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Title:Developmental and physiological responses of soybean to elevated growing temperatures
Author(s):Burroughs, Charles Harold Caldwell
Director of Research:Ainsworth, Elizabeth A
Doctoral Committee Chair(s):Ainsworth, Elizabeth A
Doctoral Committee Member(s):Bernacchi, Carl J; Lipka, Alexander E; Guan, Kaiyu
Department / Program:Plant Biology
Discipline:Plant Biology
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):soybean
heat stress
plant biology
photosynthesis
yield
Abstract:Rising temperatures have reduced soybean yields in key production regions and will have a net-negative impact on global yields. Improvements in genetics, technology, and agricultural intensification have increased yields over the past decades, however adverse climate conditions may prevent these gains from being fully realized in the future. Central Illinois in the Midwest United States is one such region where higher growing season temperatures have reduced soybean yields. While model estimates predict that future warming will contribute to further yield losses, there is uncertainty in these predictions. It is unknown if previously observed statistical correlations will remain reliable outside of the range in which data was collected. Observed soybean losses represent the combined effects of multiple mechanisms including reduced net carbon assimilation and altered development. Observation of yield and traits directly affected by heat stress under high growing temperatures is a crucial step in the development of crop models able to estimate yields under future warming scenarios. This thesis used an open-air field study to observe the direct effects of heat stress on various soybean traits and identified mechanisms that constrained yields under high-temperature conditions. The T-FACE method used in this project simulates field growing conditions more accurately than controlled environments and is the most advanced system for studying the effects of high temperature on plants. This project was carried out at the SoyFACE research facility in Champaign, Illinois. Commercial soybean varieties from maturity groups (MG) 3.6 and 4.2 were planted under ambient conditions and four different elevated heat treatments (+1.5, +3.0, +4.5, +6.0 oC) from 2017-2019. Using a range of treatments enabled us to identify threshold temperatures above which processes decline and determine if traits respond linearly or nonlinearly to growth temperature. The goal of Chapter 2 was to observe how soybean yield and yield traits changed in response to increasing temperature growth. Regression analysis was performed using the 24-hour season average canopy temperature. Yield and harvest index decreased non-linearly when temperatures exceeded 22 oC. Seed size decreased linearly with increasing temperature while seeds per pod and seeds per plant decreased non-linearly when temperatures exceeded 22 and 22.8 oC respectively. Yield losses were caused by reduced seed size and quantity since above-ground biomass did not significantly change with temperature. Air temperatures at the project site were warmer than historic averages and yields decreased under even the mildest (+1.5 oC) heat treatment. This observation suggests that further warming will be detrimental to soybean yields in central Illinois. The goal of Chapter 3 was to determine if changes in net carbon assimilation contributed to reduced yield. Photosynthetic capacity (normalized to 25 oC) was measured during all three growing seasons. Optimal photosynthetic temperature and dark respiration were observed during 2018 and 2019. Regression analysis was performed using the average canopy temperature from two weeks prior to measurements. There was little to no change in photosynthetic capacity with increasing canopy temperature. Photosynthetic optimal temperatures were higher than average daytime temperatures during the two-week period. Dark respiration rates were the same or reduced in leaves grown under elevated temperature conditions compared to ambient leaves, indicating that leaves had acclimated to their growing environment. There was no evidence that net carbon assimilation was reduced under high-temperature conditions. The goal of Chapter 4 was to determine if changes in development contributed to reduced yield. During all three seasons, vegetative and reproductive development were scored and pods on mid-stem nodes were counted every 2-3 days. Leaf area index (LAI) was measured weekly. Plants grown under mildly elevated (+1.5 and +3.0 oC) heat treatments had more stem nodes while response at higher treatments varied between MGs. More stem nodes did not increase LAI or seed mass per plant. As canopy temperatures during vegetative development increased, leaf area index increased more slowly and achieved a lower season maximum. LAI during reproductive development was significantly reduced in stages R1 (beginning flowering) through R6 (full seed). Rates of pod abortion per node did not change with canopy temperature during reproductive development, however the number of pods initiated per node and mature pods per node both significantly decreased as temperature increased. Declines in both pods initiated and mature pods indicates that both flower and pod development were impaired under high-temperature conditions. The research presented in this dissertation helps identify mechanisms that constrain soybean yield under high-temperature conditions. Yield data from this experiment can further our understanding of soybean yield response to high temperatures. LAI and development of reproductive structures were impaired under high-temperature conditions. Consequently, plants absorbed less solar energy during reproductive development and less biomass was partitioned as seed. Both factors reduced yield and harvest index as temperature decreased, despite no significant change in above ground biomass. The data from this project will aid in the development of process-based crop models to predict yields more accurately under warming scenarios. Identification of heat-sensitive traits is a crucial step in the development of crop models to accurately predict soybean yields under future warming scenarios.
Issue Date:2021-04-18
Type:Thesis
URI:http://hdl.handle.net/2142/110817
Rights Information:Copyright 2021 Charles Burroughs
Date Available in IDEALS:2021-09-17
Date Deposited:2021-05


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