Effects of increased atmospheric CO2 and abiotic stress on soybean performance in the Enviratron
By Steve Whitham, professor of plant pathology and microbiology, Lie Tang, professor of agricultural and biosystems engineering and Danny Singh, professor of agronomy, ISU
The goals of this project are to investigate the performance of soybean under future climate scenarios with respect to disease development and abiotic stress tolerance. The long-term goal of this research is to inform forward-looking breeding approaches to develop soybean germplasm well-suited for future production environments. This project utilizes the Enviratron, a unique controlled environment plant growth facility developed at ISU to enable multiple environmental variables to be studied for effects on plant performance. Up to eight different conditions can be tested in a single experiment. The Enviratron is also unique in that data collection is automated by the use of a robotic rover that visits the plants in the growth chambers and collects data using its array of cameras and sensors that includes RGB, 3D, hyperspectral, and thermal imaging, and a fluorescence probe that collects data related to photosynthetic activity.
Objective 1: Studying the effects of CO2 on soybean responses to pathogens in the Enviratron
The projected average atmospheric CO2 concentration is expected to increase from the May 2020 level of approximately 417 parts per million (ppm) to 500 –550 ppm by 2050. A 25% increase in CO2 levels is expected to have significant effects on soybean performance, and we are interested in how interactions with plant pathogens may be affected, either positively or negatively. We have several questions related to soybean-pathogen interactions under current and future climate scenarios that we will address using the unique capabilities of the Enviratron. We expect that answering these questions will provide insight into strategies needed to manage diseases. In parallel, we seek to further develop image analysis capabilities by automating the process of detecting diseased plants in real time utilizing the images collected by the robot. We expect that our approaches for automating disease detection in real time in the Enviratron can lay the groundwork for field applications in the future. Therefore, this project pursues important biological and technological goals related to soybean-pathogen-environment interactions and automated data analysis that provides an output that can be acted upon.
Objective 2: Studying the effects of elevated ambient temperatures on soybean gene expression in the Enviratron
Climate change is predicted to bring about rising global temperatures, including in the temperate regions where soybeans are heavily cultivated. Presently, the IPCC predicts an increase in ambient temperature anywhere from 1-4⁰C, with this range being partially dependent on the rate of increase in atmospheric CO2 concentrations. In addition to rises in the average temperature, current climate predictions for the end of the century also indicate an increased frequency and duration of extreme weather events such as heat waves and droughts. The combination of increased average temperature and frequency of heat waves means that in the coming decades soybeans are increasingly likely to encounter higher ambient temperatures resulting in higher incidences of heat stress. Two international groups of scientists independently simulated a 2⁰C rise and found that the United States, China, southern Brazil, and Russia had higher chances of increased heat stress for soybeans.
Present research in soybean heat tolerance is primarily limited to quantifying yield losses due to heat stress during the reproductive phases of growth. In all plant species, the reproductive growth stages generally are the most sensitive growth stage to abiotic stress, such as heat. However, the response of younger soybeans still in vegetative growth holds potential information on genotype specific heat tolerance on the physiological and molecular levels, and are also critical as early season stress can impact the yield potential. The response of any plant to heat stress is unique, with the possibility of many different aspects including effect on root anatomical traits, root microbiome, exudates, phytohormones, and genes involved and expressed. In soybeans, there has been multiple studies on the gene expression and molecular mechanisms of tolerance to drought stress. However, heat stress on this level in soybeans has barely been studied to date, and always in combination with drought stress. In our study, we will initiate our project on heat stress with the possibility extend to drought stress within the grant duration.
This proposed work complements our existing (and on-going) effort to study a large soybean accession panel (>400 varieties) for heat stress in a factorial experiment (high temperature, versus control). This large germplasm screening will identify a smaller, select set of varieties for a thorough investigation of heat stress in Enviratron, to build on our existing efforts to combine the above-and below-ground traits with novel insights on microbiome, exudates, and phytohormones. This work will lead to an understanding of microbial diversity and potential identification of gene candidates, plant growth promoting microbes, and metabolites with the study of diverse soybean genotypes subjected to heat stress. Additionally, the cameras and sensors of the robotic rover provides the potential for developing automation of stress phenotyping. We emphasize that we will initially focus on heat stress as the abiotic factor, but will keep water stress as a potential extension, time and resource permitting.
1.Understanding of how increased atmospheric CO2affects development of diseases caused by viruses, bacteria, and fungi in soybean.
2.Image analysis approaches for automated detection of diseased and heat stressed soybean plants.
3.Comprehensive understanding of mechanisms of heat tolerance in soybean, as well as study of microbiome specific to heat stress response.
4.Linking of information on heat stress from an on-going heat stress screening for a breeding objective with Enviratron experiment, which allows for more standardized soybean heat stress testing.
5.Knowledge of appropriate plant growth stage and suitable sensors for heat stress screening in eventual field studies.
We are excited about the prospect of leveraging Enviratron for CO2 and heat stress screening for disease protection and yield enhancement aspects, respectively.
Selected for funding October 2021