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Impact claims without evidence are marketing. MRV — Measurement, Reporting, and Verification — is the system that converts farm activity into verifiable, tamper-proof records that anyone can audit. It is the trust layer of the Kokonut Framework: the reason a grant reviewer, a DAO member, or a data scientist can look at Adelphi’s output numbers and trust them, rather than taking the Core Team’s word for it. Every significant farm event in the Kokonut Network — an MRV submission, a harvest milestone, a funding approval, an impact report — is designed to produce an on-chain EAS attestation: a cryptographically signed, permanent record anchored to Gnosis Chain or Base. The data pipeline runs from soil probe to satellite imagery to the Farm Registry API to an immutable on-chain record, queryable by anyone. At Adelphi, this pipeline is live. Farm data flows to hub.kokonut.network/projects/41 in real time.

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The three-tier monitoring stack

Kokonut’s MRV methodology operates across three complementary sensing tiers. Each one captures what the others cannot — satellite imagery misses ground-level soil chemistry; soil probes miss landscape-scale vegetation patterns; community analytics capture agronomic judgment that sensors cannot encode.

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On the ground sensing

Soil moisture probes are installed across the farm to provide continuous subsurface readings across three dimensions:
  • Volumetric Water Content (VWC): Determines the amount of water present in the soil relative to its total volume — providing accurate measurement of moisture levels across different soil layers and flagging irrigation needs before they become visible above ground.
  • Electrical Conductivity (EC): Measures the soil’s ability to conduct electricity, the primary proxy for soil salinity and nutrient availability. Rising EC over time indicates salt accumulation; declining EC after biochar application indicates improving nutrient retention.
  • Soil Temperature: Records soil temperature in °C — a critical variable for biological and chemical processes affecting plant growth, germination timing, and microbial activity in the root zone.
Probe readings feed directly into the ground field of each MRV payload submitted to the Farm Registry API.

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Remote sensing

Satellite imagery from Landsat 8 and Sentinel provides landscape-scale vegetation health data at regular intervals — Sentinel overpasses every 5 days at 10m resolution. Drone surveys with Pix4Dcapture supplement satellite passes at higher spatial resolution for specific plots.

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Vegetation index selection guide

Four indices are used, each suited to a specific crop condition. Index selection is not arbitrary — applying the wrong index at the wrong crop stage produces misleading readings.
IndexFormulaWhen to apply
NDVI(NIR − RED) / (NIR + RED)Throughout the production season as the primary vegetation health baseline. The most widely used index in remote sensing — accurate when canopy cover is established. Avoid during early establishment when bare soil exposure is high.
ReCI(NIR / RED) − 1During the active vegetative development phase. Responds directly to chlorophyll concentration — a proxy for nitrogen availability. Use when growth rate and leaf color are the key monitoring variables.
NDRE(NIR − RED_EDGE) / (NIR + RED_EDGE)During the crop maturity phase, when the canopy is closed and NDVI begins to saturate. More sensitive than NDVI to chlorophyll variation in dense, closed-canopy crops.
MSAVI(2 × Band4 + 1 − √((2 × Band4 + 1)² − 8 × (Band4 − Band3))) / 2At the beginning of the crop production season when seedlings are establishing and bare soil exposure is highest. Designed specifically to minimize soil background interference on crop health readings.
Normalized Difference Vegetation Index: The most common vegetation index in remote sensing. Applied throughout the crop production season as the baseline health indicator.
Formula: NDVI = (NIR – RED) / (NIR + RED)
Values range from −1 to +1. Dense, healthy vegetation approaches +1. Bare soil clusters near 0. Water bodies are negative. A declining NDVI trend over successive satellite passes is an early warning of drought stress, disease, or nutrient deficiency — before visible symptoms appear.

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From measurement to verification — the EAS pipeline

Collecting data is a measurement. Submitting it to the Farm Registry is reporting. Making it verifiable means anchoring it on-chain so that no party — including Kokonut Network itself — can retroactively alter what was recorded. Every MRV submission follows this pipeline:

Data collected

Ground probe readings, satellite vegetation indices, and community field logs are assembled into a structured MRV payload matching the KokonutMRVPayload schema — farm_id, timestamp, measurement_type, and the relevant tier object (ground, remote, or community).

