Optimizing soybean canopy architecture for efficient light and water use under climate change

Recipient Organization
UNIVERSITY OF ILLINOIS
2001 S. Lincoln Ave.
URBANA,IL 61801

Performing Department
(N/A)

Non Technical Summary
Increases in global mean temperatures, CO2 concentrations, variable precipitation and humidity are affecting crop water use efficiency (WUE). Recent studies have shown that soybean WUE decreases with increasing seasonal temperatures, despite gains from elevated CO2. It was also shown that soybean leaf shape and canopy architecture could influence light and water use efficiency. However, the complex interactions among [CO2], temperature, and soil moisture with variable canopy architectures have not been studied. We propose to address A1152 Program Area Priorities A and B by investigating the relationship among plant architecture, carbon assimilation, and WUE as they inherently relate to soybean productivity. The overall goal of this project is to predict optimal soybean canopy architecture for maximum light capture and WUE under future climate scenarios. Specific objectives include: 1. Create a digital soybean canopy with detailed 3D-geometry, illumination, and microclimate data. 2. Apply algorithms for the fast calculation of light distribution throughout the canopy under varying architectures and seeding strategies. 3. Perform integrative modeling to estimate the photosynthetic and WUE of soy canopies optimized for light capture under variable climate conditions. These objectives will be accomplished by developing, testing, and optimizing a digital twin that extends the idea of plant ideotypes into interactive, AI-based, 3D computer simulations using procedural modeling with an advanced light transportation model. Model outputs will inform short-term recommendations involving selection and management strategies, as well as long-term recommendations for targeting structural traits with genetic modification.

Animal Health Component

50%

Research Effort Categories

Basic

50%

Applied

50%

Developmental

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
206	1820	1060	100%

Knowledge Area
206 - Basic Plant Biology;

Subject Of Investigation
1820 - Soybean;

Field Of Science
1060 - Biology (whole systems);

Keywords

Goals / Objectives
The long-term goal of the project is to predict optimal soybean canopy architecture for maximum light capture and water use efficiency under future climate scenarios, and the optimal distribution of resources within that canopy.Supporting Objectives:Collect detailed 3D geometry and illumination data to reconstruct a soybean canopy digital twin.Reconstruct and enable the digital twin to be simulation ready and to respond to varying environmental conditions.Apply algorithms for the fast calculation of light distribution throughout the canopy under varying architectures and seeding strategies.Perform integrative modeling to estimate the photosynthetic and water use efficiency of soy canopies optimized for light capture.Develop an interactive application with an intuitive GUI that will allow the creation and testing of "what-if" scenarios by modifying the environment and distribution of resources determining photosynthesis at the leaf level.

Project Methods
1. Create a soybean canopy digital twin with detailed 3D geometry and illumination data.2. Reconstruct and enable the digital twin to be simulation ready, have a controllable shape, and be responsive to time (development).3. Apply algorithms for the fast calculation and optimization of light distribution throughout the canopy under varying architectures, environments, and seeding strategies.4. Perform integrative modeling to estimate the photosynthetic and water use efficiency of soy canopies optimized for light capture. ?5. Create an interactive application with a simple and intuitive GUI that will allow the creation and testing of "what-if" scenarios by modifying the environment and running simulations.

Progress 07/01/24 to 06/30/25

Outputs
Target Audience:The target audience for this research is computational biologists and modelers interested in optimization of light within canopies. Changes/Problems:The PI on the project sadly passed away in 2025. The head of the Plant Biology department at the University of Illinois asked a collegue (Ainsworth) to step in as PI and help supervise the graduate student active on the project. The new PI has met regularly with the graduate student and resumed project meetings with the co-PIs. What opportunities for training and professional development has the project provided?One graduate student at the University of Illinois has been trained on this project. He has learnedtechniques for plant physiological analysis and has presented his research findings in a group lab meeting setting. How have the results been disseminated to communities of interest? Nothing Reported What do you plan to do during the next reporting period to accomplish the goals?The original PI on this project passed away in 2025. A new PI at the University of Illinois has stepped in to help with the data collection and plant physiological analysis. The PI team resumed regular project meetings in August 2025 and plans are in place to sharedata between the experimentalists and modelers on the project.

Impacts
What was accomplished under these goals? Two soybean genotypes with variation in three dimensional shape were planted in replicated plots at two different plant densitiesat the University of Illinois Energy Farm. Soil moisture sensors, canopy temperature and relative humidity sensors, and light sensors were set up to collect continuous measurements for much of the growing season. These data are used to parameterize the Soybean Biocro model and a new three dimensional canopy twin being developed at Purdue University. Two sap flow sensor systems were set up to test water use and water use efficiency in the genotypes over the course of the summer. Those data are currently being analyzed.

Publications