整播种日期可以最小化大豆产量变异性，这也会影响该地区生殖和营养阶段 EWE 的发生。