Frequently asked questions.

Hypocotyl is a carbon intensity (CI) measurement platform for agriculture. We produce farm-specific CI scores — expressed as kg CO₂ equivalent per kg of grain — using a transparent, documented methodology. Think of us as data infrastructure: the layer that connects farm practice data to credible, auditable CI outputs that buyers and programs can rely on.

No. Hypocotyl measures and reports carbon intensity. We do not generate, sell, or manage carbon credits. If you're pursuing a carbon credit program, CI data from Hypocotyl may be relevant input, but Hypocotyl itself is a measurement and data infrastructure product, not a carbon market.

In plant biology, the hypocotyl is the early stem that connects the seed to the seedling — enabling the plant to emerge and establish itself. Our name reflects our purpose: connecting on-farm data and practices to credible, transparent carbon intensity measurement, so farmers can prove impact and access market value.

We are initially focused on the Canadian grain and oilseed sector, with particular focus on the Prairie provinces. We are monitoring developments in the US and international markets and expect to expand methodology coverage as the platform matures.

The core inputs are: fuel use by field operation (diesel/gas), nitrogen fertilizer type and application rate, tillage system and pass count, crop yield, and field location/size. Additional inputs like other fertilizer products, chemical applications, and grain drying energy improve data completeness and CI score accuracy. Most producers can pull this from existing records — agronomy notes, input receipts, or farm management software.

For a single field with typical data available, initial data entry is designed to take under 30 minutes. For multi-field operations, time scales with the number of fields. Where farm management software integrations are available, data entry time is reduced further.

A CI score for your operation expressed in kg CO₂e per kg of grain, with benchmark context (regional average, national average, program baseline), a boundary statement, a data completeness percentage, and a confidence range. The output is formatted for sharing with buyers, agronomists, or program administrators.

No. We measure and report — we do not prescribe management decisions. If you want to understand how specific practice changes might affect your CI, we can discuss that in a demo context, but agronomic decisions are yours to make.

Only you, until you choose to share your CI report with a buyer or program. We do not share individual farm data with third parties. Benchmarking uses aggregated and anonymized data only. See our Privacy Policy for full details.

No. A lower CI score is a prerequisite for participating in many low-carbon programs and buyer preferences — but whether a premium is available, and at what level, depends on market conditions and specific program criteria. Hypocotyl produces the data. Premium decisions sit with buyers and program administrators.

Scope 3 Category 1 (Purchased Goods) is the largest and most uncertain part of most food company emissions inventories. Hypocotyl provides field-level CI data that replaces national or regional emission factor estimates for purchased grain with measured, farm-specific values. The structured output format is compatible with GHG Protocol agricultural guidance.

That is the intent. CI reports include a boundary statement, confidence range, data completeness metric, and methodology version reference — the elements needed for a document to survive procurement due diligence. We recommend having your procurement and legal team review specific use cases.

We work with buyers to onboard producer partners into the Hypocotyl network. This includes a practical onboarding process for producers, data collection support, and integration of results into buyer-facing reporting. Contact us to discuss your supplier network and timeline.

Initial methodology development is focused on canola, wheat, corn, and soybeans in the Canadian Prairie provinces and Ontario. Additional crops and regions will be added as the methodology and producer network expands.

We use a life cycle assessment (LCA) aligned approach, covering emissions from farm inputs (fuel, fertilizer, chemicals) and on-farm operations through to the farmgate. Emission factors are sourced from recognized scientific literature including ECCC National Inventory Reports, IPCC 2006 Guidelines, and the Ecoinvent database. Every factor has a reference.

It means the CI score covers all emissions from the production of inputs (fertilizer manufacture, fuel extraction) through to the point the grain leaves the farm. It does not include downstream transport, processing, or food manufacturing. Exclusions are explicitly noted on every output.

Data completeness reflects the proportion of the total CI calculation that is based on actual farm-reported data versus published default values. A score based on 90% actual data has a tighter confidence range than one based on 60%. Both the completeness percentage and the resulting confidence range are reported on every output.

Yes — and this is disclosed upfront. Agricultural carbon science is developing rapidly. We use a version-controlled methodology with a transparent change log. Every CI output references the methodology version used, so historical scores remain auditable even as the methodology evolves.