2023
Carbon Cycling in Soybeans
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Contributor/Checkoff:
United Soybean Board
Category:
Sustainable Production
Keywords:
Sustainability
Parent Project:
This is the first year of this project.
Lead Principal Investigator:
Matt Rohlik, Arva Intelligence Corp.
Co-Principal Investigators:
Project Code:
23-201-S-A-1-A
Contributing Organization (Checkoff):
United Soybean Board
$306,675
Institution Funded:
Arva Intelligence
$306,675
Brief Project Summary:
By employing one eddy covariance tower combined with greenhouse gas chambers in participating soybean fields, we will create the most thorough carbon cycling study in soybeans to date which can be used to increase the value and marketability of sustainably grown soybeans and generate new revenue streams for soybean farmers from environmental offset markets. This project can be scaled up or down based on the needs of the United Soybean Board. Arva Intelligence is a technology B-corp with an established farmer-facing platform that leverages machine learning-based data analytics to help farmers identify and implement regenerative practices. Arva’s artificial intelligence modeling optimizes for efficiency, profitability, and the creation of nature-based environmental assets that can supply the carbon offsets market as well as the climate-smart agricultural commodities market.
Information And Results
Project Summary

Project Objectives

Project Deliverables

Progress Of Work

Final Project Results

Arva's goal was to understand the linkages between soil edaphic factors, environmental contexts, and soil gas fluxes in soybeans. We found dramatic differences between certain gasses and stages of plant growth, as well as CEC, Organic Matter, and pH influence on GHG flux. This data begins to enable a predictive model go GHG in soybeans as a function of soil contexts.

Benefit To Soybean Farmers

The results of this project lay the foundation for understanding how carbon and greenhouse gas fluctuations occur in soybeans. By integrating this data with field data in an AI platform like Arva's, we can begin to predictively model the GHG influence of a particular crop and field combination, empowering US Soybean Farmers to accurately predict the environmental impact of their soybean crops and generate new revenue streams through environmental asset programs or lower carbon intensity scores for forthcoming sustainable biofuel production.

The United Soybean Research Retention policy will display final reports with the project once completed but working files will be purged after three years. And financial information after seven years. All pertinent information is in the final report or if you want more information, please contact the project lead at your state soybean organization or principal investigator listed on the project.