Payload pinned to IPFS

The full MRV payload is pinned to Filecoin/IPFS before submission. The returned content identifier (CID) is immutable — the same data will always produce the same CID, and the CID cannot be generated from different data. This is the content address that the on-chain attestation will reference.

Submitted to Farm Registry API

The payload is submitted to POST /farms/{farm_id}/mrv on the Farm Registry API. The API returns a mrv_id UUID and sets is_attested: false — The event is recorded but not yet verified.
// MRV payload structure
{
  farm_id: "adelphi",
  timestamp: "2025-06-01T09:00:00Z",
  measurement_type: "remote",
  remote: {
    ndvi: 0.71,
    reci: 3.84,
    ndre: 0.42,
    msavi: 0.63,
    source: "sentinel",
    image_url: "ipfs://bafybei..."
  }
}

EAS attestation created on-chain

After the MRV event is recorded, an EAS attestation is created on Gnosis Chain or Base — encoding the farm_id, event_type, ipfs_cid, impact_score, attestor_role, and timestamp. The attestation is cryptographically signed by the attestor wallet and anchored permanently on-chain. The attestation UID is then submitted to POST /farms/{farm_id}/attestations, linking the on-chain record to the Farm Registry event. The MRV event is updated to is_attested: true and becomes immutable.

Data appears on the Data Hub

Once attested, the MRV event appears in the farm’s public record at hub.kokonut.network/projects/41 — queryable by anyone, traceable to the on-chain attestation, and permanently part of the farm’s verifiable impact history.
The Kokonut × AI Agents page documents how this pipeline is being automated — AI agents ingesting satellite data, calculating vegetation indices, submitting to the Farm Registry API, and creating EAS attestations automatically on each Sentinel overpass cycle, removing the manual bottlenecks that currently limit MRV frequency.

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Ecological impact tracking

Kokonut tracks and reports on environmental and social impacts using the EBF Framework for Environmental and Social Impact Reports. Impact is measured across four GHG and ecological dimensions, with methodologies specific to Kokonut’s farm operations.
Why it matters: Methane has approximately 80 times the warming potential of CO₂ over 20 years. Agricultural methane sources include livestock digestion and poorly managed manure. Kokonut methodology:
  • Using seaweed-based organic fertilizers (seaweed supplementation has shown significant methane reduction in ruminant digestion)
  • Collaborating with local farmers to incorporate seaweed into cow feed as a methane-reduction intervention
  • Free-range poultry management at Adelphi — poultry manure is processed into humic acids and organic urea rather than stored in anaerobic conditions that produce methane

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Annual reporting

MRV data aggregates into annual impact reports across four dimensions, aligned with the EBF Framework and queryable via the Farm Registry API’s /impact endpoint.
DimensionWhat is measuredKey metrics
EnvironmentalEcological health and carbon performanceAnnual carbon sequestration rates (t CO₂e/acre), NDVI averages across the growing season, changes in local biodiversity indices, MRV event count
EconomicFinancial impact on farmers and communitiesGross revenue, public goods allocation distributed (10% of revenue), jobs created and sustained, household income changes
SocialCommunity wellbeing and capacityCommunity workshops held, participants trained, women in leadership roles, educational program reach
SustainabilityLong-term resilience across all 8 forms of capitalAnnual sustainability audit across Natural, Financial, Social, Human, Material, Intellectual, Cultural, and Health capital; organic certification status; SDG attestations
Annual reports for Adelphi are published to hub.kokonut.network/projects/41. Historical MRV records, harvest forecasts, and aggregated impact metrics are all publicly available and traceable to their on-chain EAS attestations. This information enables more efficient and sustainable management of irrigation and nutrients — improving both crop yields and the conservation of natural resources across every farm in the network.

Kokonut × AI Agents

How AI agents automate the MRV pipeline — from satellite ingestion to EAS attestation — removing the manual bottlenecks that limit reporting frequency.

Ecological Impact Frameworks

The EBF Framework and CRISP carbon risk scoring methodology that underpin Kokonut’s annual impact reports.

Build with Kokonut

The Farm Registry API — MRV payload schema, attestation endpoint, and impact aggregation queries for developers and the Impact Guild.

Adelphi Data Hub

Live MRV data, harvest records, and impact metrics for Adelphi — the canonical reference implementation of this entire methodology.