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Earlier this year we sat down with a food company’s sustainability team and went through their soil carbon removal factors against LSRS, requirement by requirement. By the end they had a clear list of what was missing and what to collect next season. (And a lot more questions for us, which is always a good sign.) On 18 November we’re doing the same thing in public. Pablo Nicolas Ayala Espinoza and I will take an example company, open up its Scope 3 inventory and run the gap assessment live. Boundaries, carbon pools, data, uncertainty, double counting, monitoring. If something doesn’t hold up, you’ll see it. If your company has an SBTi FLAG target and plans to report removals, spend this hour with us before your next reporting cycle. 18 November, 8am PT / 11am ET / 5pm CET Register here: https://luma.com/v5xdlv1s

Can the soil carbon removals in your Scope 3 inventory be reported under the GHG Protocol’s Land Sector and Removals Standard (LSRS)? For food and agriculture companies relying on soil carbon removals to support their climate targets, including SBTi FLAG, this is becoming an increasingly important question. The LSR Standard takes effect on 1 January 2027. On 18 November, Juan Diego Carluccio and Pablo Nicolas Ayala Espinoza will run a live gap assessment using a representative company’s soil carbon removals accounting. It’s the same exercise we run with food and agriculture companies: • Start with the company’s Scope 3 inventory and existing soil carbon quantification data. • Assess the key LSR Standard requirements, including traceability, data quality, uncertainty and monitoring. • Identify gaps that could affect removals reporting and explain what evidence or improvements are needed to address them. JD is our VP of Commercial. Pablo is our Director of Carbon Policy and a former lead GHG auditor at SustainCERT. They’ll leave time for Q&A, so bring your questions. Wednesday 18 November, 8am PT / 11am ET / 5pm CET. https://luma.com/v5xdlv1s

What does the Greenhouse Gas Protocol's new Land Sector and Removals Guidance mean for food and beverage companies and partners across their value chains? We co-hosted a webinar with HowGood to walk through: Key takeaways from the guidance and what it means for your GHG inventory • How to manage accounting and substantiation for removals • Different approaches to quantifying soil organic carbon • How to get started and steps to take as you advance • Requirements to consider now to ensure alignment Watch the on-demand recording to learn more.

Uncertainty deductions below 5% for large, long-term soil carbon projects and below 10% for most projects over five years. Uncertainty that keeps decreasing as projects scale — without proportionally increasing sampling. That's what our team found in their latest peer-reviewed study on digital soil mapping for MRV in carbon markets. Earlier this year we shared a Bayer validation study, which showed we can achieve low uncertainty at a point in time with sparse sampling. A fair question came up: what about change over time? This paper addresses that. It presents our full end-to-end framework for quantifying SOC stock change, and simulates what uncertainty deductions would look like across different project sizes and durations. For developers, the implications are straightforward — lower uncertainty deductions mean more creditable tons and better project economics. It's the first peer-reviewed paper to apply the methods in Verra's VT0014 to assess change over time with digital soil mapping. And it makes Perennial, as far as we know, the only MMRV company whose digital soil mapping approach has been peer-reviewed. We decided early on to put our methods through peer review — this is the third paper our team has published on DSM. The process is slow, it invites criticism, and nobody's asking us to do it. But if your technology underpins carbon credits, I think the science should hold up to independent scrutiny. The study was led by Alexandre Wadoux at James Cook University alongside our Chief Scientist Jim Kellner. Grateful to them and the full team behind this work: Mitchell Donovan, Peng Fu, Nicholas Leach, Julia Maddalena, Rose Rustowicz, and David Schurman. https://lnkd.in/eAu2n9Xq

In validation studies with Bayer, we reduced uncertainty despite a 37x reduction in sampling density as we scaled from 700 to 53,000 acres. At the same scale with a 15x reduction in sampling density, uncertainty barely moved (just 0.03%). The takeaway: with our digital soil mapping model, beyond a certain threshold, additional samples yield diminishing returns. Scale is a far bigger lever. It's one thing to say you can reduce soil sampling while achieving low-uncertainty SOC quantification. It's another to put your model through years of validation with one of the world's largest agricultural companies — and share the results publicly. That's what we're doing today. (Link in comments.) The studies started in 2023 with blind validation — Bayer shared only field boundaries, holding back thousands of measured soil samples for comparison. Over time, they incrementally released subsets of that data, allowing us to fine-tune ATLAS-SOC, Perennial's digital soil mapping model, and observe how accuracy and uncertainty changed with each step. Across two phases — a 700-acre pilot and a 53,000-acre scale-up — Bayer compared ATLAS-SOC predictions against more than 10,000 measured soil samples. In the second phase, project-level uncertainty held near 0.5% (0.52%-0.55%) even as sampling density decreased from 1 sample every 7 acres to 1 sample every 106 acres. At 53,000 acres, uncertainty was half of what it was at 700 acres — with 37x lower sampling density. For project developers and sustainability teams, the implications directly impact project economics. If you're sampling densely, there's a path to reducing sampling — and by extension costs and complexity — while maintaining or even lowering uncertainty. If you're already sampling sparsely but facing high uncertainty, a strong digital soil mapping model can make the most of your existing samples, enabling you to lower uncertainty without increasing sampling. The studies shared today are from 2023 and 2024. Our model has continued to improve since, we're testing at lower sampling intensities now, and we look forward to sharing more in the future. Grateful to Cornelius Streit, Anna Bickel, Ross Bricklemyer, Felipe Schadeck Fiorentin, and the Bayer | Crop Science team for the scientific rigor and collaboration they brought to every phase. And proud of our science and engineering teams, whose work speaks for itself in studies like this.

Improve Scope 3 data across your global sourcing portfolio with a single, scalable solution. Get IPCC Tier 3 data while minimizing soil sampling, costs, and disruptions to farmers.