Key Takeaways:
- Perennial introduces VT0014, the first AI-powered soil carbon quantification tool approved for use in Verra’s Verified Carbon Standard (VCS) Program.
- Tool reduces the burden of soil sampling, enabling rigorous quantification in remote or data-scarce areas.
- Built on Perennial’s ATLAS-SOC model, which integrates over 350,000 soil samples with machine learning and biogeochemical predictors.
- Adoption expected to expand carbon market access, regenerative project financing, and sustainability initiatives.
- Early partners include Bayer, rTek, Anthesis, and Cool Path, with projects spanning millions of acres worldwide.
Perennial Advances Carbon Market Access with AI Technology
Perennial, a provider of measurement, monitoring, reporting, and verification (MMRV) solutions, announced the release of VT0014, an AI-powered soil carbon quantification tool now approved by Verra for use in its Verified Carbon Standard (VCS) Program. The tool enables digital soil mapping under Agricultural Land Management (ALM) methodologies, providing an alternative to traditional soil sampling.
“This tool is a quantum leap forward in soil quantification,” said David Schurman, co-founder and Chief Product Officer at Perennial. “Not only does it lower barriers for MMRV in areas where projects are already underway, it unlocks new regions, new carbon projects and new opportunities for climate finance.”
How Digital Soil Mapping Works
Digital soil mapping combines localized soil samples with AI-powered models to scale carbon measurement across fields and regions. Perennial’s ATLAS-SOC model has integrated more than 350,000 soil samples, refining predictions by training on strategically selected local datasets.
For each project, the model generates hundreds to thousands of data points beyond what traditional sampling can provide. By reducing the number of samples required, this approach lowers measurement costs, improves accuracy, and minimizes on-farm disruptions.
Verra Approval and Industry Significance
VT0014 is approved for use under several Verra ALM methodologies, including VM0042 for Improved Agricultural Land Management and VM0032 for Sustainable Grasslands. The tool establishes consistent standards for model selection, calibration, and validation throughout the project lifecycle.
“Digital soil mapping is critical to reducing the costs associated with the implementation and scaling up of Agricultural Land Management projects,” said Mandy Rambharos, CEO of Verra. “This scalable solution will strengthen access to soil carbon markets for farmers and ranchers worldwide, while ensuring the highest standards of integrity and transparency.”
Partnerships and Early Implementation
A range of leading organizations have committed to adopting Perennial’s technology, including Bayer, rTek, Anthesis, and Cool Path. These projects span continents and aim to unlock financial benefits for thousands of farmers managing millions of acres of agricultural land.
“After extensive validation studies, we chose Perennial as one of our global MMRV partners due to their exceptional ability to deliver precise results with minimal sampling,” said Leo Bastos, Senior Vice President at Bayer. “This partnership positions us at the forefront of agricultural innovation, empowering us to better reward farmers for their stewardship of the land.”
One early example is rTek’s project to regenerate 500,000 hectares of degraded grasslands in Kazakhstan, now eligible to access carbon markets under Verra’s VM0032 methodology.
Unlocking Regenerative Agriculture at Scale
The Food and Agriculture Organization of the UN estimates that soils could sequester roughly a tenth of manufactured carbon emissions over 25 years. By lowering the barriers to accurate soil carbon measurement, Perennial’s VT0014 aims to accelerate the adoption of regenerative agriculture practices and expand participation in global carbon markets.
The company’s stated vision is to enable regeneration of 100 million acres worldwide by aligning scientific innovation with climate finance and farm-level outcomes.
