Soybean maturity groups and sowing dates to minimize ENSO and extreme weather events effects on yield variability in the Southeastern US

• Published in: Agricultural and forest meteorology Vol. 324; p. 109104
• Main Authors: Perondi, Daniel, de Souza Nóia Júnior, Rogério, Zotarelli, Lincoln, Mulvaney, Michael J., Fraisse, Clyde W.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15-09-2022
• Subjects: Climate variability; Crop simulation model; DSSAT; El niño-southern oscillation; Glycine max; Crop simulation model; DSSAT; Climate variability; Glycine max; El niño-southern oscillation
• ISSN: 0168-1923; 1873-2240
• DOI: 10.1016/j.agrformet.2022.109104

•ENSO affected the occurrence of extreme weather events during soybean growing seasons.•Sowing date adjustments can minimize or maximize ENSO effects on soybean grain yield.•Soybean maturity groups and sowing dates can affect the exposure to extreme weather events.
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.