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ARS Home » Southeast Area » Stoneville, Mississippi » Sustainable Water Management Research » Research » Publications at this Location » Publication #399247

Research Project: Development of Best Management Practices, Tools, and Technologies to Optimize Water Use Efficiency and Improve Water Distribution in the Lower Mississippi River Basin

Location: Sustainable Water Management Research

Title: Nonlinear and marginal contributions of surface solar brightening to US maize yield gains

Author
item ZHAO, HAIDONG - Kansas State University
item YANG, HAISHUN - University Of Nebraska
item KLUITENBERG, GERARD - Kansas State University
item AVENSON, TOM - Kansas State University
item SASSENRATH, GRETCHEN - Kansas State University
item KIRKHAM, MARY BETH - Kansas State University
item ZHANG, L - Kansas State University
item WAN, NENGHAN - Kansas State University
item Nelson, Amanda
item Gowda, Prasanna
item LIN, XIAOMAO - Kansas State University

Submitted to: Agricultural and Forest Meteorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/17/2024
Publication Date: N/A
Citation: N/A

Interpretive Summary: Increasing total incident solar radiation (or amount of solar radiation energy received on a given surface during a given time) and improving the conversion efficiency of solar radiation to biomass by crops during the growing season are two ways to improve crop productivity. Previous work suggests that surface solar radiation (SSR) during corn grain-filling period contributes 27% to US corn yield gains in the US, where 24% is contributed to direct solar effect, with the remainder of yield improvements reportedly due to an interaction between solar brightening and technology. However, these conclusions are not supported by current models such as the 'process-based Hybrid-Maize Model' (HMM) simulations, nor were the trends in agreement with ground-based SSR observations from automated weather station (AWS) networks, indicating these values are overestimations. Researchers therefore set out to study the ability of HMM to simulate maize development and growth and AWS to calibrate and validate the model and found that that SSR contributed 10.6% to yield gains averaged from the four corn states, rather than the 27% found in the other method. These results have implications for meeting food production challenges for a growing population under changing weather conditions.

Technical Abstract: As global climate changes, meeting food security for the growing global population requires improving crop productivity. Two ways to do this are to increase total incident solar radiation during the growing season and to improve the conversion efficiency of solar radiation received by plants into biomass. With respect to these approaches, Tollenaar et al. analyzed solar brightening contributions to US maize yield gains from 1984 to 2013. They concluded that surface solar radiation (SSR) brightening during the maize grain-filling period (SSRGFP) contributed 27% to the US maize yield gains, based on ten US corn-producing states, where 24% was due to a direct effect (that is, solar brightening during the GFP) and the remainder was due to an interaction between solar brightening and technology. The trend of SSRGFP that Tollenaar et al. estimated was 6.9 W m-2 per decade (i.e., 0.06 MJ m-2 d-1 yr-1) from satellite-based solar irradiance. However, the conclusion drawn from their analysis is not supported by process-based Hybrid-Maize Model (HMM) simulations. Also, the SSRGFP trends estimated from Tollenaar et al. were not in agreement with ground-based SSR observations from automated weather station (AWS) networks. Therefore, their brightening contribution values of 27% or 24% to US maize yield gains were overestimated. This study uses HMM to simulate maize development and growth and 34 AWS stations across four US states from the mid-1980s to 2022, with high-quality SSR data, temperature, and relative humidity to calibrate and validate the model. Solar radiation was concluded to contribute 10.6% to yield gains averaged from the four corn states during the SSRGFP.