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ARS Home » Midwest Area » Urbana, Illinois » Global Change and Photosynthesis Research » Research » Research Project #442676

Research Project: Identifying Key Targets for Soybean Seed Protein Concentration Improvement by Creating A Virtual Soybean Model

Location: Global Change and Photosynthesis Research

Project Number: 5012-21000-032-003-R
Project Type: Reimbursable Cooperative Agreement

Start Date: Oct 1, 2022
End Date: Mar 31, 2024

Objective:
The objective is to identify biochemical processes and genes related to protein concentration in soybean seeds, with the long-term goal of finding new approaches to aid soybean breeding to improve meal quality.

Approach:
We have developed a basic nitrogen uptake and distribution model trained using data from a hydroponics experiment. Currently, the nitrogen model is independent of a growth model, and we will integrate it into the crop growth model (BioCro II). In order to train and validate the combined model, we will perform an experiment that will also help address the question of whether recent declines in soybean seed protein concentration is due to reduced uptake or dilution by carbohydrates. To do this, we will grow old and new soybean varieties, which vary in the protein concentrations, and measure plant nitrogen content, yield, and canopy photosynthetic rate. From this, we can determine whether the total N uptake in new cultivars is equivalent to old cultivars and estimate the role of dilution by enhanced carbohydrate uptake. This also provides a useful data set to train and validate the combined model. Nitrogen content will be measured using an elemental analyzer or the Kjeldahl method depending on the sample type. Photosynthetic capacity will be measured using gas exchange instruments and tissue masses will be measured by harvesting, drying and weighing. Leaf area will be measured using a leaf area analyzer. Models will be written as a system of differential equations and parameterized using an algorithm that chooses parameter values that minimize the difference between observed and model predicted values. We will integrate the nitrogen uptake and distribution model into our crop growth model and validate the combined models by examining nitrogen uptake of old and new soybean varieties.