By Shawn P. Conley
The U.S. is a major soybean producing country that supplies 34% of global annual soybean production. Most U.S. soybean-producing regions are rainfed, and thus are highly vulnerable to extreme weather events. Drought and elevated air temperatures, now more increasingly frequent due to climate change, are important constraints in crop production across major agricultural areas globally. Thus, the challenge to increase crop yields to meet future demand can be achieved by increasing the rate at which climate change adaptation practices are identified and adopted.
Vapor pressure deficit (Vpd) is a measure of atmospheric water demand with a strong influence on plant transpiratory water loss (Lobell et al., 2013). Increasing Vpd values are generally associated with drought and heat. Improved genetic traits and crop management strategies could help mitigate the projected negative impacts of climate change on crop yields. For example, drought-tolerant traits, introduced through conventional breeding, resulted in soybean transpiration rates that plateaued at Vpd levels above 1.4-2.1 kPa (Devi et al., 2014). Crop management strategies, such as earlier-than-typical planting, has also been proposed as a strategy to increase yields in regional studies (Rattalino Edreira et al., 2017). However, soybean exhibits different sensitivities to weather during varied developmental stages (Purcell and Specht, 2004), and therefore, the sensitivity of a crop to climate adaptation strategies and their effectiveness in mitigating drought-induced yield reduction remains unclear.
An important step towards adapting to climate change and mitigating its impact on yield is accurate identification of the weather conditions that most affect crop yield. As has been reported earlier, one option is planting date adjustment. Regional trials have shown the benefits of earlier planting (Rattalino Edreira et al., 2017); however, there is a limit to how much the regional field trials can extrapolate results. Our objective was to examine crop sensitivity to varying in-season weather conditions and to model optimal planting dates and associated yield and monetary benefits due to planting date adjustment across the U.S. To date, there is no similar previous work